KIT’s College of Engineering, Kolhapur. (An Autonomous Institute...
Transcript of KIT’s College of Engineering, Kolhapur. (An Autonomous Institute...
KIT’s College of Engineering, Kolhapur.
(An Autonomous Institute)
Department of Electronics Engineering
Teaching and Evaluation scheme for First Year M.Tech.
Program in Electronics& Telecommunication Engineering, Semester-I
Course Code
Subject Teaching Scheme Evaluation Scheme
L T P Credits Scheme Weightage
PETC0101 Next Generation Network System 3 1 - 4 Max Min Min
ISE-I 10 40 MSE 30
ISE-II 10
ESE 50 20
PETC0102 Engineering Linear Algebra 3 - - 3 ISE-I 10 40 MSE 30
ISE-II 10
ESE 50 20
PETC0103 Random Processes & Stochastic Process
4 - - 4 ISE-I 10 40 MSE 30
ISE-II 10
ESE 50 20
PETC01** Professional Elective-I 3 1 - 4 ISE-I 10 40
MSE 30 ISE-II 10
ESE 50 20
PETC01** Professional Elective-II 4 1 - 5 ISE-I 10 40
MSE 30 ISE-II 10
ESE 50 20
PETC0161 Research Methodology (Audit Course)
2 - - - ESE 100 40
PETC0131 Random Process& Stochastic Processlab
- - 2 1 ISE 50 20
ESE(OE) 50 20
PETC0132 Engineering Linear Algebra Lab - - 2 1 ISE 50 20
ESE(OE) 50 20 PETC0141 Seminar I - - 2 1 ISE 100 40
Total 17+ 2
3 6 23 Total Contact Hours/Week: 26+2Hrs
Total Credits: 23
Total Contact Hours/Week: 26+2Hrs Note: ESE: End Semester Examination, MSE: Mid Semester Examination, ISE: In Semester Evaluation.
KIT’s College of Engineering, Kolhapur. (An Autonomous Institute)
Teaching and Evaluation scheme for First Year M.Tech.
Program in Electronics & Telecommunication Engineering Semester-II
Course Code
Subject Teaching Scheme Evaluation Scheme
L T P Credits Scheme Weightage
PETC0204 RF and Microwave Circuit design 4 - - 4 Max Min Min
ISE-I 10 40 MSE 30
ISE-II 10
ESE 50 20
PETC0205 Software Defined Radio 4 1 - 5 ISE-I 10 40 MSE 30
ISE-II 10
ESE 50 20
PETC0206 Adaptive Signal Processing 3 - - 3 ISE-I 10 40
MSE 30 ISE-II 10
ESE 50 20
PETC02** Professional Elective III 3 1 - 4 ISE-I 10 40
MSE 30 ISE-II 10
ESE 50 40
PETC02** Professional Elective IV 4 1 - 5 ISE-I 10 40
MSE 30 ISE-II 10
ESE 50 20
PETC0262 Standards in communication systems(Audit)
2 - - - ESE 100 40
PETC0233 RF & Microwave Circuit Design Lab - - 2 1 ISE 50 20
ESE(OE) 50 20
PETC0234 Adaptive Signal Processing Lab - - 2 1 ISE 50 20
ESE(OE) 50 20
PETC0242 Pre Dissertation Seminar - - 2 1 ISE 100 40 PETC0243 Mini Project - - 2 1 ISE 100 40
Total 18+2 3 8 25 Total Contact Hours/Week: 29+2Hrs
Total Credits: 25
Total Contact Hours/Week: 29+2Hrs
Semester III
Course Code Subject Teaching Scheme Evaluation Scheme
L T P Credit Scheme Weightage
Max Min
PETC0343 Industrial Training
- - - 2 ISE 100 40
PETC0351 Dissertation Phase-I
- - - 2 ISE-I 50 20
4 ISE-II 100 40
PETC0352 Dissertation Phase-II
- - - 4 ESE(OE) 100 40
TOTAL - 12
Semester IV
Course Code Subject Teaching Scheme
Evaluation Scheme
L T P Credit Scheme Weightage
Max Min
PETC0453 Dissertation Phase- III
- - - 4 ISE III 100 40
- - - 4 ISE IV 100 40
PETC0454 Dissertation Phase-IV
- - - 8 ESE(OE) 200 80
Total 16
Course Code** Professional Elective-I Course Code** Professional Elective-II
PETC0121 Embedded System Programming PETC0124 Wireless Sensor Network
PETC0122 Fiber Optic Communication PETC0125 Radiating System
PETC0123 IOT Protocols & Application PETC0126 Optimization Techniques
Course Code** Professional Elective-III Course Code** Professional Elective-IV
PETC0221 Advances in Network Security PETC0224 RF IC Design
PETC0222 Adhoc Network PETC0225 Communication Protocol Design
PETC0223 Internet Traffic Engineering PETC0226 SoC Design and Verification
Kolhapur Institute of Technology’s College of Engineering, Kolhapur
Program Credit Distribution
Curriculum Component Credits
Professional Core 23
Professional Electives 18
Lab courses 4
Seminar and Mini Project 3
Industrial training 2
Dissertation 26
Total 76
23(31%)
18(24%) 4(5%)
2(3%)
2(3%)
26(35%)
Credits
Credit courses
Professional Electives
Lab courses
Seminar
Industrial training
Dissertation
Title of the Course: Next Generation Network Systems
Course Code : PETC0101
L T P Credit
3 1 - 4
Course Pre-Requisite: Computer Networks ,Wireless Networks ,Mobile Communication
Course Description: This course helps students to understand NGN along with new features.It will
help to learn technical, economic and service advantages of next generation networks. It will help to understand basic architecture of a next generation network (NGN) with reference to
mobile computing.
Course Objectives: 1. To learn the technical, economic and service advantages of next generation networks.
2. To learn the basic architecture of a next generation network (NGN) with reference to mobile computing
3. To learn the role of (IMS), network attachment and VoIP 4. To learn and compare the various methods of providing connection-oriented services over a
NGN with reference to MPLS, SMS and GSM
Course Learning Outcomes:
1. To be able to learn architecture of mobile computing and its design considertion. 2. To be able to compare emerging technologies of mobile computing over telephony and GSM.
3. To be able to learn SMS and GPRS features 4. To be able to compare various VoIP and IMS technologies
CO After the completion of the course the student
should be able to Bloom’s Cognitive
level Descriptor
CO1 Apply Design consideartions of mobile
computing methods
Application Cognitive
CO2 Classify emerging Technologies of mobile
computing over telephony
Complex
Response
Psychomotor
CO3 Differentiate SMS and GPRS features Application Cognitive
CO4 Apply VoIP and IMS applications Comprehension Cognitive
CO-PO Mapping:
CO PO1 PO2 PO3
CO1 2
CO2 1 2
CO3 3
CO4 3 3
Assessments :
Teacher Assessment:
Two components of In Semester Evaluation (ISE), One Mid Semester Examination (MSE) and one EndSemester Examination (ESE) having 20%, 30% and 50% weights respectively.
Assessment Marks
ISE 1 10
MSE 30
ISE 2 10
ESE 50
ISE 1 and ISE 2 are based on assignment/declared test/quiz/seminar/Group Discussions etc. MSE: Assessment is based on 50% of course content (Normally first three modules)
ESE: Assessment is based on 100% course content with60-70% weightage for course content
(normally last three modules) covered after MSE.
Course Contents:
Unit 1:--- Global System for mobile Communication(GSM)
GSM architecture, GSM entities, call routing in GSM, PLMN interface, GSM addresses and identifiers, network aspects in GSM,GSM frequency allocation,
authentication and security.
-6- Hrs.
Unit 2:--- General Packet Radio Service (GPRS)
General packet radio service(GPRS) GPRS and packet data network, GPRS
network architecture, GPRS network operation, data services in GPRS, Applications of GPRS, Billing and charging in GPRS
-7- Hrs
Unit 3:--- IS 95 & WLAN
IS 95- Architecture,Channel Structure, Call Processing,Channel Capacity, Wireless LAN Architecture- Types, Adhoc and Infrasture Mode, Deploying
wireless LAN
-8- Hrs.
Unit 4 - Wireless Application Protocol
WAP, WAP Application Enviroment, Wireless Session Protocol,MMS- Architecture, Transaction Flow
-7- Hrs.
Unit 5:--- Voice over IP and IMS
Voice over IP,H.323 framework for voice over IP,SIP,Real time Protocol,Call Routing – SIP to PSTN to SIP, IMS
-6- Hrs.
Unit 6 – Security Issues
Attacks, Symmetric Key Cryptography, DES, Public Key Cryptography, Security
Protocols
-6- Hrs
Textbooks:
1. Mobile Computing , Asoke K Telukder, Roopa R Yavagal, TMH
2. Mobile Communications, Jochen Schiller, Pearson
References:
1.Next Generation Telecommunications Networks, Services, and Management by Thomas Plevyak,
VeliSahin, ISBN: 978-0-470-57528-4 , Wiley-IEEE Press 2. Next Generation Wireless Systems and Networks: Hsiao – Hwa Chen, Mohsen Guizani – Wiley
Unit wise Measurable students Learning Outcomes:
Unit1
UO1: Student should be able to understand basic concepts of Mobile Computing and architecture Unit2
UO2: Student should be able to understand different emerging Technolgy Unit3
UO3: Student should be able to understand basic concepts of GSM. Unit4
UO4: Student should be able to understand different Features of SMS
Unit5
UO5: Student should be able to understand basic concepts GPRS Unit6
UO6: Student should be able to understand basic concepts of VoIP,IMS and MPLS
Title of the Course: Engineering Linear Algebra
Course Code: PETC0102
L T P Credit
3 0 2 3
Course Pre-Requisite: Engineering Mathematics, MATLAB, Matrix Algebra.
Course Description: This course helps students to develop understanding and apply the concept in linear algebra including systems of linear equations and their solutions, Matrices and their properties
, Determinants and their properties, Vector Spaces, Linear Impedance of Vectors, Subspaces, basis and dimensions of vector spaces, inner product space, Linear transformation, Eigen values and Eigen
vectors.
Course Objectives: To Understand the algebraic structures and Linear Transformations.
To Understand the concept of Metric Space and Hilbert Space.
To Evaluate Orthogonality and Eigen values. To Evaluate Engineering problems using Algebraic Theorems.
Course Learning Outcomes:
CO After the completion of the course the student should be able to
CO1 Understand the algebraic structures and Linear Transformations.
CO2 Understand the concept of Metric Space and Hilbert Space.
CO3 Evaluate Orthogonality and Eigen values.
CO4 Evaluate Engineering problems using Algebraic Theorems.
CO-PO Mapping:
CO PO1 PO2 PO3
CO1 2
CO2 2
CO3 2
CO4 2
Assessments :
Teacher Assessment:
Two components of In Semester Evaluation (ISE), One Mid Semester Examination (MSE) and one EndSemester Examination (ESE) having 20%, 30% and 50% weights respectively.
Assessment Marks
ISE 1 10
MSE 30
ISE 2 10
ESE 50
ISE 1 and ISE 2 are based on assignment/declared test/quiz/seminar/Group Discussions etc. MSE: Assessment is based on 50% of course content (Normally first three modules)
ESE: Assessment is based on 100% course content with60-70% weightage for course content (normally last three modules) covered after MSE.
Course Contents:
UNIT 1 ALGEBRAIC STRUCTURES: -
Sets, Functions, Cardinality of sets, Groups, Rings, Fields, Vector spaces, Subspaces, Basis
and dimension, Finite and infinite dimensional vector spaces.
-5- Hrs.
UNIT 2: VECTOR SPACES AND LINEAR TRANSFORMATIONS (7 hours) Definition and examples – Subspaces – Linear independence – Basis and dimensions –
-7- Hrs.
Change of basis – Row space and Column space – Linear transformations: Definition –
Matrix representations, Sum, product and inverse of Linear Transformations, Rank-
nullity theorem, Isomorphism.
UNIT III – METRIC SPACE AND HILBERT SPACE (7 hours)
Metric space, Open sets, Closed sets, Neighborhoods, Sequences , Convergence,
Completeness, Continuous mappings, Normed space, Lp space and lp space, Hilbert
space, Signal space, Properties of inner product space, Orthogonal compliments and direct sums, Projections.
-7- Hrs.
UNIT IV - ORTHOGONALITY AND EIGENVALUES (9 hours)
The Scalar product in R – Orthogonal subspace – Least squares problem
Orthonormal sets – The Gram-Schmidt Orthogonalization procedure – Orthogonal
polynomials – Eigenvalues and Eigenvectors – Systems of Linear differential
equations – Diagonalization – Hermitian matrices – The Singular Value
Decomposition – Quadratic forms – Positive defnite matrices – Non-negative
matrices.
-9- Hrs.
