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Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)
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Real-time Implementation of Sphere Decoder-based MIMO Wireless System (EUSIPCO'2006)

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Presentation on the implementation of a real-time wireless MIMO system Based on a Sphere Decoder. (EUSIPCO'2006)

Presentation on the implementation of a real-time wireless MIMO system Based on a Sphere Decoder. (EUSIPCO'2006)

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  • 1. Real-Time Implementation of a Sphere Decoder-Based MIMO Wireless System 14th EURASIP European Signal Processing Conference, EUSIPCO 4-8th September 2006, Florence, Italy Institute for Digital Communications School of Engineering and Electronics University of Edinburgh Communications and Digital Signal Processing Area Mondragon Goi Eskola Politeknikoa University of Mondragon
    • TexPoint fonts used in EMF: A A A A A A A
  • 2. Index
    • Introduction
    • Sphere decoder
    • MIMO prototyping platform
    • Real-time implementation
    • Results
    • Conclusions and future work
  • 3. Index
    • Introduction
    • Sphere decoder
    • MIMO prototyping platform
    • Real-time implementation
    • Results
    • Conclusions and future work
  • 4. Introduction Background The Sphere Decoder is considered the most promising approach to Maximum Likelihood MIMO detection [Viterbo99][Damen03]. Several interesting real-time implementations of the SD algorithm:
    • ASIC implementations
    • FPGA implementations
    However, the integration of the Sphere Decoder in a real-time system needs to be further analyzed to evaluate BER and throughput degradation due to:
    • Fixed-point operation.
    • Non-ideal parameter estimation and channel preprocessing.
    K-best: 53 Mbps constant. (4x4 16-QAM, Eb/No = 20 dB) [Wong02] Full search: 114.5 Mbps variable (4x4 16-QAM, Eb/No = 20 dB) [Barbero05] Full search: 169 Mbps variable. (4x4 16-QAM, Eb/No = 20 dB) [Burg05]
  • 5. Introduction Motivation Sphere Decoder Univ. of Edinburgh
    • Real-Time implementation
    • System Generator
    • Flat Rayleigh channel
    • Validation:
      • HW in the loop.
      • Assumptions:
        • Perfect Ch. Est.
        • Perfect Sync.
        • Offline inv., Chol.
    Real-Time Prototyping Platform Univ. of Mondragon
    • System Generator-based
    • Implemented algorithms:
      • Flat MIMO channel emulator
      • Synchronization
      • Channel estimation
      • Basic linear detectors
      • 12-bits ADC resolution
  • 6. Introduction Objectives 1.- Integration of the sphere decoder algorithm in the complete MIMO platform: a.- Platform for validating and comparing different implementations of the Sphere Decoder algorithm. b.- Complexity analysis. 2.- Evaluation of the BER and throughput degradation due to: a.- Fixed point resolution. b.- Estimation and synchronization errors. c.- Validation maintaining the flat channel assumption: c1.- Low-rate real burst transmissions. c2.- High-rate channel emulator.
  • 7. Index
    • Introduction
    • Sphere decoder
    • MIMO prototyping platform
    • Real-time implementation
    • Results
    • Conclusions and future work
  • 8. Sphere Decoder System Model
  • 9. Sphere Decoder Concept
  • 10. Sphere Decoder Algorithm
  • 11. Sphere Decoder Algorithm
  • 12. Sphere Decoder Implementation work at the Univ. of Edinburgh ZF Control Partial Distance Partial Candidates Unit Sphere Constraint Detection Internal Memory
  • 13. Sphere Decoder Implementation work at the Univ. of Edinburgh
  • 14. Index
    • Introduction
    • Sphere decoder
    • MIMO prototyping platform
    • Real-time implementation
    • Results
    • Conclusions and future work
  • 15. MIMO Prototyping Platform Hardware
  • 16. MIMO Prototyping Platform Hardware MAX2827EVKit transceivers
    • Dual-band: 2.4GHz y 5GHz.
    • Up to 20 MHz IQ modulation .
    Hunt Heron HEPC9
    • 400 MBps HEART bus.
    • VirtexII -based 4 modules:
      • IO2v2, IO2v5, FPGA3 (6M gates)
    • 6 ADC and 6 DAC up to 125MSps.
    • PCI interface.
    • JTAG interfaces for debugging
  • 17. MIMO Prototyping Platform Tools Design and Simulation: Control and Hardware Cosimulation:
    • Mathworks Matlab / Simulink
    • Xilinx System Generator for DSP
    • C++ program for PCI-based communication with the real-time platform:
    • Transmission data
    • Control Signals
    • Hardware in the loop cosimulation through JTAG interfaces
    Synthesis and debugging:
    • Xilinx ISE Navigator
    • Modeltech ModelSim
    • Xilinx Chipscope
  • 18. Index
    • Introduction
    • Sphere decoder
    • MIMO prototyping platform
    • Real-time implementation
    • Results
    • Conclusions and future work
  • 19. Real-Time Implementation Assumptions A narrowband Rayleigh AWGN channel is required to validate the Matlab simulation-based results of the SD algorithm:
    • Real RF transmission at low rates and short bursts.
    • Real-time channel emulator for high rates (FPGA):
    • Pseudorandom coefficient and noise generation.
    • Channel matrix product and noise addition.
    The Sphere Decoder algorithm requires :
    • Channel matrix inverse o pseudoinverse.
    • Cholesky decomposition of the matrix.
  • 20. Real-Time Implementation Algorithms
