Study of Gaussian Relay Channels with Correlated Noises
Lili Zhang, Jinhua Jiang, Andrea J. Goldsmith, Shuguang Cui

TL;DR
This paper analyzes Gaussian relay channels with correlated noises, deriving capacity bounds, comparing relay schemes, and optimizing power allocation, revealing how noise correlation affects scheme performance and resource use.
Contribution
It provides new capacity results for correlated noise relay channels, compares existing schemes under noise correlation, and derives optimal power allocation strategies.
Findings
DF ignores noise correlation, while CF and AF can exploit it.
Achievable rates for CF and AF decrease with negative correlation.
Optimal power allocation is derived for different power constraints.
Abstract
In this paper, we consider full-duplex and half-duplex Gaussian relay channels where the noises at the relay and destination are arbitrarily correlated. We first derive the capacity upper bound and the achievable rates with three existing schemes: Decode-and-Forward (DF), Compress-and-Forward (CF), and Amplify-and-Forward (AF). We present two capacity results under specific noise correlation coefficients, one being achieved by DF and the other being achieved by direct link transmission (or a special case of CF). The channel for the former capacity result is equivalent to the traditional Gaussian degraded relay channel and the latter corresponds to the Gaussian reversely-degraded relay channel. For CF and AF schemes, we show that their achievable rates are strictly decreasing functions over the negative correlation coefficient. Through numerical comparisons under different channel…
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