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PROJECT PROPOSAL

FOR CONSIDERATION UNDER

TECHNOLOGY SYSTEMS DEVELOPMENT (TSD) PROGRAMME

Effect of Adaptive Filters and Windowing Function on Bandwidth , Directivity and Time of Digital Beamforming

SUBMITTED BY

Muthyala R Gowtham Master of Technology in Communication Systems

Christ University Faculty of Engineering Bangalore

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CONTENTS

S.No ITEMS Page No(s) 1 Cover Sheet

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2 Project Summary

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3 Core Proposal

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4 Bio-Data of the Principal Investigator/ Co- Principal Investigator

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5 Budget Estimates

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6 Undertaking from the Principal Investigator

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7 Endorsement from Head Of the Organisation

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8 Endorsement from Collaborating Industry/ Agency

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1. COVER SHEET

1. Project Title:Effect of Adaptive Filters and Windowing on Bandwidth, Directivity and Time of Digital Beam forming.

2. Principal Investigator (PI):

Name: Muthyala R Gowtham

Designation: Student

Address: Christ University

Telephone No: 9620623956

E-mail: muthyala.gowtham@mtech.christuniversity.in

Date of birth: 01-08-1990

3. Names and Addresses of Collaborating Organisations

Christ University Faculty of Engineering,

Kengeri Campus,

Mysore Road,

Bangalore.

4. Duration of the Project The project duration lasts for 6 months

5. Budget for the Project (Amount in Lakhs of Rupees)

S.No ITEM CUFE Share

Other Agencies Share

For office use

File No:

Date of Receipt:

4

Total

6. Project Objectives The primary objectives are, Digital Beam Forming

Directivity & BW Measurements

Usage of Adaptive Algorithms

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2. PROJECT SUMMARY

1. Project Title: Effect of Adaptive Filtering and Windowing on Bandwidth, Directivity and Time of Digital Beam forming.

2. Principal Investigator: Muthyala R Gowtham

3. Collaborating University: Christ University

4. Duration:6 months

5. Total Budget: xxx

5.1 Christ University Share:xxx

5.2 Collaborators Share: xxx

6. Objectives: Digital Beam Forming Directivity & BW Measurements Usage of Adaptive Algorithms

7. Innovative Elements/Components of the Project: Reduction of side lobes such that increasing the directivity, error minimizing time using different windowing functions and adaptive filters.

8. Outcome/ Deliverables and their Expected Impact (In bullet form): Improved solution to reduce interference levels Improvement of system capacity Reduce the overall cost of network

9. Target Beneficiaries:Mobile Wireless Operators

10.Brief Technical Details , giving Justifications for the Project, the underlying Scientific Basis and the Methodology:

10.1 Aim of Project: The antenna array exhibit flexibility in the design of radiation patterns.

Conventionally, arrays are designed by controlling excitation levels, phase levels and

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space distribution of elements. In practice, for pre designed radiating elements in the array, one of the above parameters is considered for the design keeping the others fixed. When the elements of the array are uniformly excited, the first side lobe level is found to be -13.5 dB. It is of interest here to reduce the side lobe levels, increase the directivity by decreasing the beam width and also to reduce the time required to minimize the error minimization time using different window functions and adaptive filters.

10.2 Introduction: There is an ever-increasing demand on mobile wireless operators to provide voice and high-speed data services. At the same time, these operators want to support more users per base station to reduce overall network costs and make the services affordable to subscribers. As a result, wireless systems that enable higher data rates and higher capacities are a pressing need. Smart antenna technology offers a significantly improved solution to reduce interference levels and improve the system capacity. With this technology, each user's signal is transmitted and received by the base station only in the direction of that particular user. This drastically reduces the overall interference in the system. Digital beam forming (DBF) technology is progressed with the development of adaptive algorithms and architectures. Multiple Beam formation using the same antenna array is achieved by using the LMS algorithm. The performance criteria of a digital beam forming system are the number of antenna elements, the IF sampling rate, the RF frequency and the number of iterations required to converge. Least Mean Square (LMS) and Recursive Least Square (RLS) algorithms are being chosen to update complex weights to form the beam in the desired direction.

