Triangulation Algorithm for Multi-user Spatial Multiplexing in MIMO Downlink Channels

MIMO 다운링크 채널에서 다중사용자 공간다중화를 위한 알고리즘

  • 이흔철 (삼성전자 종합기술원) ;
  • ;
  • 이인규 (고려대학교 전기전자전파공학부 무선통신 연구실)
  • Published : 2010.01.31

Abstract

This paper studies the design of a multiuser multiple-input multiple-output (MIMO) system, where a base station (BS) transmits independent messages to multiple users. The remarkable "dirty paper coding (DPC)" result was first presented by Costa that the capacity does not change if the Gaussian interference is known at the transmitter noncausally. While several implementable DPC schemes have been proposed recently for single-user dirty-paper channels, DPC is still difficult to implement directly in practical multiuser MIMO channels. In this paper, we propose a network channel matrix triangulation (NMT) algorithm for utilizing interference known at the transmitter. The NMT algorithm decomposes a multiuser MIMO channel into a set of parallel, single-input single-output dirty-paper subchannels and then successively employs the DPC to each subchannel. This approach allows us to extend practical single-user DPC techniques to multiuser MIMO downlink cases. We present the sum rate analysis for the proposed scheme. Simulation results show that the proposed schemes approach the sum rate capacity of the multiuser MIMO downlink at moderate signal-to-noise ratio (SNR) values.

이 논문에서는 다중사용자 (multi-user) 다중안테나 (multiple-in multiple-out : MIMO) 시스템을 위한 전송기법을 제안한다. Costa가 증명한 더티페이퍼코딩 (dirty-paper coding: DPC)이론에 따르면 송신기가 수신기의 가우시안 분포를 갖는 간섭 신호를 알고 있는 경우 간섭 신호에 상관 없이 채널 캐패시티를 얻을 수 있음이 알려져 있다. 단독사용자 채널의 경우 간단하며 효율적인 DPC기법들이 알려져 있으나 다중사용자 환경에는 실제 구현하는데 있어 복잡도와 관련해 많은 문제를 가지고 있다. 이 논문에서 우리는 다중사용자 환경에서 송신기에 알려진 갑선신호를 효율적으로 제어할 수 있는 네트워크 채널 행렬 삼각화 (network channel matrix triangulation: NMT)기법을 제안하고자 한다. 제안하는 NMT 알고리즘은 다중사용자 MIMO 채널을 서로 독립된 병렬의 Single-input Single-output (SISO) 채널들로 변환하여 단독사용자 환경을 위해 제안되어 있는 기존 DPC기법들을 다중사용자 환경에서도 사용 가능케 한다. 시뮬레이션 결과를 통해 제안된 알고리즘이 다중사용자 환경의 채널 캐패시티에 거의 접근함을 보일 것이다.

Keywords

References

  1. G. Caire and S. Shamai, "On the Achievable Throughput of a Multiantenna Gaussian Broadcast Channel," IEEE Transactions on Information Theory, Vol.49, pp.1691-1706, July 2003. https://doi.org/10.1109/TIT.2003.813523
  2. S. Vishwanath, N. Jindal, and A. Goldsmith, "Duality, Achievable Rates, and Sum-Rate Capacity of Gaussian MIMO Broadcast Channels," IEEE Transactions on Information Theory, Vol.49, pp.2658-2668, October 2003. https://doi.org/10.1109/TIT.2003.817421
  3. W. Yu and J. M. Cioffi, "Sum Capacity of Gaussian Vector Broadcast Channels," IEEE Transactions on Information Theory, Vol.50, pp.1875-1892, September 2004. https://doi.org/10.1109/TIT.2004.833336
  4. P. Viswanath and D. N. C. Tse, "Sum Capacity of the Vector Gaussian Broadcast Channel and Uplink-Downlink Duality," IEEE Transactions on Information Theory, Vol.49, pp.1912-1921, August 2003. https://doi.org/10.1109/TIT.2003.814483
  5. H. Weingarten, Y. Steinberg, and S. Shamai, "The Capacity Region of the Gaussian Multiple-Input Multiple-Output Broadcast Channel," IEEE Transactions on Information Theory, Vol.52, pp.3936-3964, September 2006.
  6. M. Costa, "Writing on dirty paper," IEEE Transactions on Information Theory, Vol. IT-29, pp.439-441, May 1983.
  7. C. B. Peel, B. Hochwald, and A. L. Swindlehurst, "A Vector- Perturbation Technique for Near-Capacity Multiantenna Multiuser Communication-Part I: Channel Inversion and Regularization," IEEE Transactions on Communications, Vol.53, pp.195-202, January 2005. https://doi.org/10.1109/TCOMM.2004.840638
  8. Q. H. Spencer, A. L. Swindlehurst, and M. Haardt, "Zero-Forcing methods for Downlink Spatial Multiplexing in Multiuser MIMO Channels," IEEE Transactions on Signal Processing, Vol.52, pp.461-471, February 2004. https://doi.org/10.1109/TSP.2003.821107
  9. M. Tomlinson, "New Automatic Equalizer Employing Modulo Arithmetic," Electoronics Letters, Vol.7, pp.138-139, March 1971. https://doi.org/10.1049/el:19710089
  10. H. Miyakawa and H. Harashima, "A Method of code conversion for a digital communication channel with intersymbol interference," Transactions of Institute of Electronic Communication Eng. Japan, pp.272-273, June 1969.
  11. U. Erez, S. Shamai, and R. Zamir, "Capacity and lattice strategies for canceling known interference," IEEE Transactions on Information Theory, Vol.51, pp.3820-3833, November 2005. https://doi.org/10.1109/TIT.2005.856935
  12. R. Zamir, S. Shamai, and U. Erez, "Nested Linear/Lattice Codes for Structured Multiterminal Binning," IEEE Transactions on Information Theory, Vol.48, pp.1250-1276, June 2002. https://doi.org/10.1109/TIT.2002.1003821
  13. U. Erez and S. ten Brink, "A Closeto- Capacity Dirty Paper Coding Scheme," IEEE Transactions on Information Theory, Vol.51, pp.3417-3423, November 2005. https://doi.org/10.1109/TIT.2005.855586
  14. N. Jindal and A. Goldsmith, "Dirty Paper Coding vs. TDMA for MIMO Broadcast Channels," in Proc. IEEE ICC '04, Vol.2, pp.20-24, June 2004.
  15. C. G. Khatri, "Distribution of the largest or the smallest characteristic root under null hyperthesis concerning complex multivariate normal populations," The Annals of Mathematical Statistics, Vol.35, pp.1807-1810, December 1964. https://doi.org/10.1214/aoms/1177700403
  16. N. Jindal, W. Rhee, S. Vishwanath, S. Jafar, and A. J. Goldsmith, "Sum Power Iterative Water-filling for Multi-antenna Gaussian Broadcast Channels," IEEE Transactions on Information Theory, Vol.51, pp.1570-1580, April 2005. https://doi.org/10.1109/TIT.2005.844082