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Connecting Theory and Practice Spring 2013 Mid Presentation Technion Israel Institute of Technology Supervisor s: Rolf Hilgendorf, Debby Cohen Consultant : Eli Shoshan Students: Etgar Israeli, Shahar Tsiper

Connecting Theory and Practice

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Technion Israel Institute of Technology. Connecting Theory and Practice. Spring 2013 Mid Presentation. Contents. Theory Project Definition and Goals Project Main Stages: Matlab Reconstruction AWR Activities – Part A AWR Activities – Part B A-Matrix Calibration - PowerPoint PPT Presentation

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Page 1: Connecting Theory and Practice

Connecting Theory and Practice

Spring 2013Mid Presentation

TechnionIsrael Institute of Technology

Supervisors:

Rolf Hilgendorf, Debby Cohen

Consultant:

Eli Shoshan

Students: Etgar Israeli, Shahar Tsiper

Page 2: Connecting Theory and Practice

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

Page 3: Connecting Theory and Practice

Multiband model:• N – max number of transmissions• B – max bandwidth of each transmission

Goal: Blind detection + Recovery

Minimal achievable rate: 2NB << fNYQ

Model

~ ~~~

Page 4: Connecting Theory and Practice

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

Page 5: Connecting Theory and Practice

Support Recovery + Reconstruction

• Support S recovery• Signal reconstruction

Sz f

~~~~

z f

SA

y f

A

S Sz f A y f †

Page 6: Connecting Theory and Practice

Output Block Diagramm sequences

[ ]my n

SupportRecovery

Reconstructor

Sz f

SA

~~~~

z f

~~~~

z f

A

S Sz f A y f †

Digital Processing

Page 7: Connecting Theory and Practice

The Mixing Series Pi(t)

Page 8: Connecting Theory and Practice

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

Page 9: Connecting Theory and Practice

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.

Page 10: Connecting Theory and Practice

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

Page 11: Connecting Theory and Practice

Matlab reconstruction algorithm

AWR Activities

A-matrix Calibration

MWC development support systems

(Labview programming Rolf/Idan)

Project Work Plan

Page 12: Connecting Theory and Practice

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

Page 13: Connecting Theory and Practice

◦ Matlab Reconstruction

◦ AWR Activities – Part A

◦ AWR Activities – Part B

◦ A-Matrix Calibration

◦ MWC Development Support Systems

Project Main Stages

Page 14: Connecting Theory and Practice

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

Page 15: Connecting Theory and Practice

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

Page 16: Connecting Theory and Practice

Current Front-End + Series Generator

Page 17: Connecting Theory and Practice

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

Page 18: Connecting Theory and Practice

Full Current System Setup

Page 19: Connecting Theory and Practice

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

Page 20: Connecting Theory and Practice

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

Page 21: Connecting Theory and Practice

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

Page 22: Connecting Theory and Practice

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?

Page 23: Connecting Theory and Practice

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

Page 24: Connecting Theory and Practice

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

Page 25: Connecting Theory and Practice

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

Page 26: Connecting Theory and Practice

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

Page 27: Connecting Theory and Practice

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

Page 28: Connecting Theory and Practice

Thank You!

Spring 2013Mid Presentation

Supervisors: Rolf Hilgendorf, Debby CohenStudents: Etgar Israeli, Shahar Tsiper

TechnionIsrael Institute of

Technology