most citedPath Planning for UAV-Mounted Mobile Edge Computing with Deep Reinforcement Learning

9 citations · 12 across the 5 of their papers we have counts for

collaborators

5 papers

cs.IT20221 cited

Performance Analysis of Wireless Network Aided by Discrete-Phase-Shifter IRS

Rongen Dong, Yin Teng, Zhongwen Sun +5

Discrete phase shifters of intelligent reflecting surface (IRS) generates phase quantization error (QE) and degrades the receive performance at the receiver. To make an analysis of…

cs.MA2022

Collaborative Intelligent Reflecting Surface Networks with Multi-Agent Reinforcement Learning

Jie Zhang, Jun Li, Yijin Zhang +5

Intelligent reflecting surface (IRS) is envisioned to be widely applied in future wireless networks. In this paper, we investigate a multi-user communication system assisted by coo…

cs.IT2022

Phase Optimization for Massive IRS-aided Two-way Relay Network

Peng Zhang, Xuehui Wang, Siling Feng +3

In this paper, with the help of an intelligent reflecting surface (IRS), the source (S) and destination (D) exchange information through the two-way decode-and-forward relay (TW-DF…

cs.IT20202 cited

Enhanced Secrecy Rate Maximization for Directional Modulation Networks via IRS

Feng Shu, Jiayu Li, Mengxing Huang +5

Intelligent reflecting surface (IRS) is of low-cost and energy-efficiency and will be a promising technology for the future wireless communications like sixth generation. To addres…

cs.IT20209 cited

Path Planning for UAV-Mounted Mobile Edge Computing with Deep Reinforcement Learning

Q. Liu, L. Shi, L. Sun +3

In this letter, we study an unmanned aerial vehicle (UAV)-mounted mobile edge computing network, where the UAV executes computational tasks offloaded from mobile terminal users (TU…