A Novel User and Antenna Selection Techniques in Massive MIMO 5G Wireless Communication System

Loading...
Thumbnail Image

Authors

Sheikh, Tasher Ali
Bora, Joyatri
Hussain, Md Anwar

Advisor

Referee

Mark

Journal Title

Journal ISSN

Volume Title

Publisher

Společnost pro radioelektronické inženýrství

ORCID

Altmetrics

Abstract

In this paper, we have proposed a new paradigm for user scheduling in large-scale multiple-input multiple-output (MIMO) time division duplexing (TDD) system. In this paper, we have selected the users from different groups with semi-orthogonal (SO) and random criterion. We separate the users in different groups with the K-means clustering algorithm which assigns the users into different groups. After user groups are so determined, we use two new user selection paradigms where users are selected in two methods- firstly we select the users in intra-group those are SO with each other along with it also SO with other groups’ users. Secondly, users are selected from inter-group those are SO with each other also SO with other group users. In both the selection schemes antennas are scheduled based on the maximum gain of the channel. In the results, it is noticed that in intra-group with semi-orthogonal user selection (SUS) and antenna selection (AS) using the zero-forcing (ZF) precoding shown the highest systems rate. We also evaluated the computation cost of our modified proposed algorithm which is exposed in table-1. We explored the efficiency of the proposed schemes through MATLAB simulations.

Description

Citation

Radioengineering. 2020 vol. 29, č. 3, s. 548-554. ISSN 1210-2512
https://www.radioeng.cz/fulltexts/2020/20_03_0548_0554.pdf

Document type

Peer-reviewed

Document version

Published version

Date of access to the full text

Language of document

en

Study field

Comittee

Date of acceptance

Defence

Result of defence

Collections

Endorsement

Review

Supplemented By

Referenced By

Creative Commons license

Except where otherwised noted, this item's license is described as Creative Commons Attribution 4.0 International license
Citace PRO