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...

Celý popis

Podrobná bibliografia

Vydané v:	Sensors (Basel, Switzerland) Ročník 22; číslo 12; s. 4379
Hlavní autori:	Kim, Tae-Kyoung, Min, Moonsik
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 09.06.2022 MDPI
Predmet:	Accuracy Algorithms channel estimation Markov decision process multiple-input multiple-output Optimization Probability Random variables reinforcement learning Sensors Transmitters
ISSN:	1424-8220, 1424-8220
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!