activity
20172020
most citedDeep Denoising Neural Network Assisted Compressive Channel Estimation for mmWave Intelligent Reflecting Surfaces

17 citations · 27 across the 3 of their papers we have counts for

collaborators

5 papers

cs.IT202017 cited

Deep Denoising Neural Network Assisted Compressive Channel Estimation for mmWave Intelligent Reflecting Surfaces

Shicong Liu, Zhen Gao, Jun Zhang +2

Integrating large intelligent reflecting surfaces (IRS) into millimeter-wave (mmWave) massive multi-input-multi-ouput (MIMO) has been a promising approach for improved coverage and…

eess.SP20207 cited

Millimeter-Wave Full-Duplex UAV Relay: Joint Positioning, Beamforming, and Power Control

Lipeng Zhu, Jun Zhang, Zhenyu Xiao +3

In this paper, a full-duplex unmanned aerial vehicle (FD-UAV) relay is employed to increase the communication capacity of millimeter-wave (mmWave) networks. Large antenna arrays ar…

cs.IT2020

Compressive Sensing Based Massive Access for IoT Relying on Media Modulation Aided Machine Type Communications

Li Qiao, Jun Zhang, Zhen Gao +2

A fundamental challenge of the large-scale Internet-of-Things lies in how to support massive machine-type communications (mMTC). This letter proposes a media modulation based mMTC…

eess.SP2019

Millimeter-Wave NOMA with User Grouping, Power Allocation and Hybrid Beamforming

Lipeng Zhu, Jun Zhang, Zhenyu Xiao +3

This paper investigates the application of non-orthogonal multiple access in millimeter-Wave communications (mmWave-NOMA). Particularly, we consider downlink transmission with a hy…

cs.IT20173 cited

Joint Power Control and Beamforming for Uplink Non-Orthogonal Multiple Access in 5G Millimeter-Wave Communications

Lipeng Zhu, Jun Zhang, Zhenyu Xiao +3

In this paper, we investigate the combination of two key enabling technologies for the fifth generation (5G) wireless mobile communication, namely millimeter-wave (mmWave) communic…