Channel Estimation in Massive MIMO Systems Using Heuristic Approach

Channel Estimation in Massive MIMO Systems Using Heuristic Approach The significant forecasted increase in the number of devices and mobile data requirements has posed stringent requirements for future wireless communication networks. Massive MIMO is one of the chief candidates for future 5G wireless communication systems, but to fully reap the true benefits many research problems still need to be solved or require further analysis. Among many, the problem of estimating channel between the user terminals and each BS antenna holds a significant place. In this paper, we deal with the accurate and timely acquisition of massive Channel State Information as an optimization problem that is solved using heuristic optimization techniques i.e. Genetic Algorithm, Particle Swarm Optimization and Differential Evolution. Results have been obtained by exploiting the parallel processing property bestowed when using match filtering and beamforming for precoding and decoding respectively. Monte Carlos simulation have been presented for the purpose of performance comparison among aforementioned optimization techniques based on Mean Squared Error criterion. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Wireless Personal Communications Springer Journals

Channel Estimation in Massive MIMO Systems Using Heuristic Approach

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Publisher
Springer US
Copyright
Copyright © 2017 by Springer Science+Business Media, LLC
Subject
Engineering; Communications Engineering, Networks; Signal,Image and Speech Processing; Computer Communication Networks
ISSN
0929-6212
eISSN
1572-834X
D.O.I.
10.1007/s11277-017-4849-0
Publisher site
See Article on Publisher Site

Abstract

The significant forecasted increase in the number of devices and mobile data requirements has posed stringent requirements for future wireless communication networks. Massive MIMO is one of the chief candidates for future 5G wireless communication systems, but to fully reap the true benefits many research problems still need to be solved or require further analysis. Among many, the problem of estimating channel between the user terminals and each BS antenna holds a significant place. In this paper, we deal with the accurate and timely acquisition of massive Channel State Information as an optimization problem that is solved using heuristic optimization techniques i.e. Genetic Algorithm, Particle Swarm Optimization and Differential Evolution. Results have been obtained by exploiting the parallel processing property bestowed when using match filtering and beamforming for precoding and decoding respectively. Monte Carlos simulation have been presented for the purpose of performance comparison among aforementioned optimization techniques based on Mean Squared Error criterion.

Journal

Wireless Personal CommunicationsSpringer Journals

Published: Aug 20, 2017

References

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