Gaussian downlink user selection subject to access limit, power budget, and rate demands

Consider a Gaussian downlink between an access point with power budget P>0, and a set of users specified by their effective noises and rate demands. In order to control the decoding complexity and error propagation, an integer-valued access limit M>0 is imposed on the number of superimposed us...

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Bibliographic Details
Published in:Theoretical computer science Vol. 931; pp. 78 - 92
Main Authors: Liu, Xiang, Zou, Jinyu, Chen, Pengpeng, Wan, Peng-Jun
Format: Journal Article
Language:English
Published: Elsevier B.V 29.09.2022
Subjects:
Access limit
Approximation algorithm
Successive interference cancellation
User selection
User selection
Access limit
Successive interference cancellation
Approximation algorithm
ISSN:0304-3975, 1879-2294
Online Access:Get full text
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Summary:Consider a Gaussian downlink between an access point with power budget P>0, and a set of users specified by their effective noises and rate demands. In order to control the decoding complexity and error propagation, an integer-valued access limit M>0 is imposed on the number of superimposed users. For each subset S of users, its (total) power demand p(S) is a strictly increasing and nonseparable function of the effective noises and rate demands of users in S. A subset S of users is feasible if |S|≤M and p(S)≤P. The goal is to select a feasible subset S of users whose total rate demand is maximized. In this paper, we show that this problem is NP-hard, and present a (1−1/e)-approximation algorithm for this problem. In addition, we also give several other approximation algorithms with trade-offs between accuracy and efficiency. •The Gaussian downlink user selection problem studied in this paper is an NP-hard maximization problem.•The first 12(1−1/e)-approximation algorithm takes the relaxation/extraction approach.•A better algorithm utilizes partial enumeration for reducing the extraction loss, and achieves (1−1/e)-approximation factor.•The paper is concluded with a summary of the general algorithmic framework and some open problems for further studies.
ISSN:0304-3975
1879-2294
DOI:10.1016/j.tcs.2022.07.032