Intelligent Reflecting Surface Optimization for MIMO Communication Using Deep Reinforcement Learning | IEEE Conference Publication | IEEE Xplore

Intelligent Reflecting Surface Optimization for MIMO Communication Using Deep Reinforcement Learning


Abstract:

This paper focuses on the optimization of the phase shifts of an intelligent reflecting surface (IRS) for an IRS-aided multiple input multiple output (MIMO) communication...Show More

Abstract:

This paper focuses on the optimization of the phase shifts of an intelligent reflecting surface (IRS) for an IRS-aided multiple input multiple output (MIMO) communication system. Motivated by the massive success of deep reinforcement learning (DRL) algorithms in handling high-dimensional continuous action spaces and tackling non-convex optimization problems, we propose a deep deterministic policy gradient (DDPG) framework for solving the formulated non-convex optimization problem. Numerical simulations demonstrate the robustness and efficiency of the proposed model in terms of spectral efficiency and algorithm run time when compared to a state-of-the-art scheme.
Date of Conference: 21-22 November 2023
Date Added to IEEE Xplore: 01 January 2024
ISBN Information:
Conference Location: Belgrade, Serbia

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