Spring 2013 Mid Presentation Technion Israel Institute of Technology Supervisors:Rolf Hilgendorf, Debby Cohen Consultant:Eli Shoshan Students:Etgar Israeli, Shahar Tsiper

 Theory Theory  Project Definition and Goals Project Definition and Goals  Project Main Stages: Project Main Stages: ◦ Matlab Reconstruction Matlab Reconstruction ◦ AWR Activities – Part A AWR Activities – Part A ◦ AWR Activities – Part B AWR Activities – Part B ◦ A-Matrix Calibration A-Matrix Calibration ◦ MWC Development Support Systems MWC Development Support Systems  Epilogue Epilogue

 Multiband model: N – max number of transmissions B – max bandwidth of each transmission  Goal: Blind detection + Recovery  Minimal achievable rate: 2NB << f NYQ ~~ ~~

Expander Δ

Support S recovery Signal reconstruction ~~ ~~

Support Recovery Reconstructor ~~ ~~ ~~ ~~

 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:

 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.

 After the Support Recovery process:  Using Moore-Penrose psuedo-inverse process for the matrix:  Solving the problem:

 Matlab reconstruction algorithm  AWR Activities  A-matrix Calibration  MWC development support systems (Labview programming Rolf/Idan)

 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

◦ Matlab Reconstruction ◦ AWR Activities – Part A ◦ AWR Activities – Part B ◦ A-Matrix Calibration ◦ MWC Development Support Systems

ParameterValue Signal“qpsk” N6 q5 B19.5 Mhz fp19.8 Mhz fnyq5 Ghz SupRecSuccess

 Amplitudes normalized  Sinc signal used to demonstrate in time domain for visibility ParameterValue Signal“sinc” N6 q5 B19.5 Mhz fp19.8 Mhz fnyq5 Ghz SupRecSuccess

1. Step 1: measuring the delay between Input/Output signals using xcorrelation (upper Graph). 2. Step 2: Realigning the signals in time- domain. 3. Step 3: Insuring the signals are aligned (lower graph)

* Quadrature Phase Shift Keying

 Understand schematics of analog part of new MWCschematics  Get understanding of AWR tool  Define method for input and output files ◦ Matlab, CSV etc.  Enter first draft of MWC schematic

 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

 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

 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.

 Modeling each part of the system independently, according to schematic  Trying to develop specific solutions to each of the micro-problems

Expander Δ ATT Unknown phase Splitter Noise Attenuator Noise LPF – Noise & phase shift Phase shift Unknown ?

 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

 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

 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

Main missions week1 2/6week2 9/6week3 16/6week4 23/6week5 30/6week6 7/7week7 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

Spring 2013 Mid Presentation Supervisors: Rolf Hilgendorf, Debby Cohen Students: Etgar Israeli, Shahar Tsiper Technion Israel Institute of Technology