UNIT V - NUMERICAL LINEAR ALGEBRA (7 hours) Floating point numbers – Gaussian elimination – Pivoting strategies – Matrix norms
and Condition numbers – Orthogonal transformations – The Eigenvalue problem –
Least squares problem.
-7- Hrs.
UNIT VI - ITERATIVE METHODS AND CANONICAL FORMS (7 hours) Power method – Inverse power method – Inverse power method with shifts –
Iterative method for finding eigen values – Jordan canonical form
-7- Hrs.
References:
1. Gilbert Strang (2009),” Introduction to Linear algebra”, Fourth edition, Wesley Cambridge Press, MA, USA.
2. Keith Mathews (1998), “Elementary Linear algebra”, University of Queensland, Australia. 3. Jim Hefferon (2001),” Linear algebra”, Saint Michael’s college, Vermont, USA. 4. Steven J. Leon (2009): “Linear algebra and its applications,” Eighth edition, Prentice Hall
Inc., NY, USA. 5. Hoffman Kenneth and Kunze Ray, Linear Algebra, Prentice Hall of India
6. Erwin Kreyzig, Introductory Functional Analysis with Applications, John Wiley, 2006. 7. G.F.Simmons, Topology and Modern Analysis , McGraw Hill 8. Frazier, Michael W. An Introduction to Wavelets through Linear Algebra, Springer
Publications. 9. Jin Ho Kwak & Sungpyo Hong, Linear Algebra, Springer International, 2004
Unit wise Measurable students Learning Outcomes:
Unit1
UO1: Students will able to understand Algebraic Structures Unit2
UO2: Students will able to work on Vector Spaces and Linear Transformations
Unit3
UO3: Students will understand Metric Space And Hilbert Space
Unit4
UO4: Student will understand the concept of Orthogonality and Eigenvalues
Unit5
UO5: Student will know the Numerical Linear Algebra Unit6
UO6: Student will able to understand Iterative Methods And Canonical Forms
Title of the Course: Random Process and Stochastic Process
Course Code: PETC0103
L T P Credit
4 -- 2 5
Course Pre-Requisite: MATLAB, Digital Signal Processing
Course Description: This course helps students to develop understanding and apply the concept of Probability Discrete Random Variable, Continuous Random Variable. The student will be able to
evaluate Moments of Random Variable and understand types of Random Processes. The student will be able to apply Markov chains technique with continuous state space. The student will be able
to apply Queuing Theory with single or Multi server system to solve everyday problems.
Course Objectives: 1.Students should develop the logical concepts of probability theory.
2. Students should understand basic concepts of Random variables & Random Processes 3. Students should study the concepts of Markov Chains ,state-space analysis and Queuing Theory
Course Learning Outcomes:
CO After the completion of the course the student
should be able to
Bloom’s Cognitive
level Descriptor
CO1 apply Probability concepts and statistical
measures to solve Problems.
Application Cognitive
CO2 classify Continuous and Discrete multiple Random Variables
Complex
Response
Psychomotor
CO3 differentiate between various Random Processes. Application Cognitive
CO4 apply Markov Chain & Queuing Theory to solve Problems
Comprehension Cognitive
CO-PO Mapping:
CO PO1 PO2 PO3
CO1 2
CO2 3
CO3 3 3
CO4 3 3
Assessments :
Teacher Assessment:
Two components of In Semester Evaluation (ISE), One Mid Semester Examination (MSE) and one EndSemester Examination (ESE) having 20%, 30% and 50% weights respectively.
Assessment Marks
ISE 1 10
MSE 30
ISE 2 10
ESE 50
ISE 1 and ISE 2 are based on assignment/declared test/quiz/seminar/Group Discussions etc. MSE: Assessment is based on 50% of course content (Normally first three modules)
ESE: Assessment is based on 100% course content with60-70% weightage for course content (normally last three modules) covered after MSE.
Course Contents:
Unit 1:--- Probability Theory: The concept of Probability; the axioms of Probability; sample space and events; Conditional probability and Baye’s theorem, Independence of events, Bernoulli trails.
-6- Hrs.
Unit 2:--- Random variables: Introduction to Random Variables, Discrete Random Variable, Continuous Random Variable, Expectation of Random Variable, Moments of Random Variable(mean, mode
variance, skewness, Kurtosis)
-7- Hrs.
Unit 3:--- Multiple Random Variables: cumulative distribution function and probability density function of single and multiple
Random Variables, statistical properties, Jointly distributed Gaussian random variables, Conditional probability density, properties of sum of random variables, Central limit
theorem, Estimate of population means, Expected value and variance and covariance.
-8- Hrs.
Unit 4:--- Random Processes: Classification of Processes; Properties, Auto correlation and cross correlation
function; Estimate of auto correlation function. Spectral Density: Definition, Properties, white noise, Estimation of auto-correlation
function using frequency domain technique, Estimate of spectral density, cross spectral density and its estimation, coherence.
-7- Hrs.
Unit 5:--- Markov Chains: Chapman Kolmogorov equation, Classification of states, Limiting probabilities, Stability of Markov system, Reducible chains, Markov chains with continuous state
space
-6- Hrs.
Unit 6:--- Queuing Theory: Elements of Queuing System Little's Formula, M/M/1 Queue, Multi server system
-6- Hrs.
Textbooks:
1. Introduction to probability Models,(Third edition) - Sheldon M. Ross. 2. Random Signal Processing, Prof.G.V.Kumbhojkar, C.Jamanadas &Company
References:
1 Probability and Random Processes for Electrical Engg.-Alberto Lean-Garcia (Pearson
Education.) 2. Probability, Random Variables and Stochastic Processes by Athanasios Papoulis and S.
Unnikrishna Pillai, PHI, 4th Edition, 2002 3. Stochastic Processes – J. Medhi , (New Age International.)
Unit wise Measurable students Learning Outcomes:
Unit1
UO1: Student should be able to understand basic concepts of Probability , Baye’s theorem and
Bernoulli trails. Unit2
UO2: Student should be able to understand types of Random Variable and Moments of RV. Unit3
UO3: Student should be able to understand basic concepts of cumulative distribution function and probability density function of single and multiple Random Variables and statistical properties
Unit4
UO4: Student should be able to estimate Auto correlation and cross correlation
function and spectral density of Random Processes
Unit5
UO5: Student should be able to understand basic concepts of Markov chains with continuous state space and apply it.
Unit6
UO6: Student should be able to understand basic concepts of single and Multiple server Queuing
system
Embedded System Programming PETC0121
Teaching Scheme Lectures: 3 Hrs/week, Tutorial 1Hr/ week
Examination Scheme ISE-I 10, MSE 30, ISE-II10, ESE50
Course Outcomes: At the end of the course, students will demonstrate the ability to: 1. Familiarity of the embedded Linux development model. 2. Understand and create Linux BSP for a hardware platform. 3. Develop and debug applications and drivers in embedded Linux. Syllabus Contents: Chapter 1 Review of super loop and RTOS programming, Need of embedded Linux, Embedded Linux Versus Desktop Linux, Embedded Linux Distributions and porting Chapter 2 Architecture of Embedded Linux, Linux Kernel Architecture: HAL, Memory manager, Scheduler, File System, I/O and Networking subsystem, IPC, User space, Linux Start-Up Sequence Chapter 3 Board Support Package: Inserting BSP in Kernel Build Procedure, The Boot Loader Interface, Memory Map, Interrupt Management, Timers, UATRS, Power management Chapter 4 Embedded Storage: MTD, Architecture, Drivers, Embedded File System Chapter 5 Embedded Drivers: Serial, Ethernet, I2C, USB, Timer, Kernel Modules Porting Applications Chapter 6 Introduction to BeagleBone hardware platform, Introduction to Raspberry PI hardware platform, Programming hardware resources of any of above boards using programming languages Text books:
1. P Raghvan, Amol Lad, SriramNeelakandan, “Embedded Linux System Design and Development”, Auerbach Publications
2. Derek Molloy, “Exploring BeagleBone: Tools and Techniques for Building with Embedded Linux”, Wiley, 1st Edition, 2014.
3. References:
1. Karim Yaghmour, “Building Embededd Linux Systems”, O'Reilly & Associates 2. Christopher Hallinan, “Embedded Linux Primer: A Practical Real World Approach”,
Prentice Hall, 2nd Edition, 2010. 3. Mastering Embedded Linux Programming.
Title of the Course: Fiber Optical communication Course Code: PETC122
L T P Credit
3 1 -- 4
Course Pre-Requisite: Knowledge of wave propagation in different media
Course Description:
The content in this course is designed to cover a one semester course at the post graduate level.
After providing the basic foundation of fiber optic communication, the course covers the
advanced topics like the power penalty in a link, fiber amplifiers like the EDFA and Raman
Amplifiers, non-linear fiber optics, optical switches and routers, dispersion compensators, DWDM
systems, wavelength routed optical networks, optical CDMA systems, etc.
Course Objectives:
On completion of this course you should be able to:
1. Explain the principles of operation of various optical fibre communication systems. 2. Analyze the performance of various digital and analogue optical fibre systems.
3. Calculate various key parameters of optical fibre systems. These include the system optical power budget and system rise time budget, receiver noise power, Q factor, bit error rate and
maximum usable bit rate of a digital optical fibre system. 4. Explain/compare the factors affecting the performance of different optical fibre
communication systems.
Course Learning Outcomes:
1. The students will be able to analyze the optical fiber components.
2. They will have understood the basic concepts of optical communication
3. Able to evaluate different parameters of the optical fiber.
CO After the completion of the course the
student should be able to
Bloom’s Cognitive
level Descriptor
CO1 C205.1 Recognize and classify the structures of
Optical fiber and types, the channel impairments like losses and dispersion.
II Understanding
CO2 C205.3 Analyze various coupling losses. VI Creating
CO3 C205. Classify the Optical sources and detectors and
to discuss their principle IV Analyzing
CO4 C205.5. Familiar with Design considerations of
fiber optic systems. VI Creating
CO5 C205.5. Measure characteristics of optical fiber,
sources and detectors, design as well as conduct experiments in software and hardware, analyze the
results to provide valid conclusions.
V Evaluating
CO-PO Mapping:
CO PO1 PO2 PO3
CO1 2
CO2 3
CO3 1
CO4 3
CO5 2 21
Assessments :
Teacher Assessment:
Two components of In Semester Evaluation (ISE), One Mid Semester Examination (MSE) and one EndSemester Examination (ESE) having 20%, 30% and 50% weights respectively.
Assessment Marks
ISE 1 10
MSE 30
ISE 2 10
ESE 50
ISE 1 and ISE 2 are based on assignment/declared test/quiz/seminar/Group Discussions etc. MSE: Assessment is based on 50% of course content (Normally first three modules)
ESE: Assessment is based on 100% course content with60-70% weightage for course content (normally last three modules) covered after MSE.
Course Contents:
Unit 1:--- OPTICAL FIBERS Basic principles of light propagation, Optical fibers - modal propagation, ray model, wave model.
08 Hrs.
Unit 2:--- SIGNAL DISTORTION ON OPTICAL FIBERS. Attenuation and dispersion
08 Hrs.
Unit 3:--- FBG BASED DEVICES
Principle, Frequency Response of a Uniform FBG, Non-Uniform Fiber Bragg Grating, Narrow Band Filter, Add-Drop Multiplexer, Dispersion, Compensator Gain Equalizer, Mode Converter, Sensor, integrated optics, non-linear fiber optics
07 Hrs.
Unit 4:--- OPTICAL SOURCES AND RECEIVERS LED, Lasers, photo receivers
08 Hrs.
Unit 5:--- SONET/SDH AND OPTICAL LINK DESIGN
SONET/SDH, DWDM, optical switches, Optical link design, power penalty etc
08 Hrs.
Unit 6:--- OPTICAL AMPLIFIERS AND WDM NETWORKS
Fiber Amplifiers, EDFA, Raman ,DRA, WDM networks and components and Optical
CDAMA
07 Hrs.
Textbooks: 1. J.E. Midwinter, Optical fibers for transmission, John Wiley, 1979.
2.T. Tamir, Integrated optics, (Topics in Applied Physics Vol.7), Springer-Verlag, 1975.
3. Optical Fiber Communications– – John M. Senior, Pearson Education. 3rd Impression, 20073. 4.Ghatak & K. Thygarajan, Introduction to Fiber Optics, Cambridge, 1999. 5.S.E. Miller and A.G. Chynoweth, eds., Optical fibres telecommunications, Academic Press, 1979.
6.G.Agrawal, Nonlinear fibre optics, Academic Press, 2nd Ed. 1994.
7.F.C. Allard, Fiber Optics Handbook for engineers and scientists, McGraw Hill, New York (1990).
