Performance Limits of Massive MIMO Systems Based on Bayes-Optimal Inference
Abstract
This paper gives a replica analysis for the minimum mean square error (MSE) of a massive multiple-input multiple-output (MIMO) system by using Bayesian inference. The Bayes-optimal estimator is adopted to estimate the data symbols and the channels from a block of received signals in the spatial-temporal domain. We show that using the Bayes-optimal estimator, the interfering signals from adjacent cells can be separated from the received signals without pilot information. In addition, the MSEs with respect to the data symbols and the channels of the desired users decrease with the number of receive antennas and the number of data symbols, respectively. There are no residual interference terms that remain bounded away from zero as the numbers of receive antennas and data symbols approach infinity.
Cite
@article{arxiv.1410.1382,
title = {Performance Limits of Massive MIMO Systems Based on Bayes-Optimal Inference},
author = {Chao-Kai Wen and Yongpeng Wu and Kai-Kit Wong and Robert Schober and Pangan Ting},
journal= {arXiv preprint arXiv:1410.1382},
year = {2016}
}
Comments
Submitted to IEEE ICC 2015 (slightly extended version)