    • Frame synchronization : double sliding window algorithm. [Heiskala02]
    • Sample-time synchronization : basic ML approach. [Naguib98]
    • Frequency offset estimation : reduced complexity implementation. [Simoens04]
    • Channel emulator : channels (random numbers) stored in large RAM blocks
    • MIMO detection – Sphere Decoder algorithm . Adaptation of [Barbero05].
  • 21. Real-Time Implementation Task partitioning 2x2 16-QAM MIMO System PCI-based communication with host software
  • 22. Real-Time Implementation Co-simulation Flexible system to allow step-by-step validation of algorithm implementation: any algorithm can be chosen to run in Matlab, in the FPGA (may not be real-time) or both. Main setups:
    • Ideal simulation : Perfect synchronization, channel estimation and inverse calculation.
    • Estimated parameters : Channel, real-time calculated inverse and Cholesky.
    • Complete system : All algorithms running in the FPGAs.
  • 23. Index
    • Introduction
    • Sphere decoder
    • MIMO prototyping platform
    • Real-time implementation
    • Results
    • Conclusions and future work
  • 24. Results Resources Algorithm Mults Slices %Slices Transmitter 0 1,320 5.3% Receiver 74 11,923 48.3% Sync. & Ch. Estimation 18 2,693 10.9% Inversion & Cholesky dec. 33 4,608 18.6% Sphere Decoder 23 3,370 13.7% Channel Emulator 20 1,771 7.2% Comms & Control signals 0 1,542 6.2% Total Used 96 16,556 67.0% Total Availaible 216 24,696
  • 25. Results Performance
  • 26. Results Throughput
  • 27. Index
    • Introduction
    • Sphere decoder
    • MIMO prototyping platform
    • Real-time implementation
    • Results
    • Conclusions and future work
  • 28. Conclusions and Future Work
    • A basic Sphere Decoder has been integrated into a complete real-time implementation of a MIMO system.
    • A platform has been set up that allows to evaluate the performance of the Sphere Decoder algorithm at different implementation steps.
    • Results comparing simulation and real-time implementation have been shown for a 2x2 16-QAM system.
    Future work:
    • Extension of the results to larger MIMO systems.
    • Evaluation of different Sphere Decoder algorithms and implementations.
    • Analysis of the performance of the sphere decoder in a realistic high-rate wireless transmission, e.g., with OFDM.
    Conclusions:
  • 29. Thank you!
  • 30. References [Barbero05] L. G. Barbero and J. S. Thompson, “Rapid prototyping of the sphere decoder for MIMO systems,” in Proc. IEE/EURASIP Conference on DSP Enabled Radio (DSPeR ’05) , vol. 1, Southampton, UK, Sept. 2005, pp. 41–47. [Burg05] A. Burg, M. Borgmann, M.Wenk, M. Zellweger, W. Fichtner, and H. Bölcskei, “VLSI implementation of MIMO detection using the sphere decoding algorithm,” IEEE J. Solid-State Circuits , vol. 40, no. 7, pp. 1566–1577, July 2005. [Damen03] M. O. Damen, H. E. Gamal, and G. Caire, “On maximumlikelihood detection and the search for the closest lattice point,” IEEE Trans. Inform. Theory , vol. 49, no. 10, pp. 2389–2402, Oct. 2003. [Heiskala02] J. Heiskala and J. Terry, OFDM Wireless LANs: A Theoretical and Practical Guide . Indiana, USA: Sams Publishing, 2002. [Naguib98] A. F. Naguib, V. Tarokh, N. Seshadri, and A. R. Calderbank, “A space-time coding modem for high-data-rate wireless communications,” IEEE J. Solid-State Circuits , vol. 16, no. 8, pp. 1459–1478, Oct. 1998. [Schnorr94] C. P. Schnorr and M. Euchner, “Lattice basis reduction: Improved practical algorithms and solving subset sum problems,” Mathematical Programming , vol. 66, pp. 181–199, 1994. [Simoens04] F. Simoens and M. Moeneclaey, “A reduced complexity frequency offset estimation technique for flat fading mimo channels,” in Proc. IEEE CAS Symposium on Emerging Technologies , vol. 2, Shanghai, China, June 2004, pp. 705–708. [Viterbo99] E. Viterbo and J. Boutros, “A universal lattice code decoder for fading channels,” IEEE Trans. Inform. Theory , vol. 45, no. 5, pp. 1639–1642, July 1999. [Wong02] K. Wong, C. Tsiu, R. S. Cheng, and W. Mow, “A VLSI architecture of a K-best lattice decoding algorithm for MIMO channels,” in Proc. IEEE International Symposium on Circuits and Systems (ISCAS ’02) , vol. 3, Scottsdale, AZ, May 2002, pp. 273–276.
  • 31. Real-Time Implementation Algorithms Implemented algorithms:
    • Frame synchronization : double sliding window algorithm. [Heiskala02]
    • Sample-time synchronization : basic ML approach. [Naguib98]
    • Frequency offset estimation : reduced complexity implementation. [Simoens04]
    • Channel estimation : training-based least-squares.
    • Inverse calculation and normalized Cholesky decomposition :
    • MIMO detection – Sphere Decoder algorithm . Adaptation of [Barbero05].
    • Channel emulator : channels (random numbers) stored in large RAM blocks
    • Direct implementation, no resource optimization.
  • 32. Extras
  • 33. Real-Time Implementation of a Sphere Decoder-Based MIMO Wireless System 14th EURASIP European Signal Processing Conference, EUSIPCO 4-8th September 2006, Florence, Italy L. G. Barbero, J. S. Thompson Institute for Digital Communications School of Engineering and Electronics University of Edinburgh M. Mendicute, G. Landaburu, J. Altuna, V. Atxa Communications and Digital Signal Processing Area Mondragon Goi Eskola Politeknikoa University of Mondragon
    • TexPoint fonts used in EMF: A A A A

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