A Low-Complexity Algorithm for a Reinforcement Learning-Based Channel Estimator for MIMO Systems

This paper proposes a low-complexity algorithm for a reinforcement learning-based channel estimator for multiple-input multiple-output systems. The proposed channel estimator utilizes detected symbols to reduce the channel estimation error. However, the detected data symbols may include errors at th...

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Bibliographic Details

Published in:	Sensors (Basel, Switzerland) Vol. 22; no. 12; p. 4379
Main Authors:	Kim, Tae-Kyoung, Min, Moonsik
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 09.06.2022 MDPI
Subjects:	Accuracy Algorithms channel estimation Markov decision process multiple-input multiple-output Optimization Probability Random variables reinforcement learning Sensors Transmitters
ISSN:	1424-8220, 1424-8220
Online Access:	Get full text
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