PSO Based Sum Rate Optimization for MU-MIMO Linear Precoder with Imperfect CSI

It is well known that if the perfect CSI is available at the BS, achieving the maximum sum throughput is equivalent to minimizing the product of mean square error matrix determinants (PDetMSE). Due to the presence of background noise in the estimated signal, the channel estimation errors are unavoid...

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Vydáno v:Wireless personal communications Ročník 92; číslo 3; s. 1039 - 1051
Hlavní autoři: Kejalakshmi, V., Arivazhagan, S.
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.02.2017
Springer Nature B.V
Témata:
Algorithms
Background noise
Channels
Communications Engineering
Computer Communication Networks
Design optimization
Engineering
Equivalence
Errors
Maximization
Networks
Particle swarm optimization
Signal,Image and Speech Processing
Swarm intelligence
Systems design
Transmitters
Variance
Imperfect CSI
MIMO
Sum throughput
Product of Mean square error matrix determinants (PDetMSE)
PSO
Linear precoder
ISSN:0929-6212, 1572-834X
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Shrnutí:It is well known that if the perfect CSI is available at the BS, achieving the maximum sum throughput is equivalent to minimizing the product of mean square error matrix determinants (PDetMSE). Due to the presence of background noise in the estimated signal, the channel estimation errors are unavoidable. Hence, in this paper, it is assumed that the imperfect CSI is available at the BS and the channel estimation error variance is known at the transmitter. It is shown that maximizing the achievable sum rate is not exactly equal to minimizing the PDetMSE if the channel estimation error variance is included in the system design. Particle Swarm Optimization algorithm is used here to solve the sum rate maximization problem under the imperfect CSI. The simulation results compare the proposed system, which considers the channel estimation error variance as an integral part of the system design, with an existing system which assumes the perfect CSI at the transmitter side.
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ISSN:0929-6212
1572-834X
DOI:10.1007/s11277-016-3591-3