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Area-Efficient Antenna-Scalable MIMO Detector for K-best Sphere Decoding

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Abstract

K-best sphere decoding is one of the most popular MIMO (Multi-Input Multi-Output) detection algorithms because of its low complexity and close to Maximum Likelihood (ML) Bit Error Rate (BER) performance. Unfortunately, conventional multi-stage sphere decoders suffer from the inability to adapt to varying antenna configurations, requiring implementation redesign for each specific array structure. In this paper, we propose a reconfigurable in-place architecture that is scalable to an arbitrary number of antennas at run-time, while reducing area significantly compared with other sphere decoders. To improve the throughput of the in-place architecture without any degradation in BER performance, we propose partial-sort-bypass and symbol interleaving techniques, and also exploit multi-core design. Implementation results for a 16-QAM MIMO decoder in a 130 nm CMOS technology show a 41% reduction in area compared to the smallest sphere decoder while maintaining antenna reconfigurability, and better throughput. When implemented for the 802.11n standard, our architecture results in 42% reduction in area compared to the multi-stage architecture.

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References

  1. Sun, Y., Cavallaro, J. R. (2009). High Throughput VLSI Architecture for Soft-Output MIMO Detection Based on a Greedy Graph Algorithm. ACM GLSVLSI'09, Boston, Massachusetts, USA.

  2. Wu, D., Eilert, J., Asghar, R., & Liu, D. (2010) VLSI Implementation of a Fixed-Complexity Soft-Output MIMO Detector for High-Speed Wireless. EURASIP Journal on Wireless Communications and Networking, vol. 2010.

  3. Studer Test, C., et al. (2008). Soft-output sphere decoding: algorithms and VLSI implementation. IEEE Journal on Selected Areas in Communications, 26(2), 290–300.

    Article  Google Scholar 

  4. Guo, Z., & Nilsson, P. (2006). Algorithm and implementation of the K-best sphere decoding for MIMO detection. IEEE Journal on Selected Areas in Communications, 24(3), 491–503.

    Article  Google Scholar 

  5. Barbero, L., & Thompson, J. (2006). A fixed-complexity MIMO detector based on the complex sphere decoder. Cannes: IEEE Workshop on Signal Processing Advances for Wireless Communications.

    Google Scholar 

  6. Jenkal, R. S., & Davis, W. R. (2007). An architecture for energy efficient sphere decoding. In Proc. of ISLPED’07, pp. 244–249, Portland.

  7. Barbero, L. G., Ratnarajah, T., & Cowan, C. (2008). A low-complexity soft mimo detector based on the fixed-complexity sphere decoder. in IEEE International Conference on acoustics, speech and signal processing (ICASSP ’08), Las Vegas.

  8. Burg, A., et al. (2005). VLSI implementation of MIMO detection using the sphere decoding algorithm. IEEE Journal of Solid-State Circuits, 40, 1566–1577.

    Article  Google Scholar 

  9. Hess, C., Wenk, M., Burg, A., Luethi, P., Studer, C., Felber, N., & Fichtner, W. (2007). Reduced-complexity MIMO detector with close-to ML error rate performance. ACM GLSVLSI'07, Italy. pp. 200–203.

  10. Amiri, K., Dick, C., Rao, R., & Cavallaro J. R. (2008) Novel Sort-free Detector with Modified Real-valued Decomposition (M-RVD) Ordering in MIMO Systems. IEEE GLOBECOM Conference, New Orleans, LA.

  11. Wenk, M., et al. (2006). K-Best MIMO Detection VLSI architectures achieving up to 424 Mbps. In proc. IEEE ISCAS, 3, 1151–1154.

    Google Scholar 

  12. Chen, S., Zhang, T., & Xin, Y. (2007). Relaxed K-best MIMO signal detector design and VLSI implementation. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 15(3), 328–337.

    Article  Google Scholar 

  13. Mondal, S., Eltawil, A. M, & Salama, K. N. (2009). Architectural Optimizations for Low-Power K-Best MIMO Decoders. Accepted to IEEE Transactions on Vehicular Technologies

  14. Moezzi-Madani, N., & Davis, W. R. (2009). High-throughput low-complexity MIMO detector based on K-best algorithm,” GLSVLSI’09, pp. 451–456, Boston

  15. Kim, H., Lee, D., & Villasenor, J. D. (2008). Design tradeoffs and hardware architecture for real-time iterative MIMO detection using sphere decoding and LDPC coding. IEEE Journal on Selected Areas in Communications, 26(6), 1003–1014.