References:
1. Fiber optics communication by G.P Agrawal.
2. Optical Fiber Communication by G. Keiser.
3. Raman Amplifiers for communications by M.N. Islam (Ed).
Unit wise Measurable students Learning Outcomes:
1. Comprehend the principles of ray theory. 2. Apply the fundamentals of optics to analyze the performance of optical fibers. 3. Compare and contrast difference between different optical fibers. (L3) 4. Classify the transmitters and receivers in optical communication. (L4 and L5) 5. Test, debug and evaluate the performance of a typical optical fiber 6. Work in team to prepare a report based on survey of flux budget, link budget in optical comm.
Title of the Course: INTERNET OF THINGS
Course Code: PETC0123
L T P Credit
3 1 - 4
Course Pre-Requisite: :Fundamentals of Computer Network, Computer Network
Course Description: This course looks at the Internet of Things (IoT) as the general theme of physical/real-world things becoming
increasingly visible and actionable via Internet and Web technologies. The goal of the course is to look top-down as well as bottom-up, to provide students with a comprehensive understanding of the IoT.
Course Objectives:
1. To understand what Internet of Things is.
2. To get basic knowledge of RFID Technology, Sensor Technology and Satellite Technology. 3. To
make students aware of resource management and security issues in Internet of Things.
Course Learning Outcomes: 1. 1. Explain what Internet of Thins is. 2. 2. Describe key technologies in Internet of Things. 3. 3. Understand wireless sensor network architecture and its framework along with WSN applications. 4. 4. Explain resource management in the Internet of Things. 5. 5. Understand business models for the Internet of Things.
CO-PO Mapping:
CO PO1 PO2 PO3
CO1 3 3
CO2 1 2
CO3 3 2 2
CO4 2 1 2
CO5 2 3
Assessments :
Teacher Assessment:
Two components of In Semester Evaluation (ISE), One Mid Semester Examination (MSE) and one EndSemester Examination (ESE) having 20%, 30% and 50% weights respectively.
Assessment Marks
ISE 1 10
MSE 30
ISE 2 10
ESE 50
ISE 1 and ISE 2 are based on assignment/declared test/quiz/seminar/Group Discussions etc. MSE: Assessment is based on 50% of course content (Normally first three modules)
ESE: Assessment is based on 100% course content with60-70% weightage for course content (normally last three modules) covered after MSE.
Course Contents:
Unit 1
Internet/Web and Networking Basics OSI Model, Data transfer referred with OSI Model, IP
Addressing, Point to Point Data transfer, Point to Multi Point Data transfer & Network
Topologies, Sub-netting, Network Topologies referred with Web, Introduction to Web
Servers, Introduction to Cloud Computing IoT Platform overview Overview of IoT supported
Hardware platforms such as: Raspberry pi, ARM Cortex Processors, Arduino and Intel
Galileo boards. Network Fundamentals: Overview and working principle of Wired
Networking equipment’s – Router, Switches, Overview and working principle of Wireless
Networking equipment’s – Access Points, Hubs etc. Linux Network configuration Concepts:
Networking configurations in Linux Accessing Hardware & Device Files interactions.
12Hrs.
Unit 2: IoT Architecture:
History of IoT, M2M – Machine to Machine, Web of Things, IoT protocols Applications: Remote
Monitoring & Sensing, Remote Controlling,Performance Analysis The Architecture The Layering
concepts , IoT Communication Pattern, IoT protocol Architecture, The 6LoWPAN Security aspects
in IoT
8 Hrs.
Unit 3 IoT Application Development:
Application Protocols MQTT, REST/HTTP,CoAP, MySQL
Back-end Application Designing Apache for handling HTTP Requests, PHP & MySQL for data
processing, MongoDB Object type Database, HTML, CSS & jQuery for UI Designing, JSON lib for
data processing, Security & Privacy during development, Application Development for mobile
Platforms: Overview of Android / IOS App Development tools
13Hrs.
Unit 4Case Study & advanced IoT Applications:
IoT applications in home, infrastructures, buildings, security, Industries, Home appliances, other
IoT electronic equipments. Use of Big Data and Visualization in IoT, Industry 4.0 concepts.
Sensors and sensor Node and interfacing using any Embedded target boards (Raspberry Pi / Intel
Galileo/ARM Cortex/ Arduino)
6Hrs.
Textbooks: 1. 6LoWPAN: The Wireless Embedded Internet, Zach Shelby, Carsten Bormann, Wiley 2. Internet of Things: Converging Technologies for Smart Environments and Integrated Ecosystems, Dr. Ovidiu Vermesan, Dr. Peter Friess, River Publishers 3. Interconnecting Smart Objects with IP: The Next Internet, Jean-Philippe Vasseur, Adam Dunkels, Morgan Kuffmann
REFERENCES:
1. The Internet of Things: From RFID to the Next-Generation Pervasive Networked Lu Yan, Yan Zhang,
Laurence T. Yang, Huansheng Ning
2. Internet of Things (A Hands-on-Approach) , Vijay Madisetti , Arshdeep Bahga
3. Designing the Internet of Things , Adrian McEwen (Author), Hakim Cassimally
4. Asoke K Talukder and Roopa R Yavagal, “Mobile Computing,” Tata McGraw Hill, 2010.
5. Computer Networks; By: Tanenbaum, Andrew S; Pearson Education Pte. Ltd., Delhi, 4 th Edition
6. Data and Computer Communications; By: Stallings, William; Pearson Education Pte. Ltd., Delhi, 6th
Edition
7. F. Adelstein and S.K.S. Gupta, “Fundamentals of Mobile and Pervasive Computing,” McGraw Hill, 2009. 8.
Cloud Computing Bible, Barrie Sosinsky, Wiley-India, 2010
Unit wise Measurable students Learning Outcomes:
Title of the Course: Wireless Sensor Networks
Course Code: PETC124
L T P Credit
3 1 -- 4
Course Pre-Requisite: Digital Communication, Wireless Communication Network, MATLAB
Course Description: This course helps student to understand wireless sensor networking protocols architectures, hardware and software tools and standards. This course helps to understand hardware details of different types of sensors in order to select right type of sensor for various applications
Course Objectives: 1.To acquire fundamental knowledge of Wireless Sensor Network.
2 To study the different types of sensors
3 To understand the basic concepts of radio standards and communication protocols used by wireless sensor network based systems
4. To study capacity of wireless channels and multiple antenna system
5. To understand operating systems and programming languages for wireless sensor nodes 6. To understand issues like energy conservation and security challenges.
Course Learning Outcomes:
CO After the completion of the course the student
should be able to
Bloom’s Cognitive
level Descriptor
CO1 Explain basic concepts and technologies used in wireless sensor networks.
I Cognitive
Explain
CO2 Design various types of sensor motes for different real life applications.
III Psychomotor
Design
CO3 Understand and remember radio standards and communication protocols used by wireless sensor network based systems.
II Cognitive
Understand
CO4 Classify Operating systems for wireless sensor networks and design
II Affective
Classify
CO-PO Mapping:
CO PO I PO II PO III
CO1
CO2
CO3
CO4
CO4
CO5
CO6
Assessments :
Teacher Assessment:
Two components of In Semester Evaluation (ISE), One Mid Semester Examination (MSE) and one
EndSemester Examination (ESE) having 20%, 30% and 50% weights respectively.
Assessment Marks
ISE 1 10
MSE 30
ISE 2 10
ESE 50
ISE 1 and ISE 2 are based on assignment/declared test/quiz/seminar/Group Discussions etc.
MSE: Assessment is based on 50% of course content (Normally first three modules) ESE: Assessment is based on 100% course content with60-70% weightage for course content
(normally last three modules) covered after MSE.
Course Contents:
Unit 1:--- Introduction and overview
Introduction and overview: basic building blocks of sensor node, functionality of a sensor
node, characteristics of a sensor node in WSN, WSN architecture, topologies, and applications.WSN v/s Adhoc networks, IOT and applications of IOT.
-6- Hrs.
Unit 2:--- Main Features of WSN
Simulation and experimental platforms; main features of WSNs; Research issues and trends, Sensor deployment mechanisms, coverage issues
-6- Hrs.
Unit 3:--- Protocols for sensor networks Routing Protocols for Wireless Sensor Networks- Routing Challenges and Design Issues
in Wireless Sensor Networks, Routing Strategies in Wireless Sensor Networks, Transport
Control Protocols for Wireless Sensor Networks. Enabling technologies, Fundamentals of 802.15.4, Bluetooth, and UWB; Physical and
MAC layers; node discovery protocols, Network layer protocols
-6- Hrs.
Unit 4:--- Sensor Node hardware Sensor node hardware : mica2, micaZ, telosB, cricket, Imote2, tmote, btnode, and Sun SPOT
-8- Hrs.
Unit 5:---Sensor Node Software Operating Systems for Wireless Sensor Networks-Operating System Design Issues, Examples of Operating Systems, TinyOS, Mate, MagnetOS, MANTIS, Contiki, RetOS and PicOS, Programming tools: C, nesC
-8- Hrs.
Unit 6:--- Data dissemination and processing
Data dissemination and processing: Data Dissemination and Gathering, multi-hop and
cluster based protocols; routing. Middleware and application layers, Data dissemination; data storage; query processing; sensor Web; sensor Grid, Open issues for future research,
Energy preservation and efficiency; security challenges; fault-tolerance, different case
studies
-6- Hrs.
Textbooks:
1. Protocols and Architectures for Wireless Sensor Networks by . H. Karl and A. Willig. John
Wiley & Sons, June 2005.
2. Wireless Sensor Networks: Technology, Protocols, and Applications by . K. Sohraby, D.
Minoli, and T. Znati. John Wiley & Sons, March 2007
References: 1. Wireless Sensor Networks by . C. S. Raghavendra, K. M. Sivalingam, and T. Znati, Editors. Springer
Verlag, Sep. 2006. 2. Wireless Sensor Networks: Architectures and Protocols by . E. H. Callaway, Jr.
AUERBACH, Aug. 2003. 3.Networking Wireless Sensors by B. Krishnamachari. Cambridge University Press, Dec. 2005.
4.Wireless Sensor Networks: An Information Processing Approach by . F. Zhao and L.Guibas. Morgan
Kaufmann, Jul. 2004. 5. Sensor Networks and Configuration: Fundamentals, Standards, Platforms, and Applications by . N. P.
Mahalik. Springer Verlag, Nov. 2006
6.Wireless Sensor Networks: A Systems Perspective by , N. Bulusu and S. Jha, Editors, Artech House, August 2005
Unit wise Measurable students Learning Outcomes:
Unit1
UO1: Student should be able to understand basic concepts of wireless sensor network protocols and
architecture
Unit2
UO2: Student should be able to understand the different simulation platforms for WSN. Unit 3
UO3.1: Student should be able to understand MAC and routing protocols Unit 4
UO4.1: Student should be able to understand basic concepts of various Sensor node hardware Unit 5
UO5.1: Student should be able to understand basic concepts of Sensor Node Software and Programming tools
UO5.2: : Student should be able to understand basic concepts of Sensor deployment mechanisms
Unit 6
UO6.1: Student should be able to understand basic concepts of Data dissemination and processing
Title of the Course: RADIATING SYSTEMS Course Code:PETC0125
L T P Credit
4 1 - 5
Course Pre-Requisite: Knowledge of wave propagation in different media
Course Description:
The purpose of introducing this course is to describe the advanced design principles used in the radiating systems. By undergoing this course, the student will learn to analyze and design different types of antennas.
Course Objectives:
On completion of this course you should be able to:
5. Understanding of the different types of antennas and sources of radiation. 6. Knowledge of the concepts of antenna synthesis techniques.
7. Understanding of the concept of microstrip antennas. 8. Learning the various methods of antenna measurements.
9. Studying Smart antennas for wireless systems.
Course Learning Outcomes:
4. The students will be able to analyze the optical fiber components.
5. They will have understood the basic concepts of optical communication
6. Able to evaluate different parameters of the optical fiber..
CO After the completion of the course the
student should be able to
Bloom’s Cognitive
level Descriptor
CO1 C205.1 Recognize and classify the various types of
antennas II Understanding
CO2 C205.3 Analyze antenna parameters. VI Creating
CO3 C205.5. Design the antenna as per specifications VI Creating
CO4 C205.5. Measure characteristics of different
antennas V Evaluating
CO-PO Mapping:
CO PO1 PO2 PO3
CO1 2
CO2 2
CO3 3
CO4 1 2
Assessments :
Teacher Assessment:
Two components of In Semester Evaluation (ISE), One Mid Semester Examination (MSE) and one
End Semester Examination (ESE) having 20%, 30% and 50% weights respectively.
Assessment Marks
ISE 1 10
MSE 30
ISE 2 10
ESE 50
ISE 1 and ISE 2 are based on assignment/declared test/quiz/seminar/Group Discussions etc.
