User Selection for Massive MIMO under Line-of-Sight Propagation

被引:7
|
作者
Chaves, Rafael S. [1 ,2 ]
Lima, Markus V. S. [2 ]
Cetin, Ediz [1 ]
Martins, Wallace A. [3 ]
机构
[1] Macquarie Univ, Sch Engn, Sydney, NSW 2109, Australia
[2] Univ Fed Rio de Janeiro, Elect Engn Program PEE Coppe, BR-21941909 Rio De Janeiro, Brazil
[3] Univ Luxembourg, Interdisciplinary Ctr Secur Reliabil & Trust, L-4365 Esch Sur Alzette, Luxembourg
关键词
Massive MIMO; Interference; Antennas; Clustering algorithms; Signal to noise ratio; Machine learning algorithms; Throughput; favorable propagation; user selection; line-of-sight channel; inter-channel interference; IMPROVED DROPPING ALGORITHM; CHANNEL ESTIMATION; DOWNLINK; SYSTEMS; 5G; PERFORMANCE; WIRELESS; NETWORKS;
D O I
10.1109/OJCOMS.2022.3172621
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper provides a review of user selection algorithms for massive multiple-input multiple-output (MIMO) systems under the line-of-sight (LoS) propagation model. Although the LoS propagation is extremely important to some promising technologies, like in millimeter-wave communications, massive MIMO systems are rarely studied under this propagation model. This paper fills this gap by providing a comprehensive study encompassing several user selection algorithms, different linear precoders and simulation setups, and also considers the effect of partial channel state information (CSI). One important result is the existence of practical cases in which the LoS propagation model may lead to significant levels of interference among users within a cell; these cases are not satisfactorily addressed by the existing user selection algorithms. Motivated by this issue, a new user selection algorithm based on inter-channel interference (ICI) called ICI-based selection (ICIBS) is proposed. Unlike other techniques, the ICIBS accounts for the ICI in a global manner, thus yielding better results, especially in cases where there are many users interfering with each other. In such scenarios, simulation results show that when compared to the competing algorithms, the proposed approach provided an improvement of at least 10.9% in the maximum throughput and 7.7% in the 95%-probability throughput when half of the users were selected.
引用
收藏
页码:867 / 887
页数:21
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