DOI QR코드

DOI QR Code

Low-Complexity MIMO Detection Algorithm with Adaptive Interference Mitigation in DL MU-MIMO Systems with Quantization Error

  • Park, Jangyong (Department of Electrical and Electronic Engineering, Yonsei University) ;
  • Kim, Minjoon (Department of Electrical and Electronic Engineering, Yonsei University) ;
  • Kim, Hyunsub (Department of Electrical and Electronic Engineering, Yonsei University) ;
  • Jung, Yunho (School of Electronics, Telecommunication and Computer Engineering, Korea Aerospace University) ;
  • Kim, Jaeseok (Department of Electrical and Electronic Engineering, Yonsei University)
  • 투고 : 2014.07.07
  • 심사 : 2015.04.20
  • 발행 : 2016.04.30

초록

In this paper, we propose a low complexity multiple-input multiple-output (MIMO) detection algorithm with adaptive interference mitigation in downlink multiuser MIMO (DL MU-MIMO) systems with quantization error of the channel state information (CSI) feedback. In DL MU-MIMO systems using the imperfect precoding matrix caused by quantization error of the CSI feedback, the station receives the desired signal as well as the residual interference signal. Therefore, a complexMIMO detection algorithm with interference mitigation is required for mitigating the residual interference. To reduce the computational complexity, we propose a MIMO detection algorithm with adaptive interference mitigation. The proposed algorithm adaptively mitigates the residual interference by using the maximum likelihood detection (MLD) error criterion (MEC). We derive a theoretical MEC by using the MLD error condition and a practical MEC by approximating the theoretical MEC. In conclusion, the proposed algorithm adaptively performs interference mitigation when satisfying the practical MEC. Simulation results show that the proposed algorithm reduces the computational complexity and has the same performance, compared to the generalized sphere decoder, which always performs interference mitigation.