MSE: Assessment is based on 50% of course content (Normally first three modules) ESE: Assessment is based on 100% course content with60-70% weightage for course content
(normally last three modules) covered after MSE.
Course Contents:
Unit 1:--- FUNDAMENTAL PARAMETERS OF ANTENNAS Introduction, Radiation Pattern, Radiation Power Density, Radiation Intensity, Beamwidth, Directivity, Numerical Techniques, Antenna Efficiency, Gain, Beam Efficiency, Bandwidth, Polarization, Input Impedance, Antenna Radiation Efficiency, Antenna Vector Effective Length and Equivalent Areas, Maximum Directivity and Maximum Effective Area, Friis Transmission Equation and Radar Range Equation, Antenna Temperature
04 Hrs.
Unit 2:--- LINEAR WIRE ANTENNAS Introduction, Infinitesimal Dipole, Small Dipole, Region Separation, Finite Length Dipole, Half-Wavelength Dipole, Linear Elements Near or on Infinite Perfect Conductors, Ground Effects, Computer Codes
08 Hrs.
Unit 3:--- LOOP ANTENNAS
Introduction, Small Circular Loop, Circular Loop of Constant Current, Circular Loop with Non-uniform Current, Ground and Earth Curvature Effects for Circular Loops, Polygonal Loop Antennas, Ferrite Loop, Mobile Communication Systems Applications
06 Hrs.
Unit 4:--- HORN ANTENNAS, REFLECTOR ANTENNAS Introduction, E-Plane Sectoral Horn, H-Plane Sectoral Horn, Pyramidal Horn, Conical Horn, Corrugated Horn, Introduction, Plane Reflector, Corner Reflector, Parabolic Reflector, Spherical Reflector
07 Hrs.
Unit 5:--- SMART ANTENNAS
Introduction, Smart-Antenna Analogy, Cellular Radio Systems Evolution, Signal Propagation,
Smart Antennas’ Benefits, Smart Antennas’ Drawbacks, , Antenna Beam forming, Mobile Ad hoc
Networks (MANETs), Smart-Antenna System Design, Simulation, and Results
07 Hrs.
Unit 6:--- ANTENNA MEASUREMENTS
Introduction, Antenna Ranges, Radiation Patterns, Gain Measurements, Directivity
Measurements, Radiation Efficiency, Impedance Measurements, Current Measurements,
Polarization Measurements, Scale Model Measurements
07 Hrs.
Textbooks:
1. J.R.James and P.S.Hall, Handbook of MIcrostrip Antennas, Peter Peregrinus, 1989
2. R.C.Johnson and H.Jasik, Antennas Engineering Handbook, McGraw Hill, 1984
3. W.L.Stutzman and G.A.Thiele, Antenna Theory and Design, John Wiley & Sons,
1981
References:
1. C.A.Balanis, Antenna Theory - Analysis and Design, John Wiley & Sons, 1998
2. J.D.Kraus and R.J.Marhefka, Antennas for all Applications, McGraw Hill, 2003
3. G.Kumar and K.P.Ray, Broadband Microstrip Antennas, Artech House, 2003
Unit wise Measurable students Learning Outcomes:
1. Comprehend the principles of ray theory. 2. Apply the fundamentals of antenna parameters to analyze the performance of different antennas 3. Compare and contrast difference between different antenna types . (L3) 4. Classify the antennas. (L4 and L5) 5. Test, debug and evaluate the performance of a typical antenna. 6. Work in team to prepare a report based on survey of different btypes of antennas.
Title of the Course: Optimization Techniques
Course Code: PETC0126
L T P Credit
3 1 -- 4
Course Pre-Requisite: MATLAB
Course Description: This course helps students to develop understanding and apply Optimization Techniques to solve Engineering Problems. Students understand the concept of linear programming,
Nonlinear programming, Geometric programming, Dynamic programming. Students learn
formulation of problem and assignment of models. Students learn to apply Genetic Algorithms.
Course Objectives:
1. Students should understand the concept of Optimization Techniques. 2.Students should understand the concept of linear programming, Nonlinear programming,
Geometric programming, Dynamic programming. 3.Students should understand the method for formulation of problem and assignment of models.
4 .Students should understand single-dimensional and Multi-dimensional Search Methods
Course Learning Outcomes:
CO After the completion of the course the student
should be
able to
Bloom’s Cognitive
level Descriptor
CO1 Apply Optimization Techniques to Engineering
Problems.
Application Cognitive
CO2 implement Linear/Nonlinear, Dynamic, Geometric programming
Complex
Response
Psychomotor
CO3 apply single-dimensional and Multi-dimensional
Search Methods in constrained and Unconstrained problem environments
Application Cognitive
CO4 distinguish assignment of models.
Comprehension Cognitive
CO-PO Mapping:
CO a b c d e f g h i j k
CO1 H H H
CO2 M H M H H
CO3 H H L M H H
CO4 H H M H H
CO4 H H L H H
CO5 H H
CO6 M H M H H
Assessments :
Teacher Assessment:
Two components of In Semester Evaluation (ISE), One Mid Semester Examination (MSE) and one
EndSemester Examination (ESE) having 20%, 30% and 50% weights respectively.
Assessment Marks
ISE 1 10
MSE 30
ISE 2 10
ESE 50
ISE 1 and ISE 2 are based on assignment/declared test/quiz/seminar/Group Discussions etc.
MSE: Assessment is based on 50% of course content (Normally first three modules) ESE: Assessment is based on 100% course content with60-70% weightage for course content
(normally last three modules) covered after MSE.
Course Contents:
Unit 1:--- Introduction :
Historical development, Application to Engineering Problems, Statement of Optimization problems, Classification of Optimization, Multivariable optimization with and without
constraints,
-6- Hrs.
Unit 2:--- Linear Programming :
Formulation, Geometry, Graphical solution, standard and matrix form of linear
programming problems, Simplex programming and its flow chart, revised simplex algorithm, Two-phase Simplex method ,Degeneracy .
Duality in linear programming: Definition of Dual Problem, General Rules for converting any Primal into its Dual Simplex method and its flow chart. Decomposition
principle, Transportation problem.
-7- Hrs.
Unit 3:--- Nonlinear programming :
Unimodal functions, single dimensional minimization methods, Exhaustive search, Fibonnaci method, Golden section, Comparison of Elimination method, Quadrature
interpolation, Cubic interpolation , Direct root method, Random search method , Steepest decent method, Fletcher-Reeves method, David-Fletcher-Powell Method, Convex sets and
convex functions, Kuhn-Tucker conditions. convex optimization, Lagrange multipliers Convex quadratic programming: Wolfe’s
and Pivot complementary algorithms. Separable programming, Constrained Multidimensional Search Methods: Rosen’s Gradient projection method, Penalty function
method.
-8- Hrs.
Unit 4:--- Geometric programming : Problems with positive coefficients up to one degree of difficulty, Generalized method for
the positive and negative coefficients Dynamic programming: Discrete and continuous dynamic programming (simple illustrations). Multistage decision problems, computation
procedure and case studies
-7- Hrs.
Unit 5:--- Assignment Models :
Formulation of problem, Hungarian Method for Assignment Problem, Unbalanced Assignment Problems
-6- Hrs.
Unit 6:--- Genetic Algorithms:
Introduction, Representation of design variables, Representation of objective function and constraints, Genetic operators, Application procedure and case studies
-6- Hrs.
Textbooks:
1. Optimization: Theory and Practices, S.S Rao ,New Age Int. (P) Ltd. Publishers, New Delhi 2. Optimization concepts & application in Engg. -A. D. Belegundu, Tirupati R.
Chandrupatla (Pearson Edn.)
References:
1 Linear Programming and Network Flows- Mokhtar S. Bazaraa,John J. Jarvis, Hanif D.
Sherali Second Edition (Wiley Publication) 2. Chong, E.K.P.and Zak, S. H.. An Introduction to Optimization, John Wiley &Sons,N.Y.
3.Peressimi A.L., Sullivan F.E., Vhi, J.J..Mathematics of Non-linear Programming, Springer –Verlag]
Unit wise Measurable students Learning Outcomes:
Unit1
UO1: Student should be able to understand basic concepts of Multivariable optimization with and without constraints,
Unit2
UO2: Student should be able to understand basic concepts of Linear Programming
Unit3
UO3: Student should be able to understand basic concepts of single dimensional minimization
methods ,Multidimensional Search Methods Unit4
UO4: Student should be able to understand basic concepts of Dynamic programming: Discrete and continuous dynamic programming (simple illustrations). Multistage decision problems
Unit5
UO5: Student should be able to understand basic concepts of Hungarian Method for Assignment
Problem, Unbalanced Assignment Problems Unit6
UO6: Student should be able to understand basic concepts of Genetic operators and the Application procedure
Title of the Course: Research Methodology
Course Code: PETC0161
L T P Credit
2 - - 0
Course: There are no Pre-Requisite for this course
Course Description: This course will provide an opportunity for participants to establish or advance their understanding of research through critical exploration of research language, ethics, and
approaches.
Course Objectives:
1. Defending the use of Research Methodology 2. Judging the reliability and validity of experiments
3. Perform exploratory data analysis 4. Draw conclusions from categorical data
5. Using computer-intensive methods for data analysis 6. Compare statistical models
Course Learning Outcomes:
CO After the completion of the course the student should
be able to
Bloom’s Cognitive
level Descriptor
CO1 Defend the use of Research Methodology Affective domain
Defend
CO2 Judge the reliability and validity of experiments Psychomotor Judge
CO3 perform exploratory data analysis Psychomotor analysis
CO4 draw conclusions from categorical data Psychomotor conclude
CO5 Use computer-intensive methods for data analysis Psychomotor data
analysis
CO6 Drawing conclusions from statistical test results & compare statistical models
Psychomotor compare
CO-PO Mapping:
CO PO1 PO2 PO3
CO1 3 1 1
CO2 3 1 1
CO3 1 1 2
CO4 1 2 2
CO5 3 1 1
CO6 3 1 1
Assessments :
Teacher Assessment: One EndSemester Examination (ESE) having 100% weightage
Assessment Marks
ISE 1 -
MSE -
ISE 2 -
ESE 50
ESE: Assessment is based on 100% course content
Course Contents:
Unit I: Introduction to Research An Introduction, Meaning of Research , Objectives of Research, Motivation in
Research, Types of Research, Research Approaches , Significance of Research , Research Methods versus Methodology Research and Scientific
Method , Importance of Knowing How Research is Done , Research Process Criteria of Good Research, Problems Encountered by Researchers
5 Hrs.
Unit II Research Design Meaning of Research Design, Need for Research Design, Features of a Good
Design, Important Concepts Relating to Research Design, Different Research Designs, Basic Principles of Experimental Designs
4 Hrs.
Unit III Sampling Design
Need for sampling, Population, Sample, Normal distribution, Steps in sampling, Systematic bias and Sampling error, Characteristics of good sample design,
Probability sampling and Random sampling, Determination of sample size
4 Hrs.
Unit IV:---
Results and Analysis Importance and scientific methodology in recording results, importance of negative
results, Different ways of recording, industrial requirement, artifacts versus true results, types of analysis (analytical, objective, subjective) and cross verification,
correlation with published results, discussion, outcome as new idea, hypothesis, concept, theory, model etc
4Hrs.
Unit V : Measurement and Scaling Techniques
Introduction, Concept of measurement - Measurement of scale, Developing measurement scale, Criteria of good measurement tools, Error measurement.
Concept of Scaling, Classification, Approaches of scale construction, Types of scales - Rating scale, Ranking scale, Arbitrary scale, Differential scale, Summated
scale, Cumulative scale, Factor scale.
3 Hrs.
Unit VI: Data Collection and Analysis of Data
Collection of Primary Data, Observation Method, Interview Method, Collection of Data through Questionnaires, Collection of Data through Schedules, Difference
between Questionnaires and Schedules, Collection of Secondary Data, Selection of Appropriate Method for Data Collection, Data Processing Operations, Problems in
Processing, Elements/Types of Analysis
4 Hrs.
Textbooks: 1. Books: C. R. Kothari, “Research Methodology”, New Age international, 2004.
2. Deepak Chopra and Neena Sondhi, “Research Methodology : Concepts and cases”, Vikas Publishing House, New Delhi, 2008.
3. Ranjit Kumar, “Research Methodology: A Step by Step Guide for Beginners”, 2nd Edition, Sage Publisher, 2011.
Unit wise Measurable students Learning Outcomes:
1. Recall research terminology
2. Be aware of the ethical principles of research, ethical challenges and approval processes
3. Describe quantitative, qualitative and mixed methods approaches to research
4. Identify the components of a literature review process
5. Critically analyze published research
6. Discuss Research Methodology
Title of the Course: Random Process and Stochastic Process Course Code: PETC0131
L T P Credit
0 0 2 1
Course Pre-Requisite: MATLAB, Digital Signal Processing
Course Description: This Laboratory course helps students to develop understanding and
apply the concept of Probability Discrete Random Variable, Continuous Random Variable to solve Numerical problems. The student will be able to evaluate Moments of Random
Variable using MATLAB and estimate parameters to differentiate Random Processes. The student will be able to apply Markov chains technique with continuous state space. The
student will be able to apply Queuing Theory with single or Multi server system to solve everyday problems.
