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 re...

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Bibliographic Details
Published inWireless personal communications Vol. 97; no. 4; pp. 6483 - 6498
Main Authors Sohail, M. Farhan, Ghauri, Sajjad A., Alam, Sheraz
Format Journal Article
LanguageEnglish
Published New York Springer US 01.12.2017
Springer Nature B.V
Subjects
Beamforming
Communication networks
Communications Engineering
Computer Communication Networks
Computer simulation
Decoding
Electronic devices
Engineering
Evolutionary algorithms
Filtration
Genetic algorithms
Heuristic methods
MIMO (control systems)
Networks
Optimization techniques
Parallel processing
Particle swarm optimization
Signal,Image and Speech Processing
Wireless communication systems
Wireless communications
Wireless networks
Channel estimation
Massive MIMO
Heuristic techniques
Genetic Algorithm
Channel State Information
Particle Swarm Optimization
Differential Evolution (DE)
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Summary: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.
ISSN:0929-6212
1572-834X
DOI:10.1007/s11277-017-4849-0