Journal of the Institute of Electronics and Information Engineers (전자공학회논문지)

The Institute of Electronics and Information Engineers (대한전자공학회)
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Dijkstra's Search-Based Sphere Decoding with Complexity Constraint

제한된 연산량을 갖는 Dijkstra 탐색 기반의 스피어 디코딩

  • Yoon, Hye-yeon (Department of Electronics and Information Engineering, Korea Aerospace University) ;
  • Kim, Tae-Hwan (Department of Electronics and Information Engineering, Korea Aerospace University)
  • 윤혜연 (한국항공대학교 항공전자정보공학과) ;
  • 김태환 (한국항공대학교 항공전자정보공학과)
  • Received : 2017.02.28
  • Accepted : 2017.06.09
  • Published : 2017.07.25
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Abstract

This paper presents a Dijkstra's-search-based sphere decoding (SD) algorithm with limited complexity for the symbol detection in MIMO communication systems. The Dijkstra search-based SD is efficient to achieve a near-optimal error rate in the MIMO symbol detection, but has a critical problem in that its complexity is variable and can correspond to that of the exhaustive search in the worst case. The proposed algorithm limits the computations while achieving a near-optimal error rate. Simulation results show that the error rate is near optimal even with the limited complexity.

본 논문은 MIMO 통신 시스템을 위한 Dijkstra 탐색 기반의 제한된 연산량을 갖는 스피어 디코딩 (sphere decoding; SD) 알고리즘을 제안하고 이에 대한 성능을 평가한다. Dijkstra 탐색 기반의 SD는 MIMO 심볼 검파 과정에서 저 복잡도로 준 최적의 에러율 성능을 달성하는 효율적인 tree 탐색 알고리즘이다. 하지만 Dijkstra 탐색 기반의 SD는 채널 환경에 따라 연산량이 가변적이고, 최악의 경우 전역 탐색의 경우에 해당하는 높은 연산량을 갖는 심각한 문제가 있다. 본 논문에서는 이러한 문제를 해결하기 위해서 연산량을 제한시킨 새로운 Dijkstra 탐색 기반의 SD 알고리즘을 제시한다. 제안된 알고리즘은 연산량이 제한되었음에도 여전히 준 최적의 에러율 성능을 달성함을 모의 실험을 통해 검증하였다.

Keywords

References

  1. B. M. Hochwald and S. Ten Brink, "Achieving near-capacity on a multiple-antenna channel," IEEE Trans. Commun., vol. 51, no. 3, pp. 389-399, Mar. 2003. https://doi.org/10.1109/TCOMM.2003.809789
  2. E. G. Larsson, "MIMO detection methods: How they work [lecture notes]," IEEE Signal Process. Mag., vol. 26, no. 3, pp. 91-95, May 2009. https://doi.org/10.1109/MSP.2009.932126
  3. S. Yang and L. Hanzo, "Fifty years of MIMO detection: The road to large-scale MIMOs," IEEE Commun. Surveys & Tutorials, vol. 17, no. 4, pp. 1941-1988, Sep. 2015. https://doi.org/10.1109/COMST.2015.2475242
  4. M. C. Shin, Y. S. Song, D. S. Kwon, J. T. Seo, C. Y. Lee, "Performance analysis of maximum likelihood detection for the spatial multiplexing system with multiple antennas," Journal of The Institute of Electronics and Information Engineers, vol 42, no 12, pp 103-110, Dec. 2005.
  5. 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. https://doi.org/10.1007/BF01581144
  6. X. Chen, G. He, and J. Ma, "VLSI implementation of a high-throughput iterative fixed-complexity sphere decoder," IEEE Trans. Circuits Syst. II, vol. 60, no. 5, pp. 272-276, May 2013. https://doi.org/10.1109/TCSII.2013.2251954
  7. D. Seethaler and H. Bolcskei, "Infinity-norm sphere-decoding," in Proc. Int. Symp. Inf. Theory, Jul. 2008, pp. 2002-2006.
  8. L. G. Barbero and J. S. Thompson, "Fixing the complexity of the sphere decoder for MIMO detection,"IEEE Trans. Wireless Commun., vol. 7, pp. 2131-2142, June 2008. https://doi.org/10.1109/TWC.2008.060378
  9. M.Wenk, M. Zellweger, A. Burg, N. Felber, and W. Fichtner, "K-best MIMO detection VLSI architectures achieving up to 424 Mbps," in Proc. Int. Symp. Circuits Syst., May 2006, pp. 1151-1154.
  10. T.-H. Kim and I.-C. Park, "Small-area and low-energy K-best MIMO detector using relaxed tree expansion and early forwarding," IEEE Trans. Circuits Syst. I, vol. 57, no. 10, pp. 2753-2761, Oct. 2010. https://doi.org/10.1109/TCSI.2010.2046249
  11. J. W. Kim, J. W. Kang, C. Y. Lee, "An Adaptive K-best detection algorithm for MIMO systems," Journal of The Institute of Electronics and Information Engineers, vol 43, no 10, pp 1-7, Oct. 2006.
  12. T. Fukatani, R. Matsumoto, and T. Uyematsu, "Two methods for decreasing the computational complexity of the MIMO ML decoder," IEICE Trans. Fundamentals, vol. E87-A, no. 10, pp. 2571-2576, Oct.2004.
  13. M. Myllyla, M. Juntti, and J. R. Cavallaro, "A list sphere detector based on Dijkstra's algorithm for MIMO-OFDM systems," in Proc. Personal, Indoor Mobile Radio Commun., Sep. 2007, pp. 1-5.
  14. T.-H. Kim and I.-C. Park, "High-throughput and area-efficient MIMO symbol detection based on modified Dijkstra's search," IEEE Trans. Circuits Syst. I, vol. 57, no. 7, pp. 1756-1766, July 2010. https://doi.org/10.1109/TCSI.2009.2034235
  15. A. Burg, M. Wenk, and W. Fichtner, "VLSI implementation of pipelined sphere decoding with early termination," presented at the EUSIPCO, Florence, Italy, Sep. 2006.
  16. A. Burg, M. Borgmann, M. Wenk, C. Studer, and H. BOlcskei, "Advanced receiver algorithms for MIMO wireless communications," in Proc. Conf. Design, Automation and Test in Europe. European Design and Automation Association, 2006, pp. 593-598.
  17. T.-H. Kim and J.-H. Kim "Partitioned scheduling for sphere decoding with runtime constraints for practical MIMO communication systems," in Proc. Personal, Indoor Mobile Radio Commun., Aug. 2015, pp. 721-725.
  18. G. D. Golden, G. J. Foschini, R. A. Valenzuela, and P. W. Wolniansky, "Detection algorithm and initial laboratory results using V-BLAST space-time communications architecture," IEE Electron. Lett., vol. 35, pp. 14-16, Jan. 1999. https://doi.org/10.1049/el:19990058
  19. T. Handte, A. Muller, and J. Speidel, "BER analysis and optimization of generalized spatial modulation in correlated fading channels," in Proc. Veh. Tech. Conf. IEEE, Sep. 2009, pp. 1-5.