Course Objectives:
1. Students should develop the logical concepts of probability theory. 2. Students should understand basic concepts of Random variables & Random Processes
3. Students should study the concepts of Markov Chains ,state-space analysis and Queuing Theory
Course Learning Outcomes:
CO After the completion of the course the student
should be
able to
Bloom’s Cognitive
level Descriptor
CO1 apply Probability concepts and statistical measures
to solve Problems using MATLAB.
Application Cognitive
CO2 Carry out parameter evaluation of Continuous and Discrete multiple Random Variables using
MATLAB
Complex Response
Psychomotor
CO3 differentiate between various Random Processes
using MATLAB
Comprehension Cognitive
CO4 apply Markov Chain & Queuing Theory to solve Problems using MATLAB
Application Cognitive
CO-PO Mapping:
CO PO1 PO2 PO3
CO1 2
CO2 3
CO3 3 3
CO4 3 3
Assessments :
Teacher Assessment:
One component of In Semester Evaluation (ISE) and one End Semester Examination (ESE) having 50%, and 50% weights respectively.
Assessment Marks
ISE 50
ESE 50
ISE are based on practical performed/ Quiz/ Mini-Project assigned/ Presentation/ Group
Discussion/ Internal oral etc. ESE: Assessment is based on oral examination
Course Contents:
Experiment No. 1:--- Bernoulli Trials ( Binomial Distribution ) Aim and Objectives: Understand Binomial Distribution and Carry out Case Study
Outcomes: Mathematical proof for Case Study Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion:
-2- Hrs.
Experiment No. 2:--- Study of Rayleigh Probability Density Function
Aim and Objectives: Case Study
Outcomes: PDF and CDF plot Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion:
-2- Hrs.
Experiment No. 3:--- Probability density function of Gaussian distributed
random variable. Effect of changing the Mean and Standard deviation in Gaussian PDF
Aim and Objectives: Case Study
Outcomes: PDF and CDF plot
Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion:
-2- Hrs.
Experiment No. 4:--- Study of autocorrelation
Aim and Objectives: Evaluate autocorrelation of Random Processes
Outcomes: autocorrelation function value in the range 0-1
Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion:
-2- Hrs.
Experiment No. 5:--- Study of cross correlation Aim and Objectives: Evaluate cross correlation of Two Random Processes
Outcomes: cross correlation value
Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion:
-2- Hrs.
Experiment No. 6:--- power spectral density (psd) Aim and Objectives: Evaluate power spectral density of Random Processes by
different methods
Outcomes: power spectral density
Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion:
-2- Hrs.
Experiment No. 7:--- Study of markov chain
Aim and Objectives: Markov Chains Case Study Outcomes: Draw Transition State Diagram
Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion:
-2- Hrs.
Experiment No. 8:--- Calculation of various statistical parameters for random signal
Aim and Objectives: Evaluate various statistical parameters for random variable
Outcomes: Mean ,Mode ,Variance, Skew Factor , Moments etc
Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion:
-2- Hrs.
Textbooks:
1. Introduction to probability Models,(Third edition) - Sheldon M. Ross. 2. Random Signal Processing, Prof.G.V.Kumbhojkar, C.Jamanadas &Company
References:
1. Probability and Random Processes for Electrical Engg.-Alberto Lean-Garcia (Pearson
Education.) 2. Probability, Random Variables and Stochastic Processes by Athanasios Papoulis and S.
Unnikrishna Pillai, PHI, 4th Edition, 2002 3. Stochastic Processes – J. Medhi , (New Age International.)
Experiment wise Measurable students Learning Outcomes:
EO1: Student should be able to understand basic concepts of Bernoulli Trials
EO2: Student should be able to understand basic concepts of Rayleigh Probability Density
Function EO3: Student should be able to understand basic concepts of Probability density function of
Gaussian distributed random variable. EO4: Student should be able to understand basic concepts of autocorrelation of Random
Processes EO5: Student should be able to understand basic concepts of cross correlation of Two
Random Processes EO6: Student should be able to understand basic concepts of power spectral density of
Random Processes EO7: Student should be able to understand basic concepts of Markov Chains ,Transition State
Diagram
EO8: Student should be able to understand basic concepts of Mean ,Mode ,Variance, Skew
Factor , Moments etc
Title of the Course: Engineering Linear Algebra Lab Course Code: PETC0132
L T P Credit
0 0 2 1
Course Pre-Requisite: MATLAB, Basic Matrix Theory
Course Description: This Laboratory course helps students to develop understanding and
apply Linear Algebra to solve Engineering Problems.
Course Objectives:
1. Students should Understand important Concepts of Linear Algebra.
2. Students should solve Engineering Problems using Concepts of Linear Algebra. 3. Students should use the basic techniques of matrix algebra, including finding the inverse
of an invertible matrix using Gauss-Jordan elimination.
Course Learning Outcomes:
CO After the completion of the course the student
should be able to
Bloom’s Cognitive
level Descriptor
CO1 Understand the basic ideas of vector algebra:
linear dependence and independence
Understand Cognitive
CO2 Apply to Solve Engineering Problems using
Concepts of Linear Algebra.
Apply Cognitive
CO3 Apply the basic techniques of matrix algebra, including finding the inverse of an invertible
matrix using Gauss-Jordan elimination
Apply Cognitive
CO-PO Mapping:
CO PO1 PO2 PO3
CO1 1 3
CO2 3
CO3 3
Assessments :
Teacher Assessment:
One component of In Semester Evaluation (ISE) and one End Semester Examination (ESE)
having 50%, and 50% weights respectively.
Assessment Marks
ISE 50
ESE 50
ISE are based on practical performed/ Quiz/ Mini-Project assigned/ Presentation/ Group Discussion/ Internal oral etc.
ESE: Assessment is based on oral examination
Course Contents:
Experiment No. 1:--- Solutions of linear equation
Aim and Objectives: To Study and solutions of linear equation Outcomes:
Theoretical Background:
Experimentation:
Results and Discussions:
-2- Hrs.
Conclusion:
Experiment No. 2:--- Applications of system of linear equation
Aim and Objectives: To Study of applications of system of linear equation Outcomes: Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion:
-2- Hrs.
Experiment No. 3:--- Vector and Matrix Differentiation Aim and Objectives: To Study of vector and matrix Differentiation
Outcomes: Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion:
-2- Hrs.
Experiment No. 4:--- Dimensions
Aim and Objectives: To Study use of Dimensions Outcomes:
Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion:
-2- Hrs.
Experiment No. 5:--- Nullity Theorem
Aim and Objectives: To Study Row Space and Nullity Theorem Outcomes:
Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion:
-2- Hrs.
Experiment No. 6:--- Eigen Vectors Aim and Objectives: To Study of Eigen Vectors Outcomes:
Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion:
-2- Hrs.
Experiment No. 7:--- Complex Eigen Vectors
Aim and Objectives: To Study of Complex Eigen Vectors Outcomes:
Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion:
-2- Hrs.
Experiment No. 8:--- Project I
Aim and Objectives: To Solve Engineering Problem Using Linear Algebra. Outcomes:
Theoretical Background:
Experimentation:
Results and Discussions:
-2- Hrs.
Conclusion:
Experiment No. 9:--- Project II Aim and Objectives: To Solve Engineering Problem Using Linear Algebra.
Outcomes:
Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion
-2- Hrs.
Reference Books:
1. Gilbert Strang (2009),” Introduction to Linear algebra”, Fourth edition, Wesley
Cambridge Press, MA, USA. 2. Keith Mathews (1998), “Elementary Linear algebra”, University of Queensland,
Australia. 3. Jim Hefferon (2001),” Linear algebra”, Saint Michael’s college, Vermont, USA.
4. Steven J. Leon (2009): “Linear algebra and its applications,” Eighth edition, Prentice Hall Inc., NY, USA.
5. Hoffman Kenneth and Kunze Ray, Linear Algebra, Prentice Hall of India 6. Erwin Kreyzig, Introductory Functional Analysis with Applications, John Wiley,
2006. 7. G.F.Simmons, Topology and Modern Analysis , McGraw Hill
8. Frazier, Michael W. An Introduction to Wavelets through Linear Algebra, Springer Publications.
9. Jin Ho Kwak & Sungpyo Hong, Linear Algebra, Springer International, 2004
Title of the Course: RF and Microwave Circuit Design
Course Code: PETC0204
L T P Credit
4 - - 4
Course Pre-Requisite:
Basics of Microwave engineering and transmission lines
Course Description: This course aims to introduce design strategies for various microwave circuit like microwave filters, amplifiers and oscillators and Mixers.
Course Objectives: 1. To understand the basic concepts of microwave waveguides and transmission lines.
2. To Design the microwave active filters 3. To Design microwave active amplifiers
4. To Design microwave oscillators and Mixers
Course Learning Outcomes:
CO After the completion of the course the student should be
able to
Bloom’s Cognitive
level
CO1 Understand the basic concepts of microwave waveguides and transmission lines.
CO2 Design the microwave active filters
CO3 Design microwave active amplifiers
CO4 Design microwave oscillators and Mixers
CO-PO Mapping:
CO PO1 PO2 PO3
CO1 - - 2
CO2 - - 3
CO3 - - 3
CO4 - - 3
Assessments : Teacher Assessment:
Two components of In Semester Evaluation (ISE), One Mid Semester Examination (MSE) and one End Semester Examination (ESE) having 20%, 30% and 50% weights respectively.
Assessment Marks
ISE 1 10
MSE 30
ISE 2 10
ESE 50
ISE 1 and ISE 2 are based on assignment/declared test/quiz/seminar/Group Discussions etc. MSE: Assessment is based on 50% of course content (Normally first three modules)
ESE: Assessment is based on 100% course content with60-70% weightage for course content (normally last three modules) covered after MSE.
Course Contents:
Unit 1:--- Introduction to transmission lines and waveguides : Solutions for TEM waves, rectangular waveguide, circular waveguide, co-axial line, stripline, microstrip, impedance and equivalent voltage and currents, the S- matrix, ABCD matrix, SFG,
discontinuities and model analysis, waveguide excitation, introduction to smith chart,
8 Hrs.
single and double stub matching, quarter wave transformer, binomial and chebyshev
multi-section matching transformer, Bode-fano criterion
Unit 2:--- Microwave Resonators, power dividers and directional couplers: Series and parallel
resonant circuits, transmission line resonator, rectangular waveguide cavities, circular
waveguide cavities, di-electric resonators, excitation of resonators, concept of power
dividers and couplers, T-junction power divider, Wilkinson power divider, directional
coupler, quadrature hybrid, Lange coupler, 180 degree hybrid
8 Hrs
Unit 3:--- Microwave Filters: Periodic structures, filter design by image parameter method and insertion loss methods, filter transformations, filter implementation, stepped impedance LPF, coupled line filters, filters using coupled resonators
8 Hrs
Unit 4:---. Noise and Active RF components: Noise in microwave circuits, dynamic range and
inter-modulation distortion, RF diode and transistor characteristics, MMIC.
8 Hrs
Unit 5:--- Microwave amplifier design: Two port power gain, stability, single stage and
broadband transistor amplifier design, Power amplifiers.
8 Hrs
Unit 6:--- Design of microwave oscillators and mixers: RF oscillators, microwave oscillators,
oscillator phase noise, frequency multipliers, different microwave sources, mixer design.
8 Hrs
Textbooks: 1. Microwave Engineering, David M Pozar, wiley publication, 3
rd edition
References:
1. RF circuit design theory and applications, reinhold Ludwig, gene bogdanov, pearson publication 2
nd edition
2. Microwave Circuit Design: A Practical Approach Using ADS, Kyung-Whan Yeom, PHI publication
3. Advanced RF & Microwave Circuit Design: The Ultimate Guide to Superior Design By Matthew M. Radmanesh, Authorhouse publication
4. Passive RF and Microwave Integrated Circuits, Leo Maloratsky, Elsevier publication
Unit wise Measurable students Learning Outcomes: Students will be able to understand the fundamental concepts of transmission lines and waveguides
Students will be able to understand the operations Microwave Resonators, power dividers and directional couplers
Students will be able to Design Microwave Filters Students will be able to calculate Noise in Active RF components
Students will be able to design Microwave amplifier design Students will be able to design microwave oscillators and mixers
Software Defined Radio (PETC0205) Teaching Scheme:
Lectures: 4Hrs/ Week
Tutorial: 1 Hr/ Week
Examination Scheme:
ISE-I 10
MSE 30 ISE-II 10
ESE 50
Course Objectives: To understand reconfigurable Modern Radio Communication System
To understand the concept of Cognitive Radio and Spectrum sharing
To understand how SDR allows access to both PHY and MAC layer
To understand GNU Radio
Course Outcomes: Aftersuccessfully completing the course students will be able to
Compare SDR with traditional Hardware Radio HDR
Simulate modern wireless system based on OFDM, MIMO & Smart Antenna
Build experiments with evaluation kits, accessing both PHY andMAC
.
