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Efficiency Improvement of the Fixed-complexity Sphere Decoder

  • Received : 2010.11.25
  • Accepted : 2011.02.05
  • Published : 2011.02.28

Abstract

In this paper, we propose two schemes to reduce the complexity of fixed-complexity sphere decoder (FSD) algorithm in the ordering and tree-search stages, respectively, while achieving quasi-ML performance. In the ordering stage, we propose a QR-decomposition-based FSD signal ordering based on the zero-forcing criterion (FSD-ZF-SQRD) that requires only a few number of additional complex flops compared to the unsorted QRD. Also, the proposed ordering algorithm is extended using the minimum mean square error (MMSE) criterion to achieve better performance. In the tree-search stage, we introduce a threshold-based complexity reduction approach for the FSD depending on the reliability of the signal with the largest noise amplification. Numerical results show that in $8{\times}8$ MIMO system, the proposed FSD-ZF-SQRD and FSD-MMSE-SQRD only require 19.5% and 26.3% of the computational efforts required by Hassibi’s scheme, respectively. Moreover, a third threshold vector is outlined which can be used for high order modulation schemes. In $4{\times}4$ MIMO system using 16-QAM and 64-QAM, simulation results show that when the proposed threshold-based approach is employed, FSD requires only 62.86% and 53.67% of its full complexity, respectively.

Keywords

References

  1. E. Telatar, "Capacity of multi-antenna Gaussian channels," European Transactions on Telecommunications, vol. 10, pp. 585-595, Dec. 1999. https://doi.org/10.1002/ett.4460100604
  2. W. Van Etten, "Maximum likelihood receiver for multiple channel transmission systems," IEEE Transactions on Communications, pp. 276-283, Feb. 1976.
  3. Q. H. Spencer et al., "An introduction to the multi-user MIMO downlink," IEEE Communications Magazine, vol. 42, no. 10, pp. 60-67, Oct. 2004.
  4. D. Shiu and J. Kahn "Layered space-time codes for wireless communications using multiple transmit antennas," in Proc. the International Conference on Communications, Vancouver, Canada, pp. 436-440, Jun.1999.
  5. D. Wubben et al., "Efficient algorithm for decoding layered space-time codes," Electronics Letters, vol. 37, no. 22, pp. 1348-1350, Oct. 2001. https://doi.org/10.1049/el:20010899
  6. D. Wubben et al., "MMSE extension of V-BLAST based on sorted QR decomposition," in Proc. IEEE Vehicular Technology Conference, Lake Buena Vista, USA, pp. 508-512, Oct. 2003.
  7. E. Agrell et al., "Closest point search in lattices," IEEE Transactions on Information Theory, vol. 48, no. 8, pp. 2201-2214, Nov. 2002. https://doi.org/10.1109/TIT.2002.800499
  8. B. Hassibi and H. Vikalo, "On the expected complexity of sphere decoding," in Proc. Asilomar Conference on Signals, Systems and Computers, Pacific Grove, USA, pp. 1051-1055, Nov. 2001.
  9. J. Jalden and B. Ottersten, "On the complexity of sphere decoding in digital communications," IEEE Transactions on Signal Processing, vol. 53, no. 4, pp. 1474-1484, Apr. 2005. https://doi.org/10.1109/TSP.2005.843746
  10. L. Barbero and J. Thompson, "Fixing the complexity of the sphere decoder for MIMO detection," IEEE Trans. on Wireless Communications, vol. 7, no. 6, pp. 2131-2142, Jun. 2008. https://doi.org/10.1109/TWC.2008.060378
  11. L. Barbero and J. Thompson, "Extending a fixed-complexity sphere decoder to obtain likelihood information for turbo-MIMO systems," IEEE Trans. on Vehicular Technology, vol. 57, no. 5, pp. 2804-2814, Sep. 2008. https://doi.org/10.1109/TVT.2007.914064
  12. J. Jalden et al., "Full diversity detection in MIMO systems with a fixed-complexity sphere decoder," in Proc. of IEEE International Conference on Acoustics, Speech, and Signal Processing, Honolulu, USA, pp. 49-52, Apr. 2007.
  13. J. Jalden et al., "The error probability of the fixed-complexity sphere decoder," IEEE Trans. On Signal Processing, vol. 57, no. 7, pp. 2711-2720, Jul. 2009. https://doi.org/10.1109/TSP.2009.2017574
  14. P. Wolniansky et al., "V-BLAST: An architecture for realizing very high data rates over the rich-scattering wireless channel," in Proc. URSI International Symposium on Signals, Systems, and Electronics, Pisa, Italy, pp. 295-300, Oct. 1998. Article
  15. B. Hassibi, "An efficient square-root algorithm for BLAST," in Proc. IEEE International Conf. Acoustics, Speech, Signal Processing, Istanbul, Turkey, pp. 737-740, Jun. 2000.
  16. M. Mohaisen and K.H. Chang, "On improving the efficiency of the fixed-complexity sphere decoder," in Proc. IEEE VTC - Fall, Sep. 2009, Session 3B-1.
  17. C. Schnorr and M. Euchner, "Lattice basis reduction: Improved practical algorithms and solving subset sum problems," Mathematical Programming, vol. 66, pp. 181-199, Sep. 1994. https://doi.org/10.1007/BF01581144
  18. H. Zhu, Z. Lei and F. P. S. Chin, "An improved square-root algorithm for BLAST," IEEE Signal Processing Letters, vol. 11, no. 9, pp. 772-775, Sep. 2004. https://doi.org/10.1109/LSP.2004.833483
  19. K. J. Kim et al., "AQRD-M/Kalman filter based detection and channel estimation algorithm for MIMO-OFDM systems," IEEE Transactions on Wireless Communications, vol. 4, no. 2, pp. 710-721, Mar. 2005. https://doi.org/10.1109/TWC.2004.842951