Quantum-Inspired Resource Optimization for 6G Networks: A Survey

IF 34.4 1区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS IEEE Communications Surveys and Tutorials Pub Date : 2024-12-18 DOI:10.1109/COMST.2024.3519865
Muhammad Omair Butt;Nazar Waheed;Trung Q. Duong;Waleed Ejaz
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Abstract

The Internet of Things (IoT) drives an exponential surge in computing and communication devices. Consequently, it triggers capacity, coverage, interference, latency, and security issues in the existing communication networks. The forthcoming sixth-generation (6G) networks will address these issues by providing comprehensive solutions. In particular, quantum communication technology can potentially address the challenges of 6G networks. However, its implementation requires substantial infrastructure upgrades. Therefore, the quantum-inspired (QI) techniques offer an intermediate resort due to their ability to utilize the classical communication infrastructure for design and implementation. Hence, we review QI techniques in this survey that address radio resource optimization challenges across various communication aspects, including channel assignment, reconfigurable intelligent surfaces, spectrum sensing, uncrewed aerial vehicle-assisted networks, and related areas. The analysis explores diverse aspects, including objectives, constraints, problem characterization, proposed solutions, and lessons learnt. Research indicates that QI techniques offer advantages such as faster convergence and reduced complexity, providing promising solutions to complex optimization problems in communication networks. Furthermore, we identify the future directions, research gaps, and ongoing challenges from the QI radio resource optimization dataset.
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量子启发的 6G 网络资源优化:调查
物联网(IoT)推动了计算和通信设备的指数级增长。因此,它会引发现有通信网络中的容量、覆盖范围、干扰、延迟和安全问题。即将到来的第六代(6G)网络将通过提供全面的解决方案来解决这些问题。特别是,量子通信技术可以潜在地解决6G网络的挑战。然而,它的实施需要大量的基础设施升级。因此,量子启发(QI)技术提供了一种中间手段,因为它们能够利用经典通信基础设施进行设计和实现。因此,我们在本调查中回顾了QI技术,这些技术解决了各种通信方面的无线电资源优化挑战,包括信道分配、可重构智能表面、频谱传感、无人驾驶飞行器辅助网络和相关领域。分析探讨了不同的方面,包括目标、约束、问题特征、建议的解决方案和吸取的教训。研究表明,QI技术具有更快的收敛速度和降低复杂性等优点,为通信网络中的复杂优化问题提供了有希望的解决方案。此外,我们从QI无线电资源优化数据集确定了未来的方向、研究差距和正在面临的挑战。
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来源期刊
IEEE Communications Surveys and Tutorials
IEEE Communications Surveys and Tutorials COMPUTER SCIENCE, INFORMATION SYSTEMS-TELECOMMUNICATIONS
CiteScore
80.20
自引率
2.50%
发文量
84
审稿时长
6 months
期刊介绍: IEEE Communications Surveys & Tutorials is an online journal published by the IEEE Communications Society for tutorials and surveys covering all aspects of the communications field. Telecommunications technology is progressing at a rapid pace, and the IEEE Communications Society is committed to providing researchers and other professionals the information and tools to stay abreast. IEEE Communications Surveys and Tutorials focuses on integrating and adding understanding to the existing literature on communications, putting results in context. Whether searching for in-depth information about a familiar area or an introduction into a new area, IEEE Communications Surveys & Tutorials aims to be the premier source of peer-reviewed, comprehensive tutorials and surveys, and pointers to further sources. IEEE Communications Surveys & Tutorials publishes only articles exclusively written for IEEE Communications Surveys & Tutorials and go through a rigorous review process before their publication in the quarterly issues. A tutorial article in the IEEE Communications Surveys & Tutorials should be designed to help the reader to become familiar with and learn something specific about a chosen topic. In contrast, the term survey, as applied here, is defined to mean a survey of the literature. A survey article in IEEE Communications Surveys & Tutorials should provide a comprehensive review of developments in a selected area, covering its development from its inception to its current state and beyond, and illustrating its development through liberal citations from the literature. Both tutorials and surveys should be tutorial in nature and should be written in a style comprehensible to readers outside the specialty of the article.
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