On the Separability of Parallel Gaussian Interference Channels
Sang Won Choi, Sae-Young Chung
TL;DR
This paper investigates the conditions under which parallel Gaussian interference channels can be separated for optimal communication, extending previous results to more complex two-sided scenarios and identifying when diagonal covariance matrices are optimal.
Contribution
It generalizes separability conditions from one-sided to two-sided PGICs and establishes when diagonal covariance matrices achieve sum-rate optimality.
Findings
Necessary and sufficient conditions for separability in strong TPGICs.
Diagonal covariance matrices are sum-rate optimal for strong and mixed TPGICs.
Extension of separability results to more general two-sided interference channels.
Abstract
The separability in parallel Gaussian interference channels (PGICs) is studied in this paper. We generalize the separability results in one-sided PGICs (OPGICs) by Sung \emph{et al.} to two-sided PGICs (TPGICs). Specifically, for strong and mixed TPGICs, we show necessary and sufficient conditions for the separability. For this, we show diagonal covariance matrices are sum-rate optimal for strong and mixed TPGICs.
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Taxonomy
TopicsAdvanced Wireless Communication Techniques · Blind Source Separation Techniques · Wireless Communication Security Techniques