ris辅助OFDM通信的对抗强盗方法。

IF 2.3 4区 计算机科学 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Messaoud Ahmed Ouameur, Lê Dương Tuấn Anh, Daniel Massicotte, Gwanggil Jeon, Felipe Augusto Pereira de Figueiredo
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引用次数: 0

摘要

为了帮助第六代无线系统管理各种各样的服务,从关键任务到安全关键任务,提出了关键物理层技术,如可重构智能表面(RISs)。尽管RISs已经在各种场景中用于实现智能无线电环境,但它们仍然面临着实时操作方面的挑战。具体来说,高维全无源RISs通常需要昂贵的系统开销来进行信道估计。然而,本文研究了一种半被动RIS,它需要非常少的有源元素,其中每个通道相干时间只需要两个导频。虽然深度学习(DL)工具的应用还处于起步阶段,但它有望实现可行的解决方案。与基于dl的反射波束形成参考方法相比,我们提出了两种低训练开销和节能的基于对抗性强盗的方案,具有突出的性能提升。使用最先进的模型质量预测趋势讨论了所得到的深度学习模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Adversarial bandit approach for RIS-aided OFDM communication.

Adversarial bandit approach for RIS-aided OFDM communication.

Adversarial bandit approach for RIS-aided OFDM communication.

Adversarial bandit approach for RIS-aided OFDM communication.

To assist sixth-generation wireless systems in the management of a wide variety of services, ranging from mission-critical services to safety-critical tasks, key physical layer technologies such as reconfigurable intelligent surfaces (RISs) are proposed. Even though RISs are already used in various scenarios to enable the implementation of smart radio environments, they still face challenges with regard to real-time operation. Specifically, high dimensional fully passive RISs typically need costly system overhead for channel estimation. This paper, however, investigates a semi-passive RIS that requires a very low number of active elements, wherein only two pilots are required per channel coherence time. While in its infant stage, the application of deep learning (DL) tools shows promise in enabling feasible solutions. We propose two low-training overhead and energy-efficient adversarial bandit-based schemes with outstanding performance gains when compared to DL-based reflection beamforming reference methods. The resulting deep learning models are discussed using state-of-the-art model quality prediction trends.

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来源期刊
CiteScore
7.70
自引率
3.80%
发文量
109
审稿时长
8.0 months
期刊介绍: The overall aim of the EURASIP Journal on Wireless Communications and Networking (EURASIP JWCN) is to bring together science and applications of wireless communications and networking technologies with emphasis on signal processing techniques and tools. It is directed at both practicing engineers and academic researchers. EURASIP Journal on Wireless Communications and Networking will highlight the continued growth and new challenges in wireless technology, for both application development and basic research. Articles should emphasize original results relating to the theory and/or applications of wireless communications and networking. Review articles, especially those emphasizing multidisciplinary views of communications and networking, are also welcome. EURASIP Journal on Wireless Communications and Networking employs a paperless, electronic submission and evaluation system to promote a rapid turnaround in the peer-review process. The journal is an Open Access journal since 2004.
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