基于期望传播的分布式信号检测算法

针对大规模集中式天线阵列带来的硬件开销大与信号检测复杂度高等问题, 研究了期望传播算法在分布式广义线性模型中的应用, 提出了一种基于分布式的信号检测方案。首先将大规模天线阵列均分为多个独立并行的子阵列, 并在每个子阵列中独立地进行消息迭代更新, 再由一个集中处理模块对消息进行汇总, 直至迭代完成。仿真结果表明, 与期望一致信号检测算法相比, 提出的算法在降低计算复杂度的同时能够维持良好的检测性能, 研究表明该算法能够较好地适用于分布式广义线性模型。

Decentralized signal detection algorithm based on expectation propagation

Aiming at the problems of high hardware cost and signal detection complexity caused by large-scale centralized antenna array, the application of expectation propagation algorithm in decentralized generalized linear model is studied, and a decentralized signal detection scheme is proposed. Firstly, the large-scale antenna array is divided into multiple independent parallel subarrays, and the messages are iteratively updated in each subarray independently, and then the messages are summarized by a centralized processing module until the algorithm is completed. The simulation results show that compared with the expected consistent signal detection algorithm, the proposed algorithm can reduce the computational complexity and maintain good detection performance. The research shows that the algorithm can be perfectly applicable to the decentralized generalized linear model.