Unit I : Software Defined Radio fundamentals 6L
Introduction to SDR, Need of SDR, Principles of SDR , Basic Principle and difference in Analog
radio and SDR , SDR characteristics, required hardware specifications, Software/Hardware
platform, GNU radio -What is GNU radio, GNU Radio Architecture, Hardware Block of GNU,
GNU software , MATLAB in SDR , Radio Frequency Implementation issues, Purpose of RF
front End, Dynamic Range ,RF receiver Front End topologies, Flexibility of RF chain with
software radio, Duplexer ,Diplexer ,RF filter ,LNA ,Image reject filters , IF filters , RF Mixers
Local Oscillator , AGC, Transmitter Architecture and their issues,Sampling theorem in ADC,
Noise and distortion in RF chain, Pre-distortion
Lab Tutorials : AM/FM/BPSK/QPSK/OFDM Simulation in Matlab
Unit II: SDR Architecture 10L
Architecture of SDR-Open Architecture, Software Communication Architecture,
ADC, DAC, DAC/ADC Noise, Budget, ADC and DAC Distortion
LAB Tutorials: JTRS –Goals of SCA ,Architectural details ,SDR forum Architecture
Unit III : Smart/MIMO Antennas 10L
Smart Antenna Architecture, Vector Channel Modeling , Benefits of Smart Antenna Phased
Antenna Array Theory, Adaptive Arrays, DOA Arrays, Applying Software Radio Principles to
Antenna Systems, Beam forming for systems-Multiple Fixed Beam Antenna Array, Fully
Adaptive Array , Relative Benefits and Trade-offs OF Switched Beam and Adaptive Array,
Smart Antenna Algorithms , Hardware Implementation of Smart Antennas, MIMO -frequency,
time, sample Synchronization, Space time block coding-Space Time Filtering, Space Time
Trellis Coding .
LAB Tutorials : Principles of MIMO-OFDM
Unit IV : Digital Hardware for SDR 6L
Key hardware elements, DSP processors,Role of FPGA/CPU/GPU in SDR, Applications of FPGA
inSDR, Design Principles using FPGA, Trade –offs in using DSP, FPGA and ASIC,
PowerManagement Issues in DSP, ASIC, FPGA
Unit V : Cognitive Radio 8L
Cognitive Radio Architecture, Dynamic Access Spectrum, Spectrum Efficiency, Spectrum
Efficiency gain in SDR and CR ,Spectrum Usage, SDR as a platform for CR, OFDM as PHY
layer ,OFDM Modulator, OFDM Demodulator, OFDM Bandwidth, Benefits of OFDM in CR,
Spectrum Sensing in CR, CR Network
Unit VI : Applications of SDR 8L
Application of SDR in Advance Communication System-Case Study, Challenges and Issues,
Implementation, Parameter Estimation –Environment, Location, other factors, Vertical Handoff,
Network Interoperability.
LAB Tutorials: 1)CR for Public Safety –PSCR , Modes of PSCR, Architecture of PSCR OR
2)Beagle board based SDR 3)Embedded PCSR using GNU radio
Text Books:
1. Jeffrey.H.Reed ,Software Radio : A Modern Approach to Radio Engineering , Pearson , LPE
Reference Books:
1. Markus Dillinger ,KambizMadani ,Nancy Alonistioti, Software Defined Radio : Architectures , Systems and Functions ,Wiley
2. Tony .J. Rouphael , RF and DSP for SDR, Elsevier Newness Press ,2008 3. Dr.TajStruman ,Evaluation of SDR –Main Document
4. SDR –Handbook , 8th Edition , PENTEK 5. Bruce a. Fette , Cognitive Radio Technology, Newness, Elsevier
Title of the Course: Adaptive Signal Processing
Course Code: PETC0206
L T P Credit
3 - - 3
Course Pre-Requisite:
1. Familiar with Signals and Systems, Digital Signal Processing 2. Familiarity with linear algebra and random process theory
Course Description: This course aims to introduce Adaptive signal processing. It concerns with
processing of signals where the processing parameters are adjusted continuously to suit time varying signal environmental conditions. It consists of adaptive linear combiner, often called adaptive filter
where the combiner (filter) coefficients are trained continuously. The course consists of development of various adaptation algorithms and assessing them in terms of convergence rate, computational
complexity, robustness against noisy data, hardware complexity, numerical stability etc.
Course Objectives:
5. To Understand Concept of Adaption. 6. To Demonstrate concepts of Wiener Filter.
7. To Explain Least mean-square Adaptive Filter 8. To Design Kalman Filter
Course Learning Outcomes:
CO After the completion of the course the student should be able to
Bloom’s Cognitive
level
CO1 Understand Concept of Adaption.
CO2 Demonstrate concepts of Wiener Filter.
CO3 Explain Least mean-square Adaptive Filter.
CO4 Design Kalman Filter.
CO-PO Mapping:
CO PO1 PO2 PO3
CO1 3
CO2 3
CO3 2 3
CO4 3
Assessments :
Teacher Assessment: Two components of In Semester Evaluation (ISE), One Mid Semester Examination (MSE) and one
End Semester Examination (ESE) having 20%, 30% and 50% weights respectively.
Assessment Marks
ISE 1 10
MSE 30
ISE 2 10
ESE 50
ISE 1 and ISE 2 are based on assignment/declared test/quiz/seminar/Group Discussions etc.
MSE: Assessment is based on 50% of course content (Normally first three modules) ESE: Assessment is based on 100% course content with60-70% weightage for course content
(normally last three modules) covered after MSE.
Course Contents:
Unit 1:--- Introduction: Adaptive systems, areas of application, general properties, open and closed loop adaption, Application of closed loop adaption, Examples of Adaptive
systems. Adaptive linear combiner.
7 Hrs.
Unit 2:--- Wiener Filters: Linear optimum filtering, principal of Orthogonality, minimum
mean square error, Linear prediction, forward and backward, Method of steepest decent.
7 Hrs
Unit 3:--- Least mean-square Adaptive Filtering: Overview of structure and operation, statistical LMS Theory, normalized least mean –square Adaptive filters, Frequency domain and subband Adaptive filters, Methods of squares, Recursive least squares Adaptive filters.
7 Hrs
Unit 4:---. Kalman Filters: Statement of kalman filter problem, the innovation process
estimation, filtering, initial conditions varients extended kalman filters. Square root
adaptive filters. Order –recursive Adaptive filter.
7 Hrs
Unit 5:--- Finite precision Effects: Quantization errors, least mean-square Algorithm,
Recursive least square Algorithm, Square root Adaptive filters, Order recursive filters, Fast
Transversal Filters. Tracking of Time varying systems.
7 Hrs
Unit 6:--- Adaptive Filters using Infinite-Duration Impulse Response structure: IIR
Adaptive filters-Output Error Method, Equation Error Method. Some Practical
Considerations, Laguerre Transversal Filters, Adaptive Laguerre Latice Filters.
7 Hrs
Textbooks: 1. “Adaptive filter Theory” Simon Haykin Fourth Edition Pearson publication
References:
1. “Adaptive Signal Processing” Bernard Widrow, Samual Stearns Pearson publication 2. “Theory and Design of Adaptive Filters” John R.Treichler et.al PHI private Publication.
Unit wise Measurable students Learning Outcomes: UO1: Explain Adaptive systems.
UO2: Design Wiener Filters UO3: Explain Least mean-square Adaptive Filtering
UO4: Demonstrate concept of Kalman Filter. UO5: Explain Finite precision Effects
UO6: Understand Concepts of Adaptive Filters using Infinite-Duration Impulse Response structure.
Title of the Course: Advances in Network Security Course Code: PETC0221
L T P Credit
3 1 - 4
Course Pre-Requisite: Knowledge about attacks on computer and network system
Course Description: This course will focus on graduate-level topics inryptography and network security, including: Symmetric Key and Public Key encryption algorithms, Digital Signatures, Certificates, Cryptanalysis, Key management
and distribution, Classical network attacks and their solutions, User authentication protocols, Transport-level security, Wireless network security, E-mail security, Web security, IP security, Distributed system security,
Firewalls and Intrusion detection systems.
Course Objectives: 1. Understand Block Chiper and DES principles 2. Understand Symmetric Encryption Methods 3. Identify network security threat 4. Understand Key Resources and management resources
Course Learning Outcomes:
CO After the completion of the course the student
should be able to
Bloom’s Cognitive
level Descriptor
CO1 Define Cryptography methods on Network Security
concepts and Application
I Remembering
CO2 Classify Symmetric and Asymmetric methods II Understanding
CO3 Apply Message authentication and Hash Functions III Applying
CO4 Analyze the attacks and methods of web security IV Analyzing
CO-PO Mapping:
CO 1 2 3
CO1 2 1
CO2 1
CO3 1
CO4 3 1 2
Assessments :
Teacher Assessment:
Two components of In Semester Evaluation (ISE), One Mid Semester Examination (MSE) and one EndSemester Examination (ESE) having 20%, 30% and 50% weights respectively.
Assessment Marks
ISE 1 10
MSE 30
ISE 2 10
ESE 50
ISE 1 and ISE 2 are based on assignment/declared test/quiz/seminar/Group Discussions etc.
MSE: Assessment is based on 50% of course content (Normally first three modules) ESE: Assessment is based on 100% course content with60-70% weightage for course content
(normally last three modules) covered after MSE.
Course Contents:
Unit 1:--- Overview:
Services, Mechanisms, and attacks, The OSI Security Architecture, A model for network
security, Classical Encryption Techniques: Symmetric Cipher Model, Substitution Techniques, Transposition Techniques, Rotor Machines, and Steganography
05 Hrs.
Unit 2:--- Block Ciphers and the Data Encryption Standard:
Simplified DES, Block Cipher Principles, The Data Encryption Standard, The Strength of
DES, Differential Linear Cryptanalysis, Block Cipher Design Principles, Block Cipher
Modes of Operation.
06 Hrs.
Unit 3:--- Contemporary symmetric Ciphers:
Triple DES, Blowfish, RC5, Characteristics of Advanced Symmetric Block Ciphers, Confidentially
using symmetric Encryption:Placement of Encryption Function, Traffic Confidentiality, Key
Distribution, and Random Number Generation
08 Hrs.
Unit 4:--- Public Key Cryptography and RSA:
Principles of Public Key cryptosystems, The RSA Algorithm, Key Management, other Public Key
Cryptosystems key Management, Diffle-Hellman Key exchange
07 Hrs.
Unit 5:--- Message Authentication and hash functions:
Authentication Requirements, F Authentication Function, Message Authentication
Codes, Hash Functions, Security of Hash Functions and MACs. Hash Algorithms: MD5
Message Digest Algorithm, Secure Hash Algorithm. Digital signatures and Authentication
protocols: Digital signatures, Authentication protocols and Digital signature Standard
08 Hrs
Unit 6:--- Authentication Applications:
Kerberos, X. 509 Authentication Service. Electronic Mail Security: Pretty Good Privacy,
S/MIME, IP Security Overview, IP Security Architecture, Authentications, Header,
Encapsulating Security Payload, Combining Security Associations, Key Management.
Web Security: Web Security Considerations, Secure socket layer and Transport layer
security. Secure electronic transaction. System Security: Intruders, Intrusion detection,
password management. Malicious Software, Viruses, Viruses and Related Threats,
Firewalls: Firewall Design Principles, Trusted systems.
7 Hrs
Textbooks: 1] Willam Stallings, Cryptography and Network Security, Third Edition, Pearson Education
References: 1.Cbarlie Kaufman, Radia Perlman, Mike Speciner, Network Security, Private communication in a public world, Second Edition, Pearson Education Asia, 2002
2.Atul Kahate, Cryptography and Network Security, Tata McGrawhill, 2003
Unit wise Measurable students Learning Outcomes:
1. Comprehend the objectives attacks and Encryption methods(L1) 2. Apply Block Cipher Principles (L2) 3. Compare and contrast Symmentric and Assymmentric methods(L3) 4. Classify Public Key Cryptography methods (L4) 5. Test, debug and evaluate Message authentication and Hash Function (L5)
Title of the Course: Adhoc Network
Course Code: PETC222
L T P Credit
3 1 -- 4
Course Pre-Requisite: Digital Communication, Wireless Communication Network, Wireless Sensor
Network MATLAB
Course Description: This course helps student to understand adhoc networks, MACprotocols design issues. This course helps to understand various routing algorithms ,Transport Protocols and Ad Hoc
Wireless Internet applications
Course Objectives: 1.To acquire fundamental knowledge of adhoc networks.
