Symbol Detection for Massive MIMO AF Relays Using Approximate Bayesian Inference

Haochuan Zhang; Qiuyun Zou

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arXiv · 2003.11760

Symbol Detection for Massive MIMO AF Relays Using Approximate Bayesian Inference

Haochuan Zhang·Qiuyun Zou

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Abstract

For massive MIMO AF relays, symbol detection becomes a practical issue when the number of antennas is not large enough, since linear methods are non-optimal and optimal methods are exponentially complex. This paper proposes a new detection algorithm that offers Bayesian-optimal MSE at the cost of $O(n^3)$ complexity per iteration. The algorithm is in essence a hybrid of two methods recently developed for deep learning, with particular optimization for relay. As a hybrid, it inherits from the two a state evolution formulism, where the asymptotic MSE can be precisely predicted through a scalar equivalent model. The algorithm also degenerates easily to many results well-known when single-hop considered.

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Haochuan Zhang, Qiuyun Zou. 2020-03-26. Symbol Detection for Massive MIMO AF Relays Using Approximate Bayesian Inference. https://arxiv.org/abs/2003.11760

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