Joint Power Allocation and Hybrid Beamforming of mmWave NOMA Systems Using DDPG

IF 3.7 3区计算机科学 Q2 TELECOMMUNICATIONS IEEE Communications Letters Pub Date : 2024-09-10 DOI:10.1109/LCOMM.2024.3457166

Alireza Soofinezhadmoghaddam;Hamidreza Bakhshi

引用次数: 0

Abstract

Joint Hybrid Beamforming (HBF) and Power Allocation (PA) in mmWave nonorthogonal multiple access (NOMA) systems are investigated in this letter. We consider downlink mmWave NOMA systems, in which HBF is done at the Base Station (BS), and all users have only one antenna. At the BS, user grouping uses the K-means-based algorithm according to the user’s channel correlation. Subsequently, inspired by the benefits of Deep Reinforcement Learning (DRL), a novel algorithm based on DRL is proposed to output the HBF matrix and PA of all the users. Simulations represent the superiority of the proposed algorithm in comparison with the state-of-the-art schemes in both perfect Channel State Information (CSI) and imperfect CSI.

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使用 DDPG 实现毫米波 NOMA 系统的联合功率分配和混合波束成形

本文研究了毫米波非正交多址（NOMA）系统中的混合波束成形（HBF）和功率分配（PA）联合技术。我们考虑了下行毫米波非正交多址接入系统，其中混合波束成形在基站（BS）完成，所有用户只有一个天线。在基站，根据用户的信道相关性使用基于 K-means 的算法对用户进行分组。随后，受深度强化学习（DRL）优点的启发，提出了一种基于 DRL 的新型算法，以输出所有用户的 HBF 矩阵和 PA。模拟结果表明，在完美信道状态信息（CSI）和不完美信道状态信息（CSI）两种情况下，所提出的算法与最先进的方案相比都更具优势。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Communications Letters 工程技术-电信学

CiteScore

8.10

自引率

7.30%

发文量

590

审稿时长

2.8 months

期刊介绍： The IEEE Communications Letters publishes short papers in a rapid publication cycle on advances in the state-of-the-art of communication over different media and channels including wire, underground, waveguide, optical fiber, and storage channels. Both theoretical contributions (including new techniques, concepts, and analyses) and practical contributions (including system experiments and prototypes, and new applications) are encouraged. This journal focuses on the physical layer and the link layer of communication systems.

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