IEEE Wireless Communications · 2021 · 23 citations · 6 references
EngineeringCommunicationElectrical EngineeringDigital CommunicationMobile SystemsWireless CommunicationsInterference ManagementMobile CommunicationWireless Channel ModelingWireless Communication ProtocolsWireless NetworksCellular Interference ManagementCo-channel InterferenceDesign RationalesInter-cell InterferenceInterference CoordinationInterference MitigationLow-latency CommunicationUltra-reliable Low-latency Communication
This article presents enhancements that further improve the performance of 5G New Radio time division duplex (TDD) operation and performance. The focus is on mechanisms to mitigate co-channel cross link interference (CLI) between neighboring cells, providing pointers also to recent advances in remote interference mitigation between cells separated by tens to hundreds of kilometers. A sophisticated framework where User Equipment's (UEs) are used as sensors detecting CLI problems is outlined, and the underlying design rationales are presented. Solutions for simple coordination of TDD radio frame configurations between network elements are described. Solutions based on simple reinforcement learning algorithms for the network to adjust the TDD radio frame configuration are proposed, and validated for both macro and indoor factory deployments, considering both ultra-reliable low latency communication (URLLC) and enhanced mobile broadband (eMBB) traffic. Results from extensive dynamic system-level simulations confirm that such solutions offer attractive benefits.
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Reinforcement Learning: An Introduction
Richard S. Sutton, Andy Barto · IEEE Transactions on Neural Networks · 1998 · 27.1K citations