39 citations · 145 across the 43 of their papers we have counts for
59 papers
Low-overhead Beam Training Scheme for Extremely Large-Scale RIS in Near-field
Wang Liu, Cunhua Pan, Hong Ren +3
Extremely large-scale reconfigurable intelligent surface (XL-RIS) has recently been proposed and is recognized as a promising technology that can further enhance the capacity of co…
Enhanced Secure Wireless Transmission Using IRS-aided Directional Modulation
Yeqing Lin, Rongen Dong, Peng Zhang +2
As an excellent aided communication tool, intelligent reflecting surface (IRS) can make a significant rate enhancement and coverage extension. In this paper, we present an investig…
Deep Learning Based Beam Training for Extremely Large-Scale Massive MIMO in Near-Field Domain
Wang Liu, Hong Ren, Cunhua Pan +1
Extremely large-scale massive multiple-input-multiple-output (XL-MIMO) is regarded as a promising technology for next-generation communication systems. In order to enhance the beam…
Deep Learning Based DOA Estimation for Hybrid Massive MIMO Receive Array with Overlapped Subarrays
Yifan