키워드

과제정보

연구 과제 주관 기관 : KEIT

참고문헌

  1. Evolved Universal Terrestrial Radio Access (E-UTRA); Physical Channels and Modulation, 3GPP TS 36.211 v10.3.0, Sept. 2011.
  2. Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications: Enhancements for Very High Throughput for Operation in Bands below 6GHz, IEEE P802.11ac/D2.0 Std., Jan. 2012.
  3. M. Costa, "Writing on dirty paper," IEEE Trans. Inf. Theory, vol. 29, no. 3, pp. 439-441, May 1983. https://doi.org/10.1109/TIT.1983.1056659
  4. G. Caire and S. Shamai, "On the achievable throughput of a multiantenna Gaussian broadcast channel," IEEE Trans. Inf. Theory, vol. 49, no. 7, pp. 1691-1706, July 2003. https://doi.org/10.1109/TIT.2003.813523
  5. P. Viswanath and D. N. C. Tse, "Sum capacity of the vector Gaussian broadcast channel and uplink downlink duality," IEEE Trans. Inf. Theory, vol. 49, no. 8, pp. 1912-1921, Aug. 2003. https://doi.org/10.1109/TIT.2003.814483
  6. Q. H. Spencer, A. L. Swindlehurst, and M. Haardt, "Zero-forcing methods for downlink spatial multiplexing in multiuser MIMO channels," IEEE Trans. Signal Process., vol. 52, no.2, pp. 461-471, Feb. 2004. https://doi.org/10.1109/TSP.2003.821107
  7. C. B. Peel, B. M. Hochwald, and A. L. Swindlehurst, "A vector perturbation technique for near-capacity multiantenna multiuser communication - Part I: Channel inversion and regularization," IEEE Trans. Commun., vol. 53, no. 1, pp. 195-202, Jan. 2005. https://doi.org/10.1109/TCOMM.2004.840638
  8. B. M. Hochwald, C. B. Peel, and A. L. Swindlehurst, "A vector perturbation technique for near-capacity multiantenna multiuser communication - Part II: perturbation," IEEE Trans. Commun., vol. 53, no. 3, pp. 537-544, Mar. 2005. https://doi.org/10.1109/TCOMM.2004.841997
  9. J. Z. Zhang and K. Kim, "Near-capacity MIMO multiuser precoding with QRD-M Algorithm," in Proc. IEEE ACSSC, Nov. 2005, pp.1498-1502.
  10. M. Mohaisen and K. Chang, "Fixed-complexity sphere encoder for multiuser MIMO systems," J. Commun. Netw., vol. 13, no. 1, pp. 63-69, Feb. 2011. https://doi.org/10.1109/JCN.2011.6157253
  11. E. Viterbo and J. Boutros, "A universal lattice code decoder for fading channels," IEEE Trans. Inf. Theory, vol. 45, no. 5, pp. 1639-1642, July 1999. https://doi.org/10.1109/18.771234
  12. E. Agrell, T. Eriksson, A. Vardy, and K. Zeger, "Closest point search in lattices," IEEE Trans. Inf. Theory, vol. 48, no. 8, pp. 2201-2214, Aug. 2002. https://doi.org/10.1109/TIT.2002.800499
  13. M.O. Damen, H.E. Gamel, and G. Caire, "On maximum-likelihood detection and the search for the closest lattice point," IEEE Trans. Inf. Theory, vol. 49, no. 10, pp. 2389-2402, Oct. 2003. https://doi.org/10.1109/TIT.2003.817444
  14. L. G. Barbero and J. S. Thompson, "Fixing the complexity of the sphere decoder for MIMO detection," IEEE Trans. Wireless Commun., vol. 7, no. 6, pp. 2131-2142, June 2008 https://doi.org/10.1109/TWC.2008.060378
  15. K. W. Wong, C.Y. Tsui, R. S. K. Cheng, and W. H. Mow, "A VLSI architecture of a K-best lattice decoding algorithm for MIMO channels," in Proc. IEEE ISCAS, May 2002, pp.273-276.
  16. J. Lee, D. Toumpakaris, and W. Yu, "Interference mitigation via joint detection," IEEE J. Sel. Areas Commun., vol. 29, no. 6, June 2011.
  17. M. O. Damen, K. Abed-Meraim, and J.-C. Belfiore, "Generalised sphere decoder for asymmetrical space-time communication architecture," Electronics Lett., vol. 36, no. 2, pp. 166-167, Jan. 2000. https://doi.org/10.1049/el:20000168
  18. T. Cui and C. Tellambura, "An efficient generalized sphere decoder for rank-deficient MIMO systems," IEEE Commun. Lett., vol. 9, no. 5, pp. 423-425, May 2005. https://doi.org/10.1109/LCOMM.2005.1431159
  19. J. Akhtman and L. Hanzo, "An optimized-hierarchy-aided maximum likelihood detector forMIMO-OFDM," in Proc. IEEE VTC Spring, May 2005, pp. 1526-1530.
  20. P. Wang and T. Le-Ngoc, "A low-complexity generalized sphere decoding approach for underdetermined linear communication systems: Performance and complexity evaluation," in IEEE Trans. Commun., vol. 57, no. 11, pp. 3376-3388, Nov. 2009. https://doi.org/10.1109/TCOMM.2009.11.060557
  21. B. K. Ng, and E. S. Sousa, "On bandwidth-efficient multiuser-space-time signal design and detection," IEEE J. Sel. Areas Commun., vol. 20, no. 2, pp. 320-329, Feb. 2002. https://doi.org/10.1109/49.983348
  22. B.W. Zarikoff, J. K. Cavers, and S. Bavarian, "An iterative groupwise multiuser detector for overloaded MIMO applications," IEEE Trans. Wireless Commun., vol. 6, no.2, pp. 443-447, Feb. 2007. https://doi.org/10.1109/TWC.2007.05317
  23. S. L. Marple, Digital Spectral Analysis: With Applications, Englewood Cliffs, NJ: Prentice Hall, 1987.
  24. X. Zhang and J. Lee, "Low complexity MIMO scheduling with channel decomposition using capacity upperbound," IEEE Trans. Commun., vol. 56, no. 6, pp. 871-876, June 2008. https://doi.org/10.1109/TCOMM.2008.060384
  25. J. W. Demmel, Applied Numerical Linear Algebra, Philadelphia, PA: Society for Industrial and Applied Mathematics, 1997.
  26. G. H. Golub and C. F. Van Loan, Matrix Computations, 3rd ed. Baltimore, MD: The John Hopkins Univ. Press, 1996.
  27. J. Park, B. Lee, and B. Shim, "A MMSE vector precoding with block diagonalization for multiuser MIMO downlink," IEEE Trans. Commun., vol. 60, no. 2, pp. 569-577, Feb. 2012. https://doi.org/10.1109/TCOMM.2011.122111.100681
  28. E. K. P. Chong and S. H. Zak, An Introduction to Optimization, 3rd ed., New York: Wiley, 2007.