    Article  Google Scholar 

  16. Moezzi-Madani, N., & Davis, W. R. (2009). Parallel merge algorithm for high-throughput signal processing applications. Electronics Letters, 45(3), 188–189.

    Article  Google Scholar 

  17. Yang, C., & Markovic, D. (2008). A Multi-Core Sphere Decoder VLSI Architecture for MIMO Communications. IEEE GLOBECOM’08, pp. 3297–3301

  18. Radosavljevic, P., Guo, Y., & Cavallaro, J. R. (2009). Probabilistically bounded soft sphere detection for MIMO-OFDM receivers: algorithm and system architecture. IEEE Journal on Selected Areas in Communications, 27(8), 1318–1330.

    Article  Google Scholar 

  19. Wu, D., & Eilert, J, & Liu, D. (2009). Implementation of a high-speed MIMO soft-output symbol detector for software defined radio. Journal of Signal Processing Systems, Springer.

  20. Moezzi-Madani, N., Thorolfsson, T., & Davis, W. R. (2010). A low-area flexible MIMO detector for WiMAX/WiFi standards. Proceedings of Design, Automation and Test in Europe (DATE’10), pp. 1637–1640

  21. Amiri, K., Dick, C., Rao, R., & Cavallaro, J. R. (2009). A High Throughput Configurable SDR Detector for Multi-user MIMO Wireless Systems. Journal of Signal Processing Systems, Springer.

  22. Wubben, D., Bohnke, R., Kuhn, V., & Kammeyer, K. D. (2003). MMSE Extension of V-BLAST based on Sorted QR Decomposition. in IEEE Proc. VTCl, Orlando.

  23. Batcher, K. E. (1968). Sorting networks and their applications. AFIPS Proceedings on Spring Joint Computer Conference, pp. 304–314.

  24. Davis, W. R., Eun Chu, Oh, Sule, A., & Franzon, P. D. (2009). Application exploration for 3D integrated circuits: TCAM, FIFO, and FFT case studies. IEEE Transactions on VLSI Systems, 17(4), 496–506.

    Article  Google Scholar 

  25. Zyren, J., & McCoy, W. (2007). Overview of the 3GPP Long Term Evolution Physical Layer, Online available.

  26. Airmagnet, ‘802.11n Primer’, whitepaper, http://www.airmagnet.com/assets/whitepaper/WP-802.11nPrimer.pdf

  27. http://wireless.agilent.com/wireless/helpfiles/n7617b/payload_structure.htm

  28. Luethi, P., Burg, A., Haene, S., Perels, D., Felber, N., & Fichtner, W. (2007). VLSI implementation of a high-speed iterative sorted MMSE QR decomposition. in ISCAS, New Orleans, pp. 1421–1424

  29. Fasthuber, R., Li, M., Novo, D., Raghavan, P., & Perre, L. V., et al. (2010). Exploration of Soft-Output MIMO Detector Implementations on Massive Parallel Processors. Journal of Signal Processing Systems, Springer.

  30. Shamshiri, S., Lisherness, P., Pan, S.-J., & Tim Cheng K.-T. (2008). A cost analysis framework for multi-core systems with spares. IEEE International Test Conference (ITC), pp. 1–8.

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Authors and Affiliations

  1. North Carolina State University, Raleigh, NC, 27606, USA

    Nariman Moezzi-Madani, Thorlindur Thorolfsson & William Rhett Davis

  2. Oregon State University, Corvallis, OR, 97330, USA

    Patrick Chiang

Authors
  1. Nariman Moezzi-Madani
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  2. Thorlindur Thorolfsson
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  3. Patrick Chiang
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  4. William Rhett Davis
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Correspondence to Nariman Moezzi-Madani.

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Moezzi-Madani, N., Thorolfsson, T., Chiang, P. et al. Area-Efficient Antenna-Scalable MIMO Detector for K-best Sphere Decoding. J Sign Process Syst 68, 171–182 (2012). https://doi.org/10.1007/s11265-011-0595-9

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  • DOI: https://doi.org/10.1007/s11265-011-0595-9

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