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Deep Reinforcement Learning-Based Intelligent Reflecting Surface Optimization for TDD Multi-User MIMO Systems
- Source :
- IEEE Wireless Communications Letters; November 2023, Vol. 12 Issue: 11 p1951-1955, 5p
- Publication Year :
- 2023
-
Abstract
- In this letter, we investigate the discrete phase shift design of the intelligent reflecting surface (IRS) in a time-division duplexing (TDD) multi-user multiple-input-multiple-output (MIMO) system. We modify the design of deep reinforcement learning (DRL) scheme so that we can maximizing the average downlink data transmission rate free from the sub-channel channel state information (CSI). Based on the characteristics of the model, we modify the “proximal policy optimization (PPO)” algorithm and integrate gated recurrent unit (GRU) to tackle the non-convex optimization problem. Simulation results show that the performance of the proposed PPO-GRU surpasses the benchmarks in terms of performance, convergence speed, and training stability.
Details
- Language :
- English
- ISSN :
- 21622337 and 21622345
- Volume :
- 12
- Issue :
- 11
- Database :
- Supplemental Index
- Journal :
- IEEE Wireless Communications Letters
- Publication Type :
- Periodical
- Accession number :
- ejs64455761
- Full Text :
- https://doi.org/10.1109/LWC.2023.3301496