10.3 Digital Beam forming: In digital beam forming, as all know the operations of phase -shifting and amplitude scaling for each antenna element, and summation for receiving, are done digitally. Either general-purpose DSPs or dedicated beam forming chips are used [1]. Digital processing requires that the signal from each antenna element is digitized using an A/D converter. Since radio signals above shortwave frequencies (>30 MHz) cannot be directly digitized at a reasonable cost, so as a result the digital beam forming receivers uses the analog RF translators to shift the signal frequency down before the A/D converters.

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Fig.1: Digital Beam forming Receiver One set of antenna elements RF translators, and A/D converters can be shared by a number of beam formers. All RF translators and A/D converters share common oscillators. Within the digital beam former, all digital down-converters have common clock, and are set for the same center frequency and bandwidth. Their digital local oscillators are in-phase so that all phase shifts are identical [5]. Each DDC baseband output is multiplied by the complex weight for its antenna element, and the results are summed to produce one baseband signal with directional properties. A demodulator would then follow to recover information.

10.4 Adaptive Filter Algorithms:

The LMS and RLS Adaptive Algorithms: The LMS (least mean squares) algorithm is an approximation of the steepest descent algorithm which uses an instantaneous estimate of the gradient vector (L.C. Godara, 1997).The task of the LMS algorithm is to find a set of filter coefficients c that minimize the expected value of the quadratic error signal, i.e., to achieve the least mean squared error. The basic idea behind LMS filter is to approach the optimum filter weights, by updating the filter weights in a manner to converge to the optimum filter weight. The algorithm starts by assuming small weights and at each step, by finding the gradient of the mean square error (MSE), the weights are updated. That is, if the MSE-gradient is positive, it implies, the error would keep increasing positively, if the same weight is used for further iterations, which means we need to reduce the weights. In the same way, if the gradient is negative, we need to increase the weights. The RLS (recursive least squares) algorithm is another algorithm for determining the coefficients of an adaptive filter. In contrast to the LMS algorithm, the RLS algorithm uses information from all past input samples along with the current samples to estimate the (inverse of the) autocorrelation matrix of the input vector. To decrease the influence of input samples from the far past, a weighting factor for the influence of each sample is used.

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10.5 Windowing Techniques:

Taylor, Hamming, Blackman and Uniform Window Functions Taylor window allows you to make trade-offs between the main lobe width and side lobe level. The Taylor distribution avoids edge discontinuities, so Taylor window side lobes decrease monotonically. Taylor window coefficients are not normalized. Taylor windows are typically used in radar applications, such as weighting synthetic aperture radar images and antenna design. The uniform window is really no window at all. It is sometimes called the boxcar function because it looks like a boxcar, a pulse that is unity for all values of time [3].The uniform window provides the best frequency resolution and amplitude accuracy, but can only be used if the measured signal is periodic in the time record. This condition is rarely met with naturally occur- ring signals, but can be met in controlled testing.

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3. CORE PROPOSAL

1. Title of the Project: Effect of adaptive Filtering and Windowing on Bandwidth, Directivity and Time of Digital Beam forming

2. Duration : 6 months 3. Names of Participating Universities: Christ University 4. Objectives of the Proposal:

a. Digital Beam Forming b. Directivity & BW Measurements c. Usage of Adaptive Algorithms

5. Fulfillment of Technology Qualifiers Criteria: Please tick if the proposal is

based on established R&D outcome/results conforming to national / international specifications potentially useful, demand driven and required by other agencies and users

a development of technology for multiple applications an adaptation of existing technology for its applications other than originally intended

meeting a critical national need ( present/ future ) and strengthening technological capabilities for the same

an application of advanced science and technology with a promise of giving competitive solutions

6. Origin and Justification of the Proposal The origin of the proposal is with the development of Smart Antenna Technology which uses the advanced DSP Processors and advanced algorithms, which are used for solving the present major problem in Mobile Communications i.e, the Bandwidth (available) for accommodation of the increasing users. Hence this proposal can yield a better solution for the Network operators.

7. Summary Outline of the Project:

7.1 Smart Antenna: For collecting the information from the enemy countries the technology of smart antennas are used. The growing cell phone industry was also later attracted to the smart antennatechnology. The digital radio technology that was embedded in the mobile phone,wireless networks, and satellite communication industries could also create a newopportunities for the smart antennas in the late 1990s, the developments in the multipleinput multiple output antenna system was also in cooperated to the wireless technologies.

