University of Oulu

O. Lyons, M. F. Hanif, M. Juntti and L. Tran, "Fast Adaptive Minorization-Maximization Procedure for Beamforming Design of Downlink NOMA Systems," in IEEE Transactions on Vehicular Technology, vol. 69, no. 7, pp. 8023-8027, July 2020, doi: 10.1109/TVT.2020.2993987

Fast adaptive minorization-maximization procedure for beamforming design of downlink NOMA systems

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Author: Lyons, Oisin1; Hanif, Muhammad Fainan2; Juntti, Markku3;
Organizations: 1School of Electrical and Electronic Engineering, University College Dublin, Dublin D04 V1W8, Ireland
2Department of Electrical Engineering, University of Lahore, Lahore 55150, Pakistan
3Centre for Wireless Communications, University of Oulu, 90014 Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.2 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2020
Publish Date: 2020-08-04


We develop a novel technique to accelerate minorization-maximization (MM) procedure for the non-orthogonal multiple access (NOMA) weighted sum rate maximization problem. Specifically, we exploit the Lipschitz continuity of the gradient of the objective function to adaptively update the MM algorithm. With fewer additional analysis variables and low complexity second-order cone program (SOCP) to solve in each iteration of the MM algorithm, the proposed approach converges quickly at a small computational cost. By numerical simulation results, our algorithm is shown to greatly outperform known solutions in terms of achieved sum rates and computational complexity.

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Series: IEEE transactions on vehicular technology
ISSN: 0018-9545
ISSN-E: 1939-9359
ISSN-L: 0018-9545
Volume: 69
Issue: 7
Pages: 8023 - 8027
DOI: 10.1109/TVT.2020.2993987
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
Funding: M. Juntti’s work has been supported in part by 6Genesis Flagship (grant 318927) funded by the Academy of Finland.
Academy of Finland Grant Number: 318927
Detailed Information: 318927 (Academy of Finland Funding decision)
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