# Performance Analysis of DF Cooperative Relaying over Bursty Impulsive   Noise Channel

**Authors:** Md Sahabul Alam, Fabrice Labeau, Georges Kaddoum

arXiv: 1903.00495 · 2019-03-05

## TL;DR

This paper analyzes the performance of decode-and-forward cooperative relaying over channels with bursty impulsive noise modeled by a two-state Markov-Gaussian process, demonstrating significant improvements over direct transmission and conventional receivers.

## Contribution

It introduces a Markov-Gaussian noise model for bursty impulsive noise and evaluates the BER performance of DF relaying with a MAP receiver under this model.

## Key findings

- DF relaying achieves space diversity gains in bursty impulsive noise.
- The MAP receiver approaches the theoretical lower bound, outperforming conventional methods.
- DF scheme outperforms direct transmission under the same power conditions.

## Abstract

In this article, we consider the performance analysis of a decode-and-forward (DF) cooperative relaying (CR) scheme over channels impaired by bursty impulsive noise. Although, Middleton class-A model and Bernoulli-Gaussian model give good results to generate a sample distribution of impulsive noise, they fail in replicating the bursty behavior of impulsive noise, as encountered for instance within power substations. To deal with that, we adopt a two-state Markov-Gaussian process for the noise distribution. For this channel, we evaluate the bit error rate (BER) performance of direct transmission (DT) and a DF relaying scheme using M-ary phase shift keying (M-PSK) modulation in the presence of Rayleigh fading with a maximum a posteriori (MAP) receiver. From the obtained results, it is seen that the DF CR scheme in bursty impulsive noise channel still achieves the space diversity and performs significantly better than DT under the same power consumption. Moreover, the proposed MAP receiver attains the lower bound derived for DF CR scheme, and leads to large performance gains compared to the conventional receiving criteria which were optimized for additive white Gaussian noise (AWGN) channel and memoryless impulsive noise channel.

## Full text

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## Figures

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## References

36 references — full list in the complete paper: https://tomesphere.com/paper/1903.00495/full.md

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Source: https://tomesphere.com/paper/1903.00495