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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Published in | Theoretical computer science Vol. 931; pp. 78 - 92 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
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Elsevier B.V
29.09.2022
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Abstract | 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. |
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AbstractList | 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. |
Author | Chen, Pengpeng Liu, Xiang Wan, Peng-Jun Zou, Jinyu |
Author_xml | – sequence: 1 givenname: Xiang surname: Liu fullname: Liu, Xiang organization: Dongguan University of Technology, PR China – sequence: 2 givenname: Jinyu surname: Zou fullname: Zou, Jinyu organization: Dongguan University of Technology, PR China – sequence: 3 givenname: Pengpeng surname: Chen fullname: Chen, Pengpeng organization: Illinois Institute of Technology, USA – sequence: 4 givenname: Peng-Jun orcidid: 0000-0001-7926-5711 surname: Wan fullname: Wan, Peng-Jun email: wan@iit.edu organization: Illinois Institute of Technology, USA |
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Cites_doi | 10.1145/321864.321873 10.1109/TSP.2020.2982786 10.1109/TWC.2016.2616310 10.1109/TIT.1974.1055184 10.1007/BF01588971 10.1109/TIT.1973.1054980 10.1016/S0020-0190(99)00031-9 10.1109/TIT.1972.1054727 10.1109/MWC.2005.1421925 |
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Keywords | User selection Access limit Successive interference cancellation Approximation algorithm |
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Snippet | 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... |
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SubjectTerms | Access limit Approximation algorithm Successive interference cancellation User selection |
Title | Gaussian downlink user selection subject to access limit, power budget, and rate demands |
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