First-Order Methods for Energy-Efficient Power Control in Cell-Free Massive MIMO
|Title:||First-Order Methods for Energy-Efficient Power Control in Cell-Free Massive MIMO||Authors:||Tran, Le-Nam; Ngo, Hien Quoc||Permanent link:||http://hdl.handle.net/10197/11911||Date:||6-Nov-2019||Online since:||2021-02-01T17:46:14Z||Abstract:||This paper considers a cell-free massive MIMO system with multiple-antenna access points and single-antenna users. The APs use conjugate beamforming to beamform the data to all users in the network. Total energy efficiency maximization is investigated. This optimization problem is nonconvex and thus difficult to solve. Existing solutions are based on second-order optimization methods in connection with convex approximations. These methods have been shown to perform very well but their complexity does not scale favorably with the network size. To tackle this issue, in this paper we propose to use a first-order method for nonconvex programming to our energy efficiency problem. Compared to the second-order methods, the proposed method achieves the same performance, while its run time is much faster. Thus, it is considered as a feasible solution for resource allocation in cell-free massive MIMO systems.||Funding Details:||Science Foundation Ireland||Funding Details:||U.K. Research and Innovation Future Leaders Fellowships||Type of material:||Conference Publication||Publisher:||IEEE||Copyright (published version):||2019 IEEE||Keywords:||Antenna array; Array signal processing; Communication complexity; Concave programming; MIMO communication; Power control||DOI:||10.1109/IEEECONF44664.2019.9048924||Other versions:||https://signalprocessingsociety.org/blog/acssc-2019-2019-asilomar-conference-signals-systems-and-computers||Language:||en||Status of Item:||Peer reviewed||Is part of:||Matthews, M. B., and Northrop Grumman Innovation Systems (eds.). Conference Record of The Fifty-Third Asilomar Conference on Signals, Systems and Computers: November 3-6, 2019, Pacific Grove, California||Conference Details:||The 2019 53rd Asilomar Conference on Signals, Systems and Computers, Pacific Grove, California, United States of America, 3-6 November 2019||ISBN:||978-1-7281-4301-9||ISSN:||1058-6393||This item is made available under a Creative Commons License:||https://creativecommons.org/licenses/by-nc-nd/3.0/ie/|
|Appears in Collections:||Electrical and Electronic Engineering Research Collection|
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