一种基于最大化Rayleigh熵的稳健干扰对齐算法

A Robust Interference Alignment Algorithm Based on Maximizing the Rayleigh Entropy

干扰对齐在消除干扰方面具有独到的优势,但需要完美的信道状态信息(CSI),这在实际中很难实现。该文分析了传统稳健干扰对齐方案的优缺点,在此基础上,提出一种最大化Rayleigh熵的稳健干扰对齐算法,并对收敛性,自由度和频谱效率等进行了分析。不同于MAX-SINR算法,该文通过最大化信号的Rayleigh熵,求得干扰抑制矩阵。在正向通信中,考虑到数据流之间的相关性取干扰抑制矩阵为原始干扰抑制矩阵的酉矩阵形式,并采用注水功率分配实现用户数据流间的最佳功率分配;基于信道的互惠性,在反向通信时,做类似的处理。通过迭代计算,逐渐将干扰压缩。最后,在完美CSI和误差CSI时,仿真表明该算法显著地提高了系统的性能。

Interference alignment has the advantage of eliminating interference, but it needs the perfect Channel State Information （CSI） which is difficult to achieve in practical systems. The advantages and disadvantages of robust interference alignment algorithms are analyzed in this paper. And then a robust interference alignment algorithm based on maximizing the Rayleigh entropy is proposed. The convergence, the degree of freedom and spectrum efficiency are analyzed at the same time. Unlike MAX-SINR algorithm, interference suppression matrix is obtained through maximizing the signal Rayleigh entropy. The unitary form of original interference suppression matrix is regarded as the optimal interference suppression matrix considering the correlation among the data flows. And then, the water-filling power allocation scheme is used to realize the optimal power allocation among user data flows. Meanwhile, the similar process is carried out in reverse communication link based on channel reciprocity. The interference is reduced gradually through alternately computing. Finally, under the conditions of perfect CSI and error CSI, the simulation results verify that the proposed algorithm improves the performance of the system.