分布式MIMO的Turbo检测算法

沈莹; 唐友喜; 孔婷

分布式MIMO的Turbo检测算法

计量
- 文章访问数: 2145
- HTML全文浏览量: 71
- PDF下载量: 817
- 被引次数: 0
出版历程
- 收稿日期: 2005-03-28
- 修回日期: 2005-12-12
- 刊出日期: 2006-12-19

Turbo Detection Scheme for Distributed MIMO

摘要

摘要: 当信道码为卷积码时，针对V-BLAST类空时码的分布式MIMO，该文提出了两种迭代检测算法：最大似然迭代接收机及一种低复杂度的迭代检测接收机。最大似然迭代检测接收机的复杂度为O(2MTSlogM)，低复杂度的迭代检测接收机的复杂度为 O(M2TM2RS2M) 。在准静态、单径瑞利衰落信道中，对低复杂度的迭代检测接收机的误码率性能进行了计算机仿真验证，与非迭代的迫零检测相比，低复杂度的迭代检测接收机节约比特信噪比约7.5dB；在相同的误码率下，迭代6次与迭代1次相比，可节约3dB的比特信噪比；随着迭代次数的增加，迭代效果越来越小。
- 分布式多输入多输出; Turbo(迭代)检测; 软输入软输出; 并行软干扰抵消; 瞬时最小均方误差滤波; 信道传播时延
Abstract: In this paper, a iterative receiver is introduced for convolutionally coded distributed MIMO with V-BLAST architecture. A maximum-likelihood (ML) iterative detector and a low-complexity Turbo detection scheme are proposed. The computational complexity is O(2MTSlogM) and O(M2TM2RS2M) respectively. Simulation results in quasi-stationary, single-path Rayleigh fading channel demonstrate that the proposed low-complexity iterative detection algorithm offers significant performance improvement about 7.5dB at than the non-iterative zero-forcing detection. At same BER (Bit Error Rate), 1 iterations Eb/N0 is 3dB above 6 iterations. Performance improvement gradually declines as the number of iteration increases.

HTML全文

参考文献(1)

Foschini G J, Gans M J. On the limits of wireless communications in a fading environment when using multiple antennas[J].Wireless Personal Communication.1998, 6(3):311-335[2]Telatar I E. Capacity of multi-antenna Gausian channel[J].Eur. Trans. Telecommun.1999, 10(6):585-595[3]Zhou Shidong, Zhao Ming, Xu Xibin, et al.. Distributed wireless communication system: A new architecture for future public wireless access. IEEE Communications Magazine, 2003, 41(3): 108-113.[4]Xia H, Herrera A B, Kim S, et al.. A CDMA-distributed antennasystem for in-building personal communications services[J].IEEE Journal on Selected Areas in Communications.1996, 14(4):644-650[5]Berrou C, Glavieux A. Near optimum error-correcting coding and decoding: Turbo codes[J].IEEE Trans. on Communications.1996, 44(10):1261-1271[6]Ariyavisitakul S L. Turbo space-time processing to improve wireless channel capacity[J].IEEE Trans. on Communications.2000, 48(8):1347-1359[7]Hochwald B M, Brink S T. Achieving near-capacity on a multiple-antennas channel. IEEE Trans. on Communica- tions, 2003, 51(3): 398-299.[8]Boutros J J, Boixadera F, Lamy C. Bit-interleaved coded modulations for multiple-input multiple-output channels. 2000 IEEE Sixth International Symposium on Spread Spectrum Techniques and Applications, Parsippany, NJ 2000, 1: 123-126.[9]Wolniansky W, Foschini G J, Golder G D, et al.. V-BLAST: An architecture for realizing very high data rates over the rich-scattering wireless channel. 1998 URSI International Symposium on Signals, Systems, and Electronics, Pisa 1998: 295-300.[10]Sellathurai M, Haykin S. TURBO-BLAST for wireless communications: Theory and experiments[J].IEEE Trans. on Signal Processing.2002, 50(10):2538-2546[11]Bahl L R, Cocke J, Jelinek F, et al.. Optimal decoding of linear codes for minimizing symbol error rate. IEEE Trans. on Information Theory, 1974, 20(2): 284-287.[12]张贤达. 矩阵分析与应用. 北京: 清华大学出版社, 2004: 68-69.[13]Poor H V, Verdu S. Probability of error in MMSE multiuser detection[J].IEEE Trans. on Information Theory.1997, 43(3):858-871

施引文献

资源附件(0)

访问统计