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The LMS algorithm was developed by Stanford University Professor Bernad Widrow and Ted Hoff that automatically adjusts an antennas directivity pattern to reinforce desired signals. For recovering direct sequence spread spectrum signals in the presence of narrowband co-channel interference, Ted Compton at Ohio State University later developed an adaptive antenna technique. Comptons method, developed in 1974, only requires the knowledge of the desired signals pseudorandom noise (PN) code and not its direction of arrival.

To reduce co-channel interference in digital mobile networks Jack Winters showed in 1984 that received signals from multiple antennas can be combined using the optimum combining technique.

7.2 Digital Beam forming: Digital Beam forming (DBF) combines antenna technology with high performance

up/down conversion, analog to digital conversion and digital signal processing to provide receivers with very high spatial selectivity. Digital signal processing is used in DBF technology to estimate the direction in which incoming RF energy is incident on an antenna array.DBF receivers multiply each users signal by complex weight vectors that adjust the excitation amplitudes and phases of the signal from each antenna element. DBF concepts first evolved in sonar and radar systems and with the advent of multimillion gate FPGAs it has become feasible to perform DBF for sixteen or more antenna elements at up to 10 GHz carrier frequency. Digital beam formers can be deterministic or adaptive when they track an arriving signal as it moves across in azimuth or elevation. DBF technology is rapidly making forays into areas like SDR using advanced phased array antennas to dramatically lower CCI (Co-channel interference). When compared to the conventional phased array antennas it offers additional flexibility and precision in the digital domain which has further led to significant improvements in beam forming of multiple independent beams, adaptive pattern nulling, space-time adaptive processing (STAP), direction finding (DF). The adaptive nature of DBF algorithms discussed herein allows the nulls of an antenna radiation pattern to be steered in the directions of interference signals. DBF systems today utilize predominantly digital receivers; the received RF signals are detected and digitized at the element level. The RF signal from an antenna element is down-converted, digitized and further digitally down converted. The adaptive algorithm must process the baseband signal. Each element has its own ADC and DDC channel. Digital beam formers tend of have IF frequencies in excess of 10MHz. This requires ADCs with sampling rates upwards of 30 MSPS with 16 bit resolution. Commercial High speed ADCs consumes high power. The hardware expense and power consumption increase linearly with the number of antenna elements when one ADC is used per antenna element. The processing complexity of receiving system increases as the number of array elements in the array grow.

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Fig a: Transmitter Section

Fig b. Receiver Section For beam forming, the complex baseband signals are multiplied by the complex

weights to apply the phase shift and amplitude scaling required for each antenna element.

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Fig. c: Complex Multiplier

Fig d. DBF Receiver

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7.3 Adaptive Filter Algorithms:

Weight Generation Methods Weights have a significant impact on the output of the antenna array. Since the array factor is a linear function of the weights, weighting methods are well developed and can be selected to meet a wide range of objectives [7]. The objectives are pattern steering, nulling energy from specific directions relative to an array, minimizing the Mean Squared Error (MSE) between a desired output and the actual output, or minimizing the side lobe level outside a specified beam width in linear arrays. Algorithms: The LMS (least mean squares) algorithm is an approximation of the steepest descent algorithm which uses an instantaneous estimate of the gradient vector (L.C. Godara, 1997).The task of the LMS algorithm is to find a set of filter coefficients c that minimize the expected value of the quadratic error signal, i.e., to achieve the least mean squared error. The basic idea behind LMS filter is to approach the optimum filter weights, by updating the filter weights in a manner to converge to the optimum filter weight. The algorithm starts by assuming small weights and at each step, by finding the gradient of the mean square error (MSE), the weights are updated. That is, if the MSE-gradient is positive, it implies, the error would keep increasing positively, if the same weight is used for further iterations, which means we need to reduce the weights. In the same way, if the gradient is negative, we need to increase the weights. The RLS (recursive least squares) algorithm is another algorithm for determining the coefficients of an adaptive filter. In contrast to the LMS algorithm, the RLS algorithm uses information from all past input samples along with the current samples to estimate the (inverse of the) autocorrelation matrix of the input vector. To decrease the influence of input samples from the far past, a weighting factor for the influence of each sample is used.

