Connecting Theory and Practice

1. Technion Israel Institute of Technology Connecting Theory and Practice Spring 2013 Mid Presentation

2. Contents • 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

3. ~ ~ ~ ~ Model • Multiband model: • N – max number of transmissions • B – max bandwidth of each transmission • Goal: Blind detection + Recovery • Minimal achievable rate: 2NB << fNYQ

4. Input Block Diagram Analog Card Digital Processing Expander Δ

5. ~ ~ ~ ~ Support Recovery + Reconstruction • Support S recovery • Signal reconstruction

6. ~ ~ ~ ~ ~ ~ ~ ~ Output Block Diagram Digital Processing Support Recovery Reconstructor

7. The Mixing Series Pi(t)

8. Building the A-Matrix • 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:

9. Building the A-Matrix – cont. • 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.

10. Support Recovery for the A-Matrix • After the Support Recovery process: • Using Moore-Penrose psuedo-inverse process for the matrix: • Solving the problem:

11. Project Work Plan • Matlab reconstruction algorithm • AWR Activities • A-matrix Calibration • MWC development support systems (Labview programming Rolf/Idan)

12. Main Challenges • 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

13. Project Main Stages • Matlab Reconstruction • AWR Activities – Part A • AWR Activities – Part B • A-Matrix Calibration • MWC Development Support Systems

14. Matlab Reconstruction • 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

15. AWR - Part A • 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

16. Current Front-End + Series Generator

17. AWR - Part B • 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

18. Full Current System Setup

19. A Matrix Calibration • 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

20. Main Physical Issues • 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.

21. Proposed Solutions – First Approach • Modeling each part of the system independently, according to schematic • Trying to develop specific solutions to each of the micro-problems

22. Main Physical Issues Unknown ? Attenuator Noise Analog Card Digital Processing Expander ATT Δ Splitter Noise Phase shift Unknown phase LPF – Noise & phase shift

23. Second Approach – 2 Main Stages • 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

24. Current Approach • 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

25. MWC Development Support Systems • 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

26. Systems Used In Project • 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

27. Project Gantt - 1st Stage

28. Technion Israel Institute of Technology Thank You! • Spring 2013 • MidPresentation • Supervisors: Rolf Hilgendorf, Debby Cohen • Students: Etgar Israeli, Shahar Tsiper