On the Optimality of Gaussian Code-books for Signaling over a Two-Users Weak Gaussian Interference Channel

Fuente: arXiv
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Autor principal: Khandani, Amir K.
Formato: Preprint
Publicado: 2025
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author Khandani, Amir K.
author_facet Khandani, Amir K.
contents This article shows that the capacity region of a two users weak Gaussian interference channel can be achieved using single letter Gaussian code-books. It is shown that the upper concave envelope of the capacity region can be achieved using at most two time-sharing phases. In one phase, both users are active, while in the second phase, if it exists, only a single user is active. It is shown that the boundary of the capacity region can be traversed continuously through incremental reallocation of power between the messages of each user. Finally, it is established that the solution to the Han-Kobayashi achievable rate region, with single letter Gaussian code-books, achieves the optimum boundary.
format Preprint
id arxiv_https___arxiv_org_abs_2501_14941
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle On the Optimality of Gaussian Code-books for Signaling over a Two-Users Weak Gaussian Interference Channel
Khandani, Amir K.
Information Theory
Probability
This article shows that the capacity region of a two users weak Gaussian interference channel can be achieved using single letter Gaussian code-books. It is shown that the upper concave envelope of the capacity region can be achieved using at most two time-sharing phases. In one phase, both users are active, while in the second phase, if it exists, only a single user is active. It is shown that the boundary of the capacity region can be traversed continuously through incremental reallocation of power between the messages of each user. Finally, it is established that the solution to the Han-Kobayashi achievable rate region, with single letter Gaussian code-books, achieves the optimum boundary.
title On the Optimality of Gaussian Code-books for Signaling over a Two-Users Weak Gaussian Interference Channel
topic Information Theory
Probability
url https://arxiv.org/abs/2501.14941