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Performance analysis of LDPC-coded diversity combining on rayleigh fading channels with impulsive noise

Lookup NU author(s): Zhen Mei, Dr Martin Johnston, Dr Stephane Le Goff, Dr Li Chen

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This is the authors' accepted manuscript of an article that has been published in its final definitive form by Institute of Electrical and Electronics Engineers Inc., 2017.

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Abstract

© 2017 IEEE. Spatial diversity is an effective method to mitigate the effects of fading, and when used in conjunction with low-density parity-check (LDPC) codes, it can achieve excellent error-correcting performance. Noise added at each branch of the diversity combiner is generally assumed to be additive white Gaussian noise, but there are many applications where the received signal is impaired by noise with a non-Gaussian distribution. In this paper, we derive the exact bit-error probability of different linear combining techniques on Rayleigh fading channels with impulsive noise, which is modeled using symmetric alpha-stable distributions. The relationship for the signal-to-noise ratios of these linear combiners is derived and then different non-linear detectors are presented. A detector based on the biparameter Cauchy-Gaussian mixture model is used and shows near-optimal performance with a significant reduction in complexity when compared with the optimal detector. Furthermore, the threshold signal-to-noise ratio of LDPC codes for different combining techniques on these channels is derived using density evolution and an estimation of the waterfall performance of LDPC codes is derived that reduces the gap between simulated and asymptotic performance.


Publication metadata

Author(s): Mei Z, Johnston M, Le Goff S, Chen L

Publication type: Article

Publication status: Published

Journal: IEEE Transactions on Communications

Year: 2017

Volume: 65

Issue: 6

Pages: 2345-2356

Online publication date: 16/03/2017

Acceptance date: 02/04/2016

Date deposited: 22/08/2017

ISSN (print): 0090-6778

Publisher: Institute of Electrical and Electronics Engineers Inc.

URL: https://doi.org/10.1109/TCOMM.2017.2683485

DOI: 10.1109/TCOMM.2017.2683485


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