License-assisted access (LAA) to unlicensed spectrum is a potential solution to improve the resource availability and system scalability of 5G/ B5G networks. Challenges arise from coexistence between LAA and incumbent systems, especially the ubiquitous IEEE 802.11 WiFi systems. This article demonstrates that the coexistence can be substantially improved by leveraging learning-based clustering of small base stations (SBSs), referred to as learning-assisted clustered access (LACA), and improving the interoperability between licensed and unlicensed access. Fast signaling and a centralized control plane of licensed access can facilitate clustering SBSs for coordinated access to the unlicensed spectrum, hence reducing the number of parties contending for access and alleviating contention. Appropriate clustering of SBSs is important to the efficiency of LACA in 5G/B5G networks. LACA can quickly converge with strong locality, facilitating the coordination of the SBSs, for example, cooperatively connecting multiple users and conducting beamforming. Analytic evaluation and numerical tests confirm the improved coexistence through enlarged LAA-WiFi capacity regions, as well as reduced transmission delays.

中文翻译：

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5G / B5G网络的学习辅助群集访问无执照频谱

对无执照频谱进行许可辅助访问（LAA）是提高5G / B5G网络资源可用性和系统可扩展性的潜在解决方案。挑战来自LAA与现有系统（尤其是无处不在的IEEE 802.11 WiFi系统）之间的共存。本文证明，通过利用基于学习的小型基站（SBS）的群集（称为学习辅助群集访问（LACA））并改善许可访问与非许可访问之间的互操作性，可以大大改善共存。快速信令和许可访问的集中控制平面可以促进群集SBS，以便对非许可频谱进行协调访问，因此减少了争夺访问的参与者数量并减轻了竞争。SBS的适当群集对于5G / B5G网络中LACA的效率至关重要。LACA可以在很强的局域范围内快速收敛，从而促进SBS的协调，例如，协作连接多个用户并进行波束成形。分析评估和数值测试证实了通过扩大LAA-WiFi容量区域改善的共存性以及减少的传输延迟。