Performance Limits of Massive MIMO Systems Based on Bayes-Optimal Inference.

IEEE International Conference on Communications(2015)

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摘要
This paper gives a replica analysis for the minimum mean square error (MSE) of a massive multiple-input multipleoutput (MIMO) system by using Bayesian inference. The Bayesoptimal 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 of the interfering signals. 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.
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关键词
MIMO communication,belief networks,least mean squares methods,receiving antennas,Bayes optimal estimator,Bayes-optimal inference,MSE,data symbols,massive MIMO systems,massive multiple-input multiple output system,minimum mean square error,residual interference,spatial-temporal domain
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