Data-Aided Channel Estimator for MIMO Systems via Reinforcement Learning

Yo Seb Jeon, Jun Li, Nima Tavangaran, H. Vincent Poor

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a data-aided channel estimator that reduces the channel estimation error of the conventional linear minimum-mean-squared-error (LMMSE) method for multiple-input multiple-output communication systems. The basic idea is to selectively exploit detected symbol vectors obtained from data detection as additional pilot signals. To optimize the selection of the detected symbol vectors, a Markov decision process (MDP) is defined which finds the best selection to minimize the mean-squared-error (MSE) of the channel estimate. Then a reinforcement learning algorithm is developed to solve this MDP in a computationally efficient manner. Simulation results demonstrate that the presented channel estimator significantly reduces the MSE of the channel estimate and therefore improves the block error rate of the system, compared to the conventional LMMSE method.

Original languageEnglish (US)
Title of host publication2020 IEEE International Conference on Communications, ICC 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728150895
DOIs
StatePublished - Jun 2020
Event2020 IEEE International Conference on Communications, ICC 2020 - Dublin, Ireland
Duration: Jun 7 2020Jun 11 2020

Publication series

NameIEEE International Conference on Communications
Volume2020-June
ISSN (Print)1550-3607

Conference

Conference2020 IEEE International Conference on Communications, ICC 2020
CountryIreland
CityDublin
Period6/7/206/11/20

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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    Jeon, Y. S., Li, J., Tavangaran, N., & Poor, H. V. (2020). Data-Aided Channel Estimator for MIMO Systems via Reinforcement Learning. In 2020 IEEE International Conference on Communications, ICC 2020 - Proceedings [9149283] (IEEE International Conference on Communications; Vol. 2020-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICC40277.2020.9149283