7.4 Windowing:

Taylor window allows you to make trade-offs between the main lobe width and side lobe level. The Taylor distribution avoids edge discontinuities, so Taylor window side lobes decrease monotonically. Taylorwindow coefficients are not normalized. Taylor windows are typically used in radar applications, such asweighting synthetic aperture radar images and antenna designthe uniform window is really no window at all. It is sometimes called the boxcar function because it lookslike a boxcar, a pulse that is unity for all values of time. The uniform window provides the best frequency resolution and amplitude accuracy, but can only be used if the measured signal is periodic in the time record.This condition is rarely met with naturally occur- ring signals, but can be met in controlled testing.

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8. Expected Outcome :

Fig: Single Beam Radiation using Hamming window and LMS Algorithm at 45degree

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Fig: Single Beam Radiation using Hamming window and RLS Algorithm at 45degree

9. Deliverables of the Project

The deliverables of the Project is the efficient code with simulation results so that they can be useful for the respective applications for network operators. The code can be modified according to our applications.

10. Methodology

The methods followed are as follows, First we need to choose which type of Antenna Arrays would be liked to use. Based upon that we need to build code for antenna array pattern. Second, on decision of choosing required model, we need to generate the Beam forming with appropriate inputs. Then by applying the algorithms described earlier simulate the code. Lastly based upon the results choose the best algorithm and technique for the particular application.

11. Work Plan Using the MATLAB software and following the above prescribed methodology.

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4.BIO-DATA OF THE PRINCIPAL INVESTIGATOR

1. Name: Muthyala R Gowtham

2. Gender: Male

3. Date of Birth: 01-08-1990

4. Designation :Student (M.Tech)

5. Postal Address: S/o M Radha Krishnaiah, 4th Lane Ravindranagar, KP Gate Road,

A K Nagar PO, Nellore-524004.

Andhra Pradesh

6. Phone Numbers:09494144383, 09620623956

7. Email Id:muthyala.gowtham@mtech.christuniversity.in

8. Qualification:

S.No. Degree Institution Year 1 B Tech Priyadarshini college of

Engineering & Technology 2011

2 M Tech Christ university Faculty of Engineering

2015

9. Sponsored Projects:

S. No

Title Sponsoring Agency

Period Amount (Rupees in lakhs)

1 RFID Based Control System

PRIK 6 months xx

2 Effect of Windowing on Directivity & BW

CUFE 6 months xx

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5. BUDGET ESTIMATES

1. Break-up of the Total Budget :

S.

No

Item 1st Year 2nd Year 3rd Year Total

D

ST

Collabor

ator*

D

ST

Collabor

ator*

D

ST

Collabor

ator*

D

ST

Collabor

ator*

1. Manpower

2. Consumable

s

3. Contingency

4. Other Costs (Outsourcing,Fabrication, Testing, Patents, etc.)

5. Travel

6 Permanent Equipment

7 Overhead

Charges

Total

2. Itemised Budget a.Man Power: Budget for Salaries

Designation Qualification Salary per

month

Number of

Persons

Amount (Rupees in Lakhs)

b. Consumables:

1st Month 3rd Month 6th Month Total Justification including the basis of cost

estimates/quotations

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c. Contingencies Budget for Contingencies

1st Month 3rd Month 6th Month Total Justification including

the basis of cost estimates

d. Others

1st Month 3rd Month 6th Month Total Justification including the basis of cost

estimates

e. Travelling

1st Month 3rd Month 6th Month Total Justification including the basis of cost

estimates

f. Budget for Equipment relevant to this project

Description

of Equipment

Foreign/Indigenous Unit

LandedCost (CIF+Custom

Duty+ others )

Number

of Items

Total (Rupees

in

Lakhs)

Justification

in relation to Project

requirement

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6. UNDERTAKING FROM THE PRINCIPAL INVESTIGATOR

Project Title:Effect of Adaptive Filtering and Windowing on Bandwidth, Directivity and Time of Digital Beam forming

1. I have carefully read the terms and conditions of the Technology Systems Development Programme and I agree to abide by them.

2. I have not submitted this or a similar Project Proposal elsewhere for financial support. 3. I shall ensure that no item/equipment shown available in the Project Proposal from my

Organization, shall be purchased under the Project. 4. I undertake that idle capacity of the permanent equipment procured under the Project will

be made available to other users.

