Intelligent Radio: When Artificial Intelligence Meets the Radio Network

Tao Chen, Hsiao-Hwa Chen, Zheng Chang, S. Mao
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引用次数: 1

Abstract

The articles in this special section provide a comprehensive overview on the recent development of the intelligent radio. The advances in wireless communications have continuously been pushing the limit of radio technologies. Nowadays, radio networks can provide extremely high data rate, ultra-low latency, and high reliability to serve communication needs of sectors that could not be imagined before. However, radio technologies have become highly complex and call for new solutions. The recent advances in artificial intelligence (AI), including machine learning (ML), data mining, and big data analysis, bring significant promise for addressing hard problems in radio networks. It has been the increasing trend to move the intelligence beyond the spectrum access, which is primarily targeted by cognitive radio, to address various challenges in radio networks, including, but not limited to, channel modeling, modulation, beamforming, radio resource allocation, and network management. Radio technologies are on the way evolving to the intelligent radio, in which AI/ML frameworks and algorithms are applied to learn from environments and explore hidden characteristics of networks for new capacity, performance, and services. We believe the intelligent radio will be the prominent feature of next generation wireless networks. It calls for interdisciplinary research to integrate the advances in AI/ML, communications, computing, and cloud technologies. Both theoretical and applied breakthroughs are expected in this new area.
智能无线电:当人工智能遇上无线网络
本专题的文章全面概述了智能无线电的最新发展。无线通信的进步不断推动着无线电技术的发展。如今,无线网络可以提供极高的数据速率、超低延迟和高可靠性,以满足以前无法想象的行业通信需求。然而,无线电技术已经变得高度复杂,需要新的解决方案。人工智能(AI)的最新进展,包括机器学习(ML)、数据挖掘和大数据分析,为解决无线网络中的难题带来了重大希望。认知无线电的主要目标是将智能转移到频谱接入之外,以解决无线电网络中的各种挑战,包括但不限于信道建模、调制、波束形成、无线电资源分配和网络管理,这已经成为日益增长的趋势。无线电技术正在向智能无线电发展,其中AI/ML框架和算法被应用于从环境中学习,并探索网络的隐藏特征,以获得新的容量、性能和服务。我们相信智能无线电将是下一代无线网络的突出特征。它呼吁跨学科研究,以整合人工智能/机器学习、通信、计算和云技术的进步。这一新领域有望在理论和应用上取得突破。
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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