摘要
针对MIMO-OFDM系统,提出了一种基于复数FastICA的盲多用户检测算法.该算法首先利用复数FastICA算法的快速收敛特性来提高多用户的分离速度,同时利用信号的相关函数对复数FastICA算法引起的幅度不确定性和相位不确定性进行了修正,最后将所提出的改进算法与复数自然梯度学习算法(CNGLA)进行仿真比较.结果表明,相比于传统的自然梯度算法,所提算法不仅收敛速度较快,而且具有更低的误码率,另外随着接收天线的增多,信号的分离效果会更好.
A new blind multi-user detection algorithm was proposed on the basis of complex FastlCA in MIMO-OFDM system. With the proposed algorithm, the separation of multi-user could be speeded up by fast convergence characteristics of complex FastlCA algorithm firstly, and the indeterminacy of amplitude and indeterminacy of phase by CFastlCA algorithm were revised by using correlation function. At last, comparing the improved algorithm with the complex natural gradient learning algorithm( CNGLA), it was proved that CFastlCA algorithm has not only faster convergent speed but also smaller bit error rate. It also indicated that using more numbers of receiving antennas would get better signal separation.
出处
《东北大学学报(自然科学版)》
EI
CAS
CSCD
北大核心
2014年第9期1253-1256,1261,共5页
Journal of Northeastern University(Natural Science)
基金
中央高校基本科研业务费专项资金资助项目(N100404018)