activity
20172021
most citedJoint Resource Management for MC-NOMA: A Deep Reinforcement Learning Approach

56 citations · 61 across the 4 of their papers we have counts for

collaborators

5 papers

cs.AI202156 cited

Joint Resource Management for MC-NOMA: A Deep Reinforcement Learning Approach

Shaoyang Wang, Tiejun Lv, Wei Ni +2

This paper presents a novel and effective deep reinforcement learning (DRL)-based approach to addressing joint resource management (JRM) in a practical multi-carrier non-orthogonal…

eess.SP2020

Frequency-Hopping MIMO Radar-Based Communications: An Overview

Kai Wu, J. Andrew Zhang, Xiaojing Huang +1

Enabled by the advancement in radio frequency technologies, the convergence of radar and communication systems becomes increasingly promising and is envisioned as a key feature of…

eess.SP20205 cited

Integrating Secure and High-Speed Communications into Frequency Hopping MIMO Radar

Kai Wu, J. Andrew Zhang, Xiaojing Huang +1

Dual-function radar-communication (DFRC) based on frequency hopping (FH) MIMO radar (FH-MIMO DFRC) achieves symbol rate much higher than radar pulse repetition frequency. Such DFRC…

cs.NI2019

Framework for a Perceptive Mobile Network using Joint Communication and Radar Sensing

Md. Lushanur Rahman, J. Andrew Zhang, Xiaojing Huang +2

In this paper, we develop a framework for a novel perceptive mobile/cellular network that integrates radar sensing function into the mobile communication network. We propose a unif…

cs.NI2017

Framework for an Innovative Perceptive Mobile Network Using Joint Communication and Sensing

J. Andrew Zhang, Antonio Cantoni, Xiaojing Huang +2

In this paper, we develop a framework for an innovative perceptive mobile (i.e. cellular) network that integrates sensing with communication, and supports new applications widely i…