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Performance Analysis of MRC Receivers with Adaptive Modulation and Coding in Rayleigh Fading Correlated Channels with Imperfect CSIT
Ref: CISTER-TR-161102       Publication Date: Jan 2017

Performance Analysis of MRC Receivers with Adaptive Modulation and Coding in Rayleigh Fading Correlated Channels with Imperfect CSIT

Ref: CISTER-TR-161102       Publication Date: Jan 2017

Abstract:
This paper addresses the performance analysis of an adaptive wireless link with one antenna transmitter and a multiple-antenna maximum-ratio combining (MRC) receiver. Two main assumptions are used throughout this paper: 1) Rayleigh fading correlated channels (i.e., MRC branch correlation), and 2) imperfect (outdated) channel state information at the transmitter side (CSIT). The main contribution of this work lies in the derivation of closed-form analytical expressions (in terms of a series expansion) of the statistics of correct packet reception conditional on the decisions made by the transmitter based on outdated CSIT. The novelty of this derivation is the joint modelling of spatially correlated branches, imperfect CSIT and adaptive modulation based on threshold-trigger decision. The results presented here suggest that spatial correlation not always affects the performance of the MRC receiver: at low signal-to-noise ratio (SNR), correlation can improve performance rather than degrading it. By contrast, at high SNR, correlation is found to always degrade performance. At high SNR, correlation tends to worse the degrading effects of imperfect CSIT, particularly when the number of antennas increases. Imperfect CSIT causes errors in the assignment of MCSs, thus reducing throughput performance. These errors become more evident in the high SNR regime, particularly when the values of branch correlation and the number of antennas both increase.

Authors:
Ramiro Robles
,
Egons Lavendelis
,
Eduardo Tovar


Published in Wireless Communications and Mobile Computing, Hindawi, Volume 2016, Article No 6940368, pp 1-12.

DOI:10.1155/2017/6940368.
ISSN: 1530-8677.



Record Date: 7, Nov, 2016