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SINR-Aware Deep Reinforcement Learning for Distributed Dynamic Channel Allocation in Cognitive Interference Networks
Feb. 29, 2024, 5:42 a.m. | Yaniv Cohen, Tomer Gafni, Ronen Greenberg, Kobi Cohen
cs.LG updates on arXiv.org arxiv.org
Abstract: We consider the problem of dynamic channel allocation (DCA) in cognitive communication networks with the goal of maximizing a global signal-to-interference-plus-noise ratio (SINR) measure under a specified target quality of service (QoS)-SINR for each network. The shared bandwidth is partitioned into K channels with frequency separation. In contrast to the majority of existing studies that assume perfect orthogonality or a one- to-one user-channel allocation mapping, this paper focuses on real-world systems experiencing inter-carrier interference (ICI) …
abstract arxiv bandwidth cognitive communication cs.lg distributed dynamic eess.sp global interference network networks noise quality reinforcement reinforcement learning service signal type
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