Enhancing beamforming performance in 6G-V2X base stations using meta-deep reinforcement Q-learning

IF 7.1 3区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Internet of Things Pub Date : 2026-01-01 Epub Date: 2025-11-14 DOI:10.1016/j.iot.2025.101825

Ali Belgacem , Abbas Bradai

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Abstract

Beamforming plays a crucial role in base stations, particularly with the integration of Vehicle-to-Everything (V2X), Artificial Intelligence (AI), and massive Multiple Input Multiple Output (MIMO) technologies in 6G networks. It significantly enhances network performance by accurately tracking vehicles. However, achieving effective beamforming in dynamic environments with moving vehicles while maintaining high performance at base stations remains challenging. This paper presents a novel approach using meta-deep reinforcement Q-learning (Meta-DRQL) to develop a beamforming model that narrows beamwidth and improves system performance. The model dynamically adjusts key parameters for optimal beamforming. Simulation results demonstrate notable improvements in beamwidth efficiency and energy consumption, highlighting the model’s potential for V2X communications and 6G MIMO systems. These advancements contribute to the creation of more reliable, high-capacity networks for connected vehicles and smart infrastructure.

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利用元深度强化q学习增强6G-V2X基站的波束成形性能

波束成形在基站中起着至关重要的作用，特别是在6G网络中集成了车联网（V2X）、人工智能（AI）和大规模多输入多输出（MIMO）技术。它通过精确跟踪车辆显著提高了网络性能。然而，在移动车辆的动态环境中实现有效的波束形成，同时保持基站的高性能仍然具有挑战性。本文提出了一种利用元深度强化q -学习（Meta-DRQL）开发波束形成模型的新方法，该模型可以缩小波束宽度并提高系统性能。该模型动态调整波束形成的关键参数。仿真结果表明，该模型在波束宽度效率和能耗方面有显著改善，突出了该模型在V2X通信和6G MIMO系统中的潜力。这些进步有助于为互联汽车和智能基础设施创建更可靠、更大容量的网络。

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

Internet of Things Multiple-

CiteScore

3.60

自引率

5.10%

发文量

115

审稿时长

37 days

期刊介绍： Internet of Things; Engineering Cyber Physical Human Systems is a comprehensive journal encouraging cross collaboration between researchers, engineers and practitioners in the field of IoT & Cyber Physical Human Systems. The journal offers a unique platform to exchange scientific information on the entire breadth of technology, science, and societal applications of the IoT. The journal will place a high priority on timely publication, and provide a home for high quality. Furthermore, IOT is interested in publishing topical Special Issues on any aspect of IOT.