为了提高时变信道环境中MIMO信道估计的性能,利用KarhunenLoeve基扩展模型(KLBEM)建立MIMO系统中符合期望最大化(EM)算法框架的信号模型,从而得到MIMO时变信道的迭代估计方法.将EM算法应用于MIMO系统中进行迭代信道估计,一方面利用了EM迭代来提高信道估计的性能,另一方面利用了KLBEM基函数的正交性来降低信道估计的运算复杂度.在2×2 MIMO系统下的仿真结果表明:算法经5次迭代即可收敛,而且迭代估计的信道脉冲响应与实际响应几乎重合;此外,迭代估计后系统的BER性能接近理想信道时的BER性能,在高信噪比区域,两者之间的差别在1 dB以内,比最小二乘信道估计有约2 dB的性能增益,可见迭代估计方法在时变信道条件下具有良好的估计性能.
Abstract
Abstract: In order to improve the channel estimation performance for MIMO systems in timevarying channels, a signal model fitting the framework of expectation maximization (EM) algorithm was established based on the KarhunenLoeve basis expansion model(KLBEM). The channel response was estimated in iterative fashion by EM algorithm. In the estimation scheme, the EM iterations and the orthogonality of KLBEM basis functions were introduced to improve the estimation performance and reduce the computational complexity, respectively. The simulation results of 2 by 2 MIMO system show that the proposed scheme convergences after 5 iterations and the estimated channel impulse response is nearly consistent with the actual one. The bit error rate (BER) performance by the proposed scheme is near to that of perfect channel knowledge. At high signal to noise ratio region, the difference between them is lower than 1 dB with 2 dB performance enhancement over the least square channel estimator. The proposed scheme has good estimation performance in timevarying channel conditions.
关键词
多输入多输出 /
信道估计 /
期望最大化算法 /
时变信道 /
基扩展模型
{{custom_keyword}} /
Key words
multiple input and multiple output /
channel estimation /
expectation maximization algorithm /
time varying channel /
basis expansion model
{{custom_keyword}} /
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1]赵睿.结合波束形成的双向中继选择策略.江苏大学学报:自然科学版, 2011, 32(6): 706-709.
Zhao Rui. Twoway relay selection strategy combined with beamforming. Journal of Jiangsu University:Natural Science Edition, 2011, 32(6): 706-709.(in Chinese)
[2]Zafarani E, Omidi M J, Heydaryan F, et al. Oversampled legendre basis expansion model for doublyselective channels // Proceedings of 2011 19th Iranian Conference on Electrical Engineering. Tehran, Iran: IEEE Computer Society, Article number: 5955647.
[3]Gupta P, Mehra D K. A novel technique for channel estimation and equalization for high mobility OFDM systems . Wireless Personal Communications, 2009, 49 (4):613-631.
[4]Barhumi I, Leus G, Moonen M. MMSE estimation of basis expansion models for rapidly timevarying channels // Proceedings of EUSIPCO 2005. Antalya, Turkey: European Association for Signal Processing, 2005: 1728-1732.
[5]Tang Z, Leus G. Timemultiplexed training for timeselective channels . IEEE Signal Processing Letters, 2007, 14 (9): 585-588.
[6]Xie Y Z, Georghiades C N. Two EMtype channel estimation algorithm for OFDM with transmitter diversity . IEEE Transactions on Communications, 2003, 51(1): 106-115.
[7]Ylioinas J, Juntti M. Iterative joint detection, decoding, and channel estimation in turbocoded MIMOOFDM . IEEE Transactions on Vehicular Technology, 2009,58(4): 1784-1796.
[8]许鹏,汪晋宽,祁峰.基于EM的MIMOOFDM系统MAP信道估计算法.系统工程与电子技术, 2010, 32 (1): 27-30.
Xu Peng, Wang Jinkuan, Qi Feng. EMbased MAP channel estimation algorithm for MIMOOFDM systems . Systems Engineering and Electronics, 2010, 32(1): 27-30.(in Chinese)
[9]Kandovan R S,Salari S. Joint frequency and channel estimation for MIMOOFDM systems via the EM algorithm // Proceedings of 2010 7th International Conference on Wireless and Optical Communications Networks. Colombo, Sri Lanka: Association for Computing Machinery, doi: 10.1109/WOCN.2010.5587332.
[10]Yang Feng, Song Jian, Zhang Yu, et al. SAGEbased estimation of doubly selective channel with an orthogonal polynomial model . Signal Processing, 2008, 88 (4): 1061-1068.
[11]Dogˇan H, Panayrc E, Vincent Poor H.Lowcomplexity joint data detection and channel equalization for highly mobile orthogonal frequency division multiplexing systems. IET Commun, 2010, 4 (8):1000-1011.
[12]Baracca P, Tomasin S, Vangelista L, et al. Per subblock equalization of very long OFDM blocks in mobile communications . IEEE Transactions on Communications, 2011, 59 (2): 363-368.
{{custom_fnGroup.title_cn}}
脚注
{{custom_fn.content}}
基金
侨办科研基金资助项目(11QZR02); 福建省自然科学基金资助项目(2012J05119); 华侨大学科研基金资助项目(12BS230); 广西无线宽带通信与信号处理重点实验室2011年度主任基金资助项目(21104)
{{custom_fund}}