修正的MIMO-FSO信道自适应SVD估计算法

徐建武; 王红星; 胡昊; 孙晓明

doi:doi:10.3788/cjl201138.1105001

中国激光, 2011, 38 (11): 1105001, 网络出版: 2011-10-27

修正的MIMO-FSO信道自适应SVD估计算法

Modified Adaptive SVD Estimating Algorithm about MIMO-FSO Channels

论文大纲

徐建武 ^*王红星胡昊孙晓明

作者单位

海军航空工程学院电子与信息工程系，山东烟台 264001

摘要

针对多入多出（MIMO）无线光通信(FSO)中传统的奇异值分解（SVD）信道估计算法由于训练序列的单极性容易导致信号能量损失，从而引起信道估计值不准确的问题，提出了一种修正的自适应SVD估计算法。该修正算法能对SVD算法中存在的估计误差进行补偿，从而能使该估计方法更好地应用于MIMO-FSO系统中。仿真结果表明，与SVD算法相比，在信噪比为15 dB时，修正的算法有2个数量级的均方误差（MSE）性能提高，在信噪比为30 dB时，MSE性能有3个数量级的提高。与相同条件下的均值修正SVD算法相比，平均有1 dB左右的性能改善。该修正方法可移植性强，在其他信道估计方法中也可采用类似的改进方法。

Abstract

Because the training serials are unipolar in multi-input multi-output free space optical communication (MIMO-FSO) systems, which leads to the signal energy loss easily, the result of traditional singular value decomposition (SVD) channel estimation algorithm is inaccurate. A kind of modified adaptive SVD estimation algorithm is put forward which can compensate for the estimation errors of SVD algorithm. So the modified adaptive SVD estimation algorithm can be better fit for MIMO-FSO systems. The simulation results indicate that compared with the SVD algorithm, the mean square error (MSE) performance of the modified algorithm is improved by two and three orders of magnitude when the signal-to-noise ratio (SNR) is 15 dB and 30 dB, respectively. Compared with the average value modified SVD algorithm, the modified algorithm has 1 dB improvement of the MSE performance under the same condition. The modified algorithm possesses strong transplanting property and can be adopted in other channel estimation methods.

参考文献

[1] 胡昊, 王红星, 周旻等. 湍流大气中脉冲位置调制和数字脉冲间隔调制差错性能的建模与分析［J］. 中国激光, 2010, 37(5): 1269～1274

Hu Hao, Wang Hongxing, Zhou Min et al.. Modeling and analyzing of error performance for pulse position modulation and digital pulse interval modulation under turbulence［J］. Chinese J. Lasers, 2010, 37(5): 1269～1274

[2] 谢伟良, 刘璐, 汤俊雄. 无线光通信差错控制系统的时间参数特性［J］. 中国激光, 2004, 31(5): 575～578

Xie Weiliang, Liu Lu, Tang Junxiong. Analysis on characterization of atmospheric optical wireless communication system based on turbo code［J］. Chinese J. Lasers, 2004, 31(5): 575～578

[3] Zheng Ziwei, Yang Zhixing, Pan Changyong et al.. Synchronization and channel estimation for TDS-OFDM systems［C］. Vehicular Technology Conference 2003, 2: 1229～1233

[4] H. Minn, V. K. Bhargava. An investigation into time-domain approach for OFDM channel estimation［J］. IEEE Trans. Broadcasting, 2000, 46(4): 240～248

[5] 严冬. MIMO系统的信道估计算法研究及仿真［D］. 南京: 河海大学, 2004

Yan Dong. Study and Simulation of Channel Estimates Algorithms of MIMO Systems［D］. Nanjing: Hehai University, 2004

[6] 杨剑啸, 徐元欣, 赵小祥等. DVB-T中非自适应和自适应信道估计算法的实现［J］. 电路与系统学报, 2006, 11(3): 139～144

Yang Jianxiao, Xu Yuanxin, Zhao Xiaoxiang et al.. Implement of non-adaptive and adaptive channel estimates algorithms in DVB-T［J］. Journal of Circuit and System, 2006, 11(3): 139～144

[7] 柯熙政, 殷致云. 无线激光通信系统中的编码理论［M］. 北京: 科学出版社, 2008. 262～270

Ke Xizheng, Yin Zhiyun. Coding Theory in FSO Communication Systems［M］. Beijing: Science Press, 2008. 262～270

[8] 何键, 胡艳军. 基于SVD算法的无线光MIMO系统的性能分析［J］. 安徽大学学报, 2007, 31(3): 34～37

He Jian, Hu Yanjun. Performance analysis of FSO-MIMO systems based on SVD algorithm［J］. Journal of Anhui University, 2007, 31(3): 34～37

[9] A. Benjebbour, S. Yoshida. Performance improvement of ordered successive detection with imperfect channel estimates for MIMO systems［J］. IEICE Trans. Commun., 2003, E86-B(11): 1287～1291

[10] 温广瑞. 奇异值分解技术在声音信息分离中的应用［J］. 西安交通大学学报, 2003, 37(1): 37～40

Wen Guangrui. The application of SVD technology in sound information separation［J］. Journal of Xi′an Jiaotong University, 2003, 37(1): 37～40

徐建武, 王红星, 胡昊, 孙晓明. 修正的MIMO-FSO信道自适应SVD估计算法[J]. 中国激光, 2011, 38(11): 1105001. Xu Jianwu, Wang Hongxing, Hu Hao, Sun Xiaoming. Modified Adaptive SVD Estimating Algorithm about MIMO-FSO Channels[J]. Chinese Journal of Lasers, 2011, 38(11): 1105001.

修正的MIMO-FSO信道自适应SVD估计算法

关于本站 Cookie 的使用提示

全站搜索

修正的MIMO-FSO信道自适应SVD估计算法

相关论文

相关资讯

关于本站 Cookie 的使用提示

全站搜索