Gaussian downlink user selection subject to access limit, power budget, and rate demands - Liu, Xiang; Zou, Jinyu; Chen, Pengpeng; Wan, Peng-Jun (Theoretical computer science, 2022)
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.