认知MIMO网络中增强型干扰对齐算法

发布时间：2018-11-20 10:00

【摘要】：针对认知多输入多输出(MIMO)网络中传统基于最大信干噪比的干扰对齐算法,在发送多数据流时随着信噪比的增加不易收敛以及数据流之间的干扰突出的问题,提出一种充分考虑数据流间干扰并进行迭代限制的干扰对齐算法。首先,次用户通过编码设计消除主次间的干扰;然后,在消除主用户之间和次用户之间干扰时,根据信道互易性,运用广义瑞利熵计算基于最大信干噪比算法的预编码与干扰抑制矩阵,并在迭代过程中,每次迭代始终使预编码与干扰抑制矩阵先满足干扰功率在期望信号空间最小;最后,结合次用户间MIMO干扰信道、主次用户间构成的MIMO干扰信道以及次用户网络干扰对齐的必要性,推导出次用户可达自由度上限。实验结果表明,相比传统最大信干噪比算法,所提算法在信噪比较低时次用户总容量无明显提高,但随着信干噪比的增加其优势越来越明显;当达到收敛时,所提算法迭代次数比传统最大信干噪比算法约减少40%。因此,所提算法能够提高系统容量且加快收敛。
[Abstract]:In view of the traditional interference alignment algorithm based on maximum signal-to-noise ratio in cognitive multi-input and multiple-output (MIMO) networks, it is difficult to converge with the increase of SNR and the interference between data streams is prominent when transmitting multiple data streams. In this paper, an interference alignment algorithm is proposed, which takes full account of interstream interference and is restricted by iteration. First, the secondary user eliminates the interference between the primary and the secondary by coding design. Then, in order to eliminate the interference between primary and secondary users, the generalized Rayleigh entropy is used to calculate the precoding and interference suppression matrix based on the maximum signal-to-noise ratio algorithm according to the channel reciprocity. Each iteration always makes the precoding and interference suppression matrix satisfy the interference power in the desired signal space first. Finally, combined with the necessity of MIMO interference channel between secondary users, the MIMO interference channel between primary and secondary users and the interference alignment of secondary user network, the upper limit of degree of freedom for secondary users is derived. The experimental results show that compared with the traditional maximum signal-to-noise ratio algorithm, the proposed algorithm has no significant increase in the total capacity of users at low SNR, but with the increase of signal-to-noise ratio, the advantages of the proposed algorithm become more and more obvious. When convergence is reached, the number of iterations of the proposed algorithm is about 40% less than that of the traditional maximum signal-to-noise ratio algorithm. Therefore, the proposed algorithm can improve the system capacity and speed up convergence.
【作者单位】：重庆邮电大学移动通信技术重点实验室;
【基金】：长江学者和创新团队发展计划资助项目(IRT1299) 重庆市科委重点实验室专项经费资助项目(cstc2013yykfA40010)~~
【分类号】：TN919.3

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