Pilot Decontamination in Spatially Correlated Massive MIMO Uplink via Expectation Propagation
Pilot Decontamination in Spatially Correlated Massive MIMO Uplink via Expectation Propagation
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DOI：
10.1587/transfun.2020eap1073
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发表时间：
2021-04-01
影响因子：
0.5
通讯作者：
Takeuchi, Keigo
中科院分区：
文献类型：
--
作者：
Tatsuno, Wataru;Takeuchi, Keigo
研究了大规模多输入多输出（MIMO）上行链路中的导频污染问题。导频污染是由相邻小区中相同导频序列的重复使用引起的。为了解决导频污染，基站利用不同用户的传输帧之间的差异，这些差异通过联合信道和数据估计来检测。在压缩感知中，联合估计被看作是一个双线性推理问题。利用期望传播（EP）提出了一种迭代的信道和数据估计算法。通过时移导频获得初始信道估计，而不利用关于大尺度衰落的信息。该算法对传统的双线性自适应向量近似消息传递算法（BAd-VAMP）进行了两点改进。一种是EP在信道估计中使用软判决之后的数据估计，而BAd-VAMP在软判决之前使用它们。另一点是EP可以利用信道矩阵的先验分布，而BAd-VAMP原则上不能。数值模拟表明，EP收敛速度比BAd-VAMP在空间相关MIMO，其中近似消息传递无法收敛到相同的固定点EP和BAd-VAMP。
This paper addresses pilot contamination in massive multiple-input multiple-output (MIMO) uplink. Pilot contamination is caused by reuse of identical pilot sequences in adjacent cells. To solve pilot contamination, the base station utilizes differences between the transmission frames of different users, which are detected via joint channel and data estimation. The joint estimation is regarded as a bilinear inference problem in compressed sensing. Expectation propagation (EP) is used to propose an iterative channel and data estimation algorithm. Initial channel estimates are attained via time-shifted pilots without exploiting information about large scale fading. The proposed EP modifies two points in conventional bilinear adaptive vector approximate message-passing (BAd-VAMP). One is that EP utilizes data estimates after soft decision in the channel estimation while BAd-VAMP uses them before soft decision. The other point is that EP can utilize the prior distribution of the channel matrix while BAd-VAMP cannot in principle. Numerical simulations show that EP converges much faster than BAd-VAMP in spatially correlated MIMO, in which approximate message-passing fails to converge toward the same fixed-point as EP and BAd-VAMP.