2 To study the MAC Protocols: design issues
3 To understand the basic concepts of Multicast routing algorithms, hybrid routing algorithm
4. To understand adhoc transport protocols. Security issues in adhoc networks 5. To understand Ad Hoc Wireless Internet Application
Course Learning Outcomes:
CO After the completion of the course the student
should be able to
Bloom’s Cognitive
level Descriptor
CO1 design technique appropriate to adhoc network systems
Design Cognitive
CO2 apply the MAC protocols Application Cognitive
CO3 discuss protocols using Directional Antenna Comprehension Cognitive
CO4 remember Security issues in adhoc networks Remembering Cognitive
CO5 discuss special issues related to Ad Hoc Wireless
Internet
Comprehension Affective
CO-PO Mapping:
CO PO I PO II PO III
CO1 2
CO2 2
CO3 3 3
CO4 3 3
CO5 2
Assessments :
Teacher Assessment:
Two components of In Semester Evaluation (ISE), One Mid Semester Examination (MSE) and one
EndSemester Examination (ESE) having 20%, 30% and 50% weights respectively.
Assessment Marks
ISE 1 10
MSE 30
ISE 2 10
ESE 50
ISE 1 and ISE 2 are based on assignment/declared test/quiz/seminar/Group Discussions etc.
MSE: Assessment is based on 50% of course content (Normally first three modules)
ESE: Assessment is based on 100% course content with60-70% weightage for course content (normally last three modules) covered after MSE.
Course Contents:
Unit 1:--- Introduction and overview Introduction to adhoc networks – definition, characteristics features, applications.
Characteristics of Wireless channel, Adhoc Mobility Models:- Indoor and out door models.
-6- Hrs.
Unit 2:--- Medium Access Protocols MAC Protocols: design issues, goals and classification. Contention based protocols- with
reservation, scheduling algorithms, protocols using directional antennas. IEEE standards: 802.11a,
802.11b, 802.11g, 802.15. HIPERLAN
-6- Hrs.
Unit 3:--- Network Protocols Routing Protocols: Design issues, goals and classification. Proactive Vs reactive routing, Unicast
routing algorithms, Multicast routing algorithms, hybrid routing algorithm, Energy aware routing
algorithm, Hierarchical Routing, QoS aware routing.
-6- Hrs.
Unit 4:--- End-End Delivery And Security
Transport layer : Issues in designing- Transport layer classification, adhoc transport protocols. Security issues in adhoc networks: issues and challenges, network security attacks, secure routing
protocols
-8- Hrs.
Unit 5:--- Cross Layer Design And Integration Of Adhoc For 4G Cross layer Design: Need for cross layer design, cross layer optimization, parameter optimization
techniques, Cross layer cautionary perspective. Integration of adhoc with Mobile IP networks.
-8- Hrs.
Unit 6:--- Ad Hoc Wireless Internet Gateways, Address mobility, Routing, Transport layer protocol, Load balancing, Pricing/billing, Provisioning of security, QoS support, Service, address, and location discovery
-6- Hrs.
Textbooks: 1. C.Siva Ram Murthy and B.S.Manoj, Ad hoc Wireless Networks Architectures and protocols, 2nd edition, Pearson Education. 2007
2. Charles E. Perkins, Ad hoc Networking, Addison – Wesley, 2000
References: 1. Stefano Basagni, Marco Conti, Silvia Giordano and Ivan stojmenovic, Mobilead hoc
networking, Wiley-IEEE press, 2004. 2. Mohammad Ilyas, The handbook of adhoc wireless networks, CRC press, 2002.
3. T. Camp, J. Boleng, and V. Davies “A Survey of Mobility Models for Ad Hoc Network
4. Research,” Wireless Commun. and Mobile Comp., Special Issue on Mobile Ad Hoc Networking Research, Trends and Applications, vol. 2, no. 5, 2002, pp. 483–502.
5. A survey of integrating IP mobility protocols and Mobile Ad hoc networks, Fekri M.
Abduljalil and Shrikant K. Bodhe, IEEE communication Survey and tutorials, v no.1 2007
6. V.T. Raisinhani and S.Iyer “Cross layer design optimization in wireless protocol stacks”Comp. communication, vol 27 no. 8, 2004.
7. V.T.Raisinhani and S.Iyer,ӃCLAIR; An Efficient Cross-Layer Architecture for
wireless protocol stacks”,World Wireless cong., San francisco,CA,May 20044.Wireless Sensor Networks: An Information Processing Approach by . F. Zhao and L.Guibas. Morgan Kaufmann, Jul. 2004.
5. Sensor Networks and Configuration: Fundamentals, Standards, Platforms, and Applications by . N. P. Mahalik. Springer Verlag, Nov. 2006
6.Wireless Sensor Networks: A Systems Perspective by , N. Bulusu and S. Jha, Editors, Artech House,
August 2005
Unit wise Measurable students Learning Outcomes:
Unit1
UO1: Student should be able to understand basic concepts of adhoc networks Unit2
UO2: Student should be able to understand basic concepts of MAC Protocols
Unit 3
UO3.1: Student should be able to understand basic concepts of Energy aware routing algorithm, UO3.2: Student should be able to understand basic concepts of Hierarchical Routing Protocols
Unit 4 UO4.1: Student should be able to understand basic concepts of adhoc transport protocols.
Unit 5 UO5.1: Student should be able to understand Need for cross layer design Security issues in adhoc
networks Unit 6
UO6.1: Student should be able to understand basic concepts of Ad Hoc Wireless Internet
Title of the Course: Internet Traffic Engineering
Course Code: PETC0223
L T P Credit
3 1 -- 4
Course Pre-Requisite:
Course Description:
Course Objectives:
To optimize an operational network so that performance requirements are met, yet network
resources are well utilized
To develop the platform for understanding the basics of routers and types of routers, and as
the background material to understand more details about a router’s critical functions, such as
address lookup and packet class classification,
Make students to understand forwarding capacity of a router is highly dependent on how
quickly it can determine to which interface transfer the packet i,e. algorithms for fast IP address lookup
Make student to understand algorithms for efficient packet classification to offer differentiated services based agreements
Make students to understand paradigm of QoS routing and its inherent relation to traffic engineering. Extending different routing algorithms to fit the QoS routing framework
To study applicability of MPLS for routing and traffic engineering for a set of representative
real-world problems
Course Learning Outcomes:
After successfully completing the course students will be able to
estimate traffic in the network, as well as what performance measures might be of interest in IP
networks
evaluate various IP router architectures and highlight their advantages and disadvantages.
apply algorithms to meet specifications viz: lookup speed, memory usage, scalability, and
updatability
evaluate performance requirements of a packet classification algorithm in terms of number of
memory accesses and the amount of storage requirement
use of numerical studies, to understand the implications of different routing schemes and roles
played by different network controls
student can solve set of routing and traffic engineering problems in which MPLS can be used by giving due consideration to path management, traffic assignment, network information
dissemination, and network management
CO After the completion of the course the
student should be able to Bloom’s Cognitive
level Descriptor
CO-PO Mapping:
CO PO1 PO2 PO3
Assessments :
Teacher Assessment:
Two components of In Semester Evaluation (ISE), One Mid Semester Examination (MSE) and one
EndSemester Examination (ESE) having 20%, 30% and 50% weights respectively.
Assessment Marks
ISE 1 10
MSE 30
ISE 2 10
ESE 50
ISE 1 and ISE 2 are based on assignment/declared test/quiz/seminar/Group Discussions etc.
MSE: Assessment is based on 50% of course content (Normally first three modules) ESE: Assessment is based on 100% course content with60-70% weightage for course content
(normally last three modules) covered after MSE.
Course Contents:
Unit1:IP traffic engineering: Evolution of Traffic engineering in internet domain,
Taxonomy and recommendation for internet traffic engineering, Performance Measures
and characteristics, applications view and traffic models, Architectural frame work, link
weight determination, Duality of the MCNF Problem
6 Hrs
Unit2: Internet Routing and Router Architectures: Architectural View of the Internet,
Allocation of IP Prefixes and AS Number, Policy-Based Routing, Point of Presence,
Traffic Engineering Implications, Internet Routing Instability. Router Architectures:
Functions, Types, Elements of a Router, Packet Flow, Packet Processing: Fast Path versus
Slow Path, Router Architectures
8 Hrs
Unit 3: Analysis of IP address lookup Algorithms: Network Bottleneck, Network
Algorithmics, Strawman solutions, Thinking Algorithmically, Refining the Algorithm,
Cleaning up, Characteristics of Network Algorithms. IP Address Lookup Algorithms :
Impact, Address Aggregation, Longest Prefix Matching, Naïve Algorithms, Binary ,
Multibit and Compressing Multibit Tries
6 Hrs
Unit 4: IP Packet Filtering and Classification Search by Length Algorithms, Search by Value Approaches, Hardware Algorithms, Comparing Different Approaches IP Packet Filtering and Classification : Classification, Classification Algorithms, Naïve Solutions, Two-Dimensional Solutions, Approaches for d Dimensions
6 Hrs
Unit 5: Quality of Service Routing: QoS Attributes, Adapting Routing: A Basic
Framework. Update Frequency, Information Inaccuracy, and Impact on Routing,
Dynamic Call Routing in the PSTN, Heterogeneous Service, SingleLink Case, A General
Framework for Source-Based QoS Routing with Path Caching , Routing Protocols for
QoS Routing, QOSPF: Extension to OSPF for QoS Routing, ATM PNNI
6 Hrs
Unit 6: Routing and Traffic Engineering with MPLS: Traffic Engineering of IP/MPLS
Networks, VPN Traffic Engineering, Problem Illustration: Layer 3 VPN, LSP Path
Determination: Constrained Shortest Path Approach, LSP Path Determination: Network
Flow Modeling Approach, Layer 2 VPN Traffic Engineering, Observations and General
Modeling Framework, Routing/Traffic Engineering for Voice Over MPLS.
8 Hrs
Unit wise Measurable students Learning Outcomes:
Title of the Course: RF IC Design
Course Code: PETC0224
L T P Credit
4 1 -- 5
Course Pre-Requisite:
Course Description:
Course Objectives:
Course Learning Outcomes:
CO After the completion of the course the
student should be able to
Bloom’s Cognitive
level Descriptor
CO-PO Mapping:
CO PO1 PO2 PO3
Assessments :
Teacher Assessment:
Two components of In Semester Evaluation (ISE), One Mid Semester Examination (MSE)
and one EndSemester Examination (ESE) having 20%, 30% and 50% weights respectively.
Assessment Marks
ISE 1 10
MSE 30
ISE 2 10
ESE 50
ISE 1 and ISE 2 are based on assignment/declared test/quiz/seminar/Group Discussions etc.
MSE: Assessment is based on 50% of course content (Normally first three modules)
ESE: Assessment is based on 100% course content with60-70% weightage for course content
(normally last three modules) covered after MSE.
Course Contents:
Unit wise Measurable students Learning Outcomes:
Title of the Course: Communication Protocol Design
Course Code: PETC0225
L T P Credit
4 1 -- 5
Course Pre-Requisite: Knowledge of Communication Protocol and network architecture
Course Description:
Course Objectives:
Course Learning Outcomes:
CO After the completion of the course the
student should be able to Bloom’s Cognitive
level Descriptor
CO-PO Mapping:
CO PO1 PO2 PO3
Assessments :
Teacher Assessment:
Two components of In Semester Evaluation (ISE), One Mid Semester Examination (MSE) and one
EndSemester Examination (ESE) having 20%, 30% and 50% weights respectively.
Assessment Marks
ISE 1 10
MSE 30
ISE 2 10
ESE 50
ISE 1 and ISE 2 are based on assignment/declared test/quiz/seminar/Group Discussions etc.
MSE: Assessment is based on 50% of course content (Normally first three modules)
ESE: Assessment is based on 100% course content with60-70% weightage for course content
(normally last three modules) covered after MSE.
