Low-Coupling Policy Optimization Framework for Power Allocation in Ultra-Dense Small-Cell Networks
Haibo Chen,
Xiao Liu,
Zhongwei Huang
et al.
Abstract:Deep reinforcement learning (DRL) methods have emerged as a feasible solution for addressing the power resource allocation problem in ultra-dense small-cell networks (UDSCNs). In this paper, we propose a novel actor-critic-based low-coupling policy optimization (LCPO) framework. Our framework aims to achieve practicality by employing a design that consists of training and execution modules with low coupling. By adopting policy optimization methods, including advantage actor-critic (A2C) and proximal policy opt… Show more
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