Connecting Theory and Practice
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![Page 1: Connecting Theory and Practice](https://reader035.fdocuments.net/reader035/viewer/2022062304/56813320550346895d99eefd/html5/thumbnails/1.jpg)
Connecting Theory and Practice
Spring 2013Mid Presentation
TechnionIsrael Institute of Technology
Supervisors:
Rolf Hilgendorf, Debby Cohen
Consultant:
Eli Shoshan
Students: Etgar Israeli, Shahar Tsiper
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Theory
Project Definition and Goals
Project Main Stages:
◦ Matlab Reconstruction
◦ AWR Activities – Part A
◦ AWR Activities – Part B
◦ A-Matrix Calibration
◦ MWC Development Support Systems
Epilogue
Contents
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Multiband model:• N – max number of transmissions• B – max bandwidth of each transmission
Goal: Blind detection + Recovery
Minimal achievable rate: 2NB << fNYQ
Model
~ ~~~
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1
2 sT
Input Block Diagram
sequencesm
q
1
2 sT
snT
snT/ ( )m qp t
Expander
m
sequences
[ ]my npf
Δ
Analog Card Digital Processing
s
p
fq
f
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Support Recovery + Reconstruction
• Support S recovery• Signal reconstruction
Sz f
~~~~
z f
SA
y f
A
S Sz f A y f †
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Output Block Diagramm sequences
[ ]my n
SupportRecovery
Reconstructor
Sz f
SA
~~~~
z f
~~~~
z f
A
S Sz f A y f †
Digital Processing
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The Mixing Series Pi(t)
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In theory there is a solid algorithm for building the A-Matrix. We use the fourier coefficients of the mixing series:
We’re interested in finding the coeff. Therefore we’ll use:
We can further simplify if the mixing series are step functions:
Building the A-Matrix
ilc
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We can now define an all constant A-Matrix:
We can now use the same A matrix in time domain. Due to the invariance for iDTFT.
Building the A-Matrix – cont.
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After the Support Recovery process:
Using Moore-Penrose psuedo-inverse process for the matrix:
Solving the problem:
Support Recovery for the A-Matrix
, 2m mS
rL r N
AA
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Matlab reconstruction algorithm
AWR Activities
A-matrix Calibration
MWC development support systems
(Labview programming Rolf/Idan)
Project Work Plan
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Understanding and fixing the Matlab code
Learning AWR tool and Modeling MWC
Deeper understanding of the main issues the
system suffers from
Developing calibration solutions for the system
Implementing the solutions on the actual system
Main Challenges
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◦ Matlab Reconstruction
◦ AWR Activities – Part A
◦ AWR Activities – Part B
◦ A-Matrix Calibration
◦ MWC Development Support Systems
Project Main Stages
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We’ve developed signal comparison
algorithm using cross-correlation.
Main Issues:
◦ Support recovery is successful at approx. 80% of
the runs (better % for qpsk than sinc)
◦ If the recovery adds redundant harmonics
◦ If time reconstruction still isn’t perfect
Matlab Reconstruction
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Understand schematics of analog part of
new MWC
Get understanding of AWR tool
Define method for input and output files
◦Matlab , CSV etc.
Enter first draft of MWC schematic
AWR - Part A
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Current Front-End + Series Generator
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Refine MWC design
◦ Get final spice models for all components
◦ Get model of card
◦ Enter final schematic
◦ Ensure synchronization between patterns
◦ Ensure synchronization with trigger
◦ How to create the input scenarios (AWR or matlab)
◦ Sampling rate for AWR simulation and for output
Basic Verification of output data using matlab
◦ Is input mapped to output as expected
◦ Limits for input signal (saturation, undetectable due to noise)
◦ Anti-aliasing filter response
AWR - Part B
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Full Current System Setup
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Understanding the Physical Issues
Using the AWR model output define A-
Matrix
◦ Perform developed procedure using model and
matlab only
◦ Perform procedure using MWC development
systems described below
A Matrix Calibration
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Phase Shifts inside the system:
◦ Signals enter with unknown phase into the analog card. We should make
sure we know how to recover the signals with their original phases.
◦ Analog Low-Pass Filter causes unknown phase shifts between the
different channels.
◦ Fixed phase shift between the mixer channels and the Expander Unit.
Noise Sources:
◦ Impedance mismatches in the input cable end – attenuator is used, and
acts as a noise source.
◦ Analog splitter before entering the different mixers provide as a noise
source.
◦ Analog Low-Pass Filter causes noise.
Main Physical Issues
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Modeling each part of the system
independently, according to schematic
Trying to develop specific solutions to each
of the micro-problems
Proposed Solutions – First Approach
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1
2 sT
Main Physical Issues
sequencesq
m
1
2 sT
snT
snT/ ( )m qp t
Expander
m
sequences
[ ]my npf
Δ
Analog Card
Digital Processing
ATT
Unknown phase
Splitter Noise
Attenuator Noise
LPF – Noise & phase shift
Phase shift
Unknown?
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Multiplying by a correction matrix before applying the
original A-Matrix - .
◦ In order to get we planned to drive an impulse function into the
system, and determine the impulse response for each Hardware
Channel
Applying a filter after multiplying the signal with the A-
Matrix -
◦ We’ll use multiple known fixed carriers inputs (modulated sincs
or simple sine waves) in order to devise the required
Second Approach – 2 Main Stages
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Thinking on new calibration methods after
examining a full analog model or real MWC
System - Still work in progress
Synchronizing the A matrix’s via cyclic shifts
to the mixer series - Might be necessary
Current Approach
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Data acquisition using NI converter with
external sampling clock
Immediate system based on Tabor AWG
◦ Load data from AWR simulation
Final development system using NI AWG
◦ NI sync card and external clocking
MWC Development Support Systems
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Matlab:
◦ Used for full modeling of the MWC system –
Already given – need to be fixed
◦ Calibration Methods
AWR:
◦ Implementing an analog model of the entire
MWC system.
◦ Linking the analog AWR frontend and the
digital Matlab backend
Labview:
◦ Implementing calibration procedure
Systems Used In Project
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Main missions week1 2/6 week2 9/6 week3 16/6 week4 23/6 week5 30/6 week6 7/7 week7 14/7
Fix Matlab reconstruction algorithm
Understanding the existing Matlab code and Sub-Nyquist Radar AWR
Becoming proficient in AWR environment
Understand schematics of analog part of new MWC
Define method for the input and output betweem AWR amd Matlab
Enter first draft of MWC schematic
Entering second stage of project: Refine MWC design
Project Gantt - 1st Stage
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Thank You!
Spring 2013Mid Presentation
Supervisors: Rolf Hilgendorf, Debby CohenStudents: Etgar Israeli, Shahar Tsiper
TechnionIsrael Institute of
Technology