Course Contents:
Unit 1:--- Communication Model: OSI and TCP/IP model, Flow control Protocols, Noisy
and Noiseless protocol, Piggybacking, HDLC
07 Hrs.
Unit 2 – IPv4, Datagrams, Fragmentation, Options, Checksum, IP over ATM, Security,IP
Package, ARP, ATMARP, ARP Package
08 Hrs.
Unit 3:--- Introduction to ICMPv4, Debugging Tools, ICMP package, Mobile IP –
Addressing, Agents, Three Phase, Ineffciency in Mobile IP
07 Hrs.
Unit 4:--- SCTP-Introduction,SCTP Services, SCTP Features, Packet Format, SCTP
Association, State transition Diagram, Flow Control
07 Hrs.
Unit 5:--- DHCP operation, Packet Format, Configuration, DNS, Name Space, DNS in
internet, Resolution, DNS messages, Types of Records, SMTP
07 Hrs.
Unit 6:--- SSH- Components,Port Forwarding,SSH packets, TFTP -
messages,Connection, Data Transfer,UDP Ports,Options, World Wide web, SNMP-
Management Components,SMI,MIB,Format and Messages
07 Hrs.
Textbooks:
References:
1, TCP/IP Protocol Suite Behrouz Fourouzan
2.Adavanced Computer Network, Dr Deven Shah,Dreamtek
3. Data Communication and Networking, Fourozon
Unit wise Measurable students Learning Outcomes:
Title of the Course: System on Chip
Course Code: PETC0226
Unit 1: Introduction to Architectures
Introduction to System on Chip (SoC); Architectures of GPP, DSP, ASIC-semi and full custom
ASICs, Gate arrays, FPGA, CPLD; Comparison among all these Architectures on the basis of related
performance parameters
Unit 2: Fundamentals of Design
Design abstractions: Behavioral Modeling, Structural Modeling, Physical; Hardware Design Flow,
Hardware Software Co-design; Design Partitions: Data Path Unit; Control unit; Case Study of
System Design; Need of IP, Types of IP, IP Life Cycle.
Unit 3: Buses and Interconnects
Bus circuits, Bus protocol and Specifications; Logic Design for Buses, System Buses; GPIO; AXI
Bus Architecture, PCI Buses.
Unit 4: Gates and Interconnect Delay
Static Complementary Gate: Logic Levels, Inverter, Delay and Transition Time, Power
Consumption, Switch Logic; Delay through Resistive Network: Delay through RC Transmission
Line, Buffer Insertion in RC Transmission Line, Cross Talk; Delay through Resistive Network: RLC
Transmission Line, Buffer insertion in RLC Transmission Line.
Unit 5: Sequential and Subsystem Design
Sequential Design: Generic Sequential System, Clocking Disciplines,
One Phase Clocking for flip-flop, Two Phase Clocking for Latches, Power Optimization, Design
Validation, Sequential Testing; Subsystem Design: Adder, Multiplier, SRAM Cell, DRAM Cell,
Flash Memory Cell.
Unit 6: Floor Planning and Low Power Architectures
Physical Design, Blocks and Channels, Routing, Global Interconnects, Power Distribution, Decap
Capacitor, Clock Distribution Methods, Floor Planning Rules; Off Chip Connections, Packages,
Effect of Power Line Inductance, I/O Architectures and Pads; Generic IC Design Flow; Architecture
for Low Power: Gate Power Control, Data Latching, Clock Gating, Architecture Driven Voltage
Scaling.
References:
1. Wayne Wolf, “Modern VLSI Design”, Prentice Hall publication, Fourth edition.
2. ION Grout, “Digital systems design with FPGAs” Newnes Publication.
Title of the Course: Measurements and Standards in
Communication Systems
Course Code: PETC0262
L T P Credit
2 -- --
Course Pre-Requisite:
Study of RF signal spectrum, Characteristics of RF signal, Wired and Wireless communication networks
Course Description:
The course is designed to make students aware of measurements in RF domain, use of RF equipment to carry out measurements on RF signals derived from various sources
Course Objectives: 1. Understanding measurement techniques for various parameters in communication system
2. Understanding instruments for signal analysis.
3. Understanding various standards in communication system
Course Learning Outcomes:
CO After the completion of the course the student should be
able to
Bloom’s Cognitive
level Descriptor
CO1 Select wright instruments for RF measurements
CO2 Evaluate performance parameters of communication system by physical measurements
CO3 Interpret standards in wired and wireless communication
systems
CO-PO Mapping:
CO 1 2 3 4 5 6 7 8 9 10 11 12 PSO1 PSO2
CO1 L M L M M L M L M L L L H H
CO2 M M M M M L L L L L L L H M
CO3 L M M M M
L L L L L L L M L
Assessments :
Teacher Assessment:
Two components of In Semester Evaluation (ISE), One Mid Semester Examination (MSE)
and one EndSemester Examination (ESE) having 20%, 30% and 50% weights respectively.
Assessment Marks
ISE 1 10
MSE 30
ISE 2 10
ESE 50
ISE 1 and ISE 2 are based on assignment/declared test/quiz/seminar/Group Discussions etc.
MSE: Assessment is based on 50% of course content (Normally first three modules) ESE: Assessment is based on 100% course content with60-70% weightage for course content
(normally last three modules) covered after MSE.
Course Contents:
Unit 1:--- Measurements and instruments for communication signal analysis:
Spectrum analyzer, Network analyzer and related measurements, harmonic
distortion analyzer, RF measurement issues, receiver related measurements.
8 Hrs.
Unit 2:---
Standards for communication systems: Study of IEEE 802.11 a, b and g
(Wi - fi) standards, 802.16 d and e Wi - MAX standards
8 Hrs.
Unit 3:---
Mobile communication standards 2G, 2.5G, 3G standards, current scenario
of 3G and 4G standards, GSM, EDGE, HSCSD, CDMA, WCDMA
standards, Concept of convergence of the standards towards broadband
communication
8 Hrs.
Textbooks:
Theodore S. Rappaport, Wireless communications: principles and practice, Pearson education
H. S. Kalsi, Electronic Instrumentation, Tata McGraw Hill, 2/e.
Vijay K. Garg, Joseph E. Wilkes, “Principle & Applications of GSM”, Person Education.
Unit wise Measurable students Learning Outcomes:
1 Student should be able to measure performance parameters of system under test
2 Student should be able to specify wireless LAN system for application in design
3 Students should be able analyses standards of cellular communication
Title of the Course: RF & Microwave Circuit Design Lab Course Code: PETC0233
L T P Credit
0 0 2 1
Course Pre-Requisite: MATLAB, Electromagnetic Engineering, Microwave Engineering.
Course Description: This Laboratory course helps students to develop understanding and
apply the concept of Microwave Engineering
Course Objectives:
1. Students should understand basic concepts of Microwave Engineering
2. Students should Design Microwave Circuits. 3. Students should able to perform Experimentation on apply Microwave Circuits.
Course Learning Outcomes:
CO After the completion of the course the student
should be able to
Bloom’s Cognitive
level Descriptor
CO1 Understand concepts of Microwave Circuits Comprehension Cognitive
CO2 Apply theory to design Microwave Circuits Applying Psychomotor
CO3 Analyze the designed Microwave circuits Analysis Cognitive
CO-PO Mapping:
CO PO1 PO2 PO3
CO1 1 3
CO2 1 3
CO3 1 3
Assessments :
Teacher Assessment:
One component of In Semester Evaluation (ISE) and one End Semester Examination (ESE)
having 50%, and 50% weights respectively.
Assessment Marks
ISE 50
ESE 50
ISE are based on practical performed/ Quiz/ Mini-Project assigned/ Presentation/ Group Discussion/ Internal oral etc.
ESE: Assessment is based on oral examination
Course Contents:
Experiment No. 1:--- Overview of Microwave Engineering
It is Expected to Perform Following Experiments as a Overview Using Virtual Lab Lab of IIT Kanpur (Separate List Enclosed)
Aim and Objectives: Overview of Microwave Engineering
Outcomes:
Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion:
-2- Hrs.
Experiment No. 2:--- Microwave Resonators, Power Dividers and Directional
Couplers
-2- Hrs.
Aim and Objectives: To Study of Microwave Resonators, Power Dividers and
Directional Couplers
Outcomes:
Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion:
Experiment No. 3:---Microwave Filters. Aim and Objectives: Design of Microwave Filters (Using CAD Tool)
Outcomes: Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion:
-2- Hrs.
Experiment No. 4:--- Characteristics of Active Components. Aim and Objectives: To Study of characteristics of Active Components
Outcomes:
Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion:
-2- Hrs.
Experiment No. 5:--- Microwave Amplifier
Aim and Objectives: Design of Single stage Microwave Amplifier Outcomes:
Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion:
-2- Hrs.
Experiment No. 6:--- Broadband Transistor Amplifier
Aim and Objectives: To Design of Broadband Transistor Amplifier Outcomes:
Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion:
-2- Hrs.
Experiment No. 7:--- Power Amplifier
Aim and Objectives: To Design of Power Amplifier
Outcomes:
Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion:
-2- Hrs.
Experiment No. 8:--- Microwave Oscillators Aim and Objectives: To Design of Microwave Oscillators
Outcomes:
Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion:
-2- Hrs.
Experiment No. 9:--- Structures of Adaptive Filter
Aim and Objectives: To Design of Microwave Mixers Outcomes:
Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion
-2- Hrs.
Textbooks:
1. Microwave Engineering, David M Pozar, wiley publication, 3rd
edition
References:
1. RF circuit design theory and applications, reinhold Ludwig, gene bogdanov, pearson publication 2
nd edition
2. Microwave Circuit Design: A Practical Approach Using ADS, Kyung-Whan Yeom, PHI publication
3. Advanced RF & Microwave Circuit Design: The Ultimate Guide to Superior Design By Matthew M. Radmanesh, Authorhouse publication
4. Passive RF and Microwave Integrated Circuits, Leo Maloratsky, Elsevier publication
Title of the Course: Adaptive Signal Processing Lab Course Code: PETC0234
L T P Credit
0 0 2 1
Course Pre-Requisite: MATLAB, Digital Signal Processing
Course Description: This Laboratory course helps students to develop understanding and
apply the concept Adaptive Signal Processing
Course Objectives:
1. Students should understand the concept of Adaption . 2. Students should understand basic concepts of Random variables & Random Processes
3. Students should study the concepts of Markov Chains ,state-space analysis and Queuing Theory
Course Learning Outcomes:
CO After the completion of the course the student
should be
able to
Bloom’s Cognitive
level Descriptor
CO1 Understand the Basic Concepts of Adaption. Application Cognitive
CO2 Design Adaptive Filters using various algorithms. Comprehension Cognitive
CO3 Realize the Adaptive filters. Construct Psychomotor
CO-PO Mapping:
CO PO1 PO2 PO3
CO1 1 3
CO2 3
CO3 3
Assessments :
Teacher Assessment:
One component of In Semester Evaluation (ISE) and one End Semester Examination (ESE)
having 50%, and 50% weights respectively.
Assessment Marks
ISE 50
ESE 50
ISE are based on practical performed/ Quiz/ Mini-Project assigned/ Presentation/ Group Discussion/ Internal oral etc.
ESE: Assessment is based on oral examination
Course Contents:
Experiment No. 1:--- Linear Optimal Filtering
Aim and Objectives: To Study Concept Linear Optimal Filtering
Outcomes:
Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion:
-2- Hrs.
Experiment No. 2:--- Steepest Decent Method
Aim and Objectives: To Study Steepest Decent Method :Case Study
Outcomes: Theoretical Background:
-2- Hrs.
Experimentation:
Results and Discussions:
Conclusion:
Experiment No. 3:--- Least Square Algorithm
Aim and Objectives: Study of Normalized Least Square Algorithm
Outcomes: Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion:
-2- Hrs.
Experiment No. 4:--- Kalmans Filter Aim and Objectives: To Study Kalmans Filter
Outcomes:
Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion:
-2- Hrs.
Experiment No. 5:--- Quantization Effect
Aim and Objectives: To Study Quantization Effect. Outcomes:
Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion:
-2- Hrs.
Experiment No. 6:--- Principal of Orthogonality
Aim and Objectives: To Study Principal of Orthogonality. Outcomes:
Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion:
-2- Hrs.
Experiment No. 7:--- To Study Recursive Least Square Algorithm. Aim and Objectives: Recursive Least Square Algorithm
Outcomes:
Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion:
-2- Hrs.
Experiment No. 8:--- Transversal Filter Aim and Objectives: To Study Transversal Filter
Outcomes:
Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion:
-2- Hrs.
Experiment No. 9:--- Structures of Adaptive Filter
Aim and Objectives: To study various structures of Adaptive Filter Outcomes:
Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion
-2- Hrs.
Experiment No. 10:--- IIR Adaptive Filter
Aim and Objectives: To study IIR Adaptive Filter Outcomes:
Theoretical Background:
Experimentation:
Results and Discussions:
Conclusion
-2- Hrs.
Reference Books: Textbooks: 1. “Adaptive filter Theory” Simon Haykin Fourth Edition Pearson publication
References: 1. “Adaptive Signal Processing” Bernard Widrow, Samual Stearns Pearson publication
2. “Theory and Design of Adaptive Filters” John R.Treichler et.al PHI private
Publication.