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Distributed Receiver Processing for Extra-Large MIMO Arrays: A Message Passing Approach
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DOI：10.1109/TWC.2021.3114380.png)
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We study the design of receivers in extra-large scale MIMO (XL-MIMO) systems, i.e. systems in which the base station is equipped with an antenna array of extremely large dimensions. While XL-MIMO can significantly increase the system's spectral efficiency, they present two important challenges. One is the increased computational cost of multi-antenna processing. The second one is the presence of spatial non-stationarities in the channel response, which imply that the mean energy of a given user's signal varies across the array. Such non-stationarities limit the performance of the system. In this paper, we propose a distributed receiver for such an XL-MIMO system that can address both challenges. Based on variational message passing (VMP), we propose a set of receiver options providing a range of complexity-performance characteristics to adapt to different requirements. Furthermore, we distribute the processing into local processing units (LPU), that can perform most of the complex processing in parallel, before sharing their outcome with a central processing unit (CPU). Our designs are specifically tailored to exploit the spatial non-stationarities and require lower computations than linear receivers. Our simulation study, performed with a channel model accounting for the special characteristics of XL-MIMO channels, confirms the superior performance of our proposals compared to the state of the art methods.
Keyword:
Antenna arrays
Complexity theory
Receiving antennas
Channel models
Central Processing Unit
Wireless communication
Message passing
Massive MIMO
message passing
extra-large scale MIMO
beyond 5G (B5G)
large intelligent surface
spatial non-stationary
complexity reduction
期刊
IF:
10.7
论文数:
1.3W
被引数:
5.3W
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