5. I have enclosed the following :

a. Endorsement from the Head of the Organization (on letter head) b. Endorsement from the Collaborating Industry/Agency

c. Project Proposal complete in all respect (15 hard copies and a soft copy)

Principal Investigator: Name Muthyala R Gowtham

Signature MRGowtham

Date 19/9/2014

Place Bangalore

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7. ENDORSEMENT FROM HEAD OF ORGANISATION

Project Title :Effect of Adaptive Filtering and Windowing on Bandwidth, Directivity and Time of Digital Beam forming

1. Affirmed that the Organisation welcomes the participation of Dr/Mr/Ms Muthyala R Gowthamas the PI for the Project and that in the unforeseen and legitimate event of discontinuation by the PI, the Co-PI will assume full responsibility for completion of the Project. Information to this effect, endorsed by me, will be promptly sent to DST 2. Affirmed that the equipment and basic as well as other administrative facilities as per the terms and conditions of the award of the Project, will be made available to the Investigator(s) throughout the duration of the Project 3. The Organisation shall ensure that the financial and purchase procedures are followed as per the prevailing norms of the Organisation, within the allocated budget. 4. The Organisation shall provide timely the Statement of Expenditure and the Utilisation Certificate of the Funds under the Grant as required by DST in the prescribed format.

(Head of Organisation) Seal/Stamp

Date Place

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8. Endorsement from collaborating Industry/ Agency

(On the official letter- head)

I have gone through the Project Proposal entitled Effect of Adaptive Filtering and Windowing on Bandwidth, Directivity and Time of Digital Beam forming submitted by) Muthyala R Gowtham of Christ University for DST funding and noted the obligations and responsibilities indicated in our name as stated below :

1. Contribution in financial terms (Rupees in Lakhs)

2. Contribution in kind (List activities)

I hereby affirm that my Organisation/Industry is committed to participate in the Project to the full extent as indicated in the Project Proposal including the financial liabilities accruing therefrom as detailed above. A summary profile of my Organisation is given below:

Name of Organisation Nature of Business Number of Employees Annual Turn over

The Annual Report for the preceding financial year is enclosed.

(Head of the Industry/Agency) Seal/Stamp

Date Place

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REFEREES REPORT

Please tick in the boxes and enter your comments in the space provided. Please be as objective as possible, as PAC relies substantially on referees reports.

DST Reference No :

PROJECT TITLE :

PRINCIPAL INVESTIGATOR :

1. Suitability under Technology Qualifiers Criteria (Tick one or more)

The Technology is

Based on established R&D outcome/ results. Conforming to national / international specifications Potentially useful, demand driven and required by other agencies and users (name them) A development of technology for multiple applications An adaptation of existing technology for its applications other than originally intended Meeting a critical national need ( present/ future ) and/or strengthening technological capabilities for the same

An application of advanced science and technology with a promise of giving competitive solutions

Please tick one :

Suitable

Not Suitable

If considered `Suitable, indicate the Qualifiers criteria being satisfied by ticking the appropriate box (es). If considered `Unsuitable, skip all other items and directly go to item (9)

2. Objectives:

Please tick one :

Precise and well formulated

Vague and lacking precision/ focus

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3. Work Plan including Methodology and Time Schedules:

Please tick one : Well planned and practical

Needs revision

Impractical

4. Opinion on Proposed Budget and Manpower :

4.1 Justification for Equipment in relation to the Project Objectives:

4.2 Spares and Consumables:

4.3 Travel :

4.4 Expenditure on other Items (Fabrication etc):

4.5 Total Budget :

4.6 Manpower requested :

1. Opinion on Professional Competence of PI and the Project Team with regard to the Project under review:

5.1 PIs Publication Record in the related Area

a) International Journals

b) National Journals

c) International Conferences/National Conferences

5.2 Patents

5.3 PIs Experience in the related Area(s)

5.4 General Opinion on Competence of PI, Co-PI and the Team

6. Track Record and Commitment of the Industrial Collaborator, if any. (Opinion may be given only on the basis of reliable information)

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7. Comments on Involvement of PI in other Projects (too many or unrelated)

8. General Comments on the Project Proposal as a whole

9. Rating of the Project (Please tick one)

Excellent:

Very Good:

Good:

Fair:

Poor:

10. Recommendations (Please tick one)

Recommended

Needs Revision (Give Suggestions)

Not Recommended (Give Critical View)

Signature Name Address Phone(s) Fax Email

Date:

For official Use Only

Date on which the Proposal was sent to the Referee:

Date on which the Referees Report was received: