Deep Reinforcement Learning for IRS Phase Shift Design in Spatiotemporally Correlated Environments

2 November 2022

Papers citing "Deep Reinforcement Learning for IRS Phase Shift Design in Spatiotemporally Correlated Environments"

8 / 8 papers shown

Title
On the Robustness of Deep Reinforcement Learning in IRS-Aided Wireless Communications Systems Amal Feriani A. Mezghani Ekram Hossain 22 9 0 17 Jul 2021
Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains Matthew Tancik Pratul P. Srinivasan B. Mildenhall Sara Fridovich-Keil N. Raghavan Utkarsh Singhal R. Ramamoorthi Jonathan T. Barron Ren Ng 80 2,384 0 18 Jun 2020
Reconfigurable Intelligent Surface Assisted Multiuser MISO Systems Exploiting Deep Reinforcement Learning Chongwen Huang Ronghong Mo Chau Yuen 22 579 0 24 Feb 2020
Towards Understanding the Spectral Bias of Deep Learning Yuan Cao Zhiying Fang Yue Wu Ding-Xuan Zhou Quanquan Gu 68 217 0 03 Dec 2019
Indoor Signal Focusing with Deep Learning Designed Reconfigurable Intelligent Surfaces Chongwen Huang G. C. Alexandropoulos Chau Yuen Mérouane Debbah 16 232 0 19 May 2019
Towards Characterizing Divergence in Deep Q-Learning Joshua Achiam Ethan Knight Pieter Abbeel 41 96 0 21 Mar 2019
Spatially Controlled Relay Beamforming: $2$ -Stage Optimal Policies Dionysios S. Kalogerias Athina P. Petropulu 16 8 0 21 May 2017
Continuous control with deep reinforcement learning Timothy Lillicrap Jonathan J. Hunt Alexander Pritzel N. Heess Tom Erez Yuval Tassa David Silver Daan Wierstra 148 13,174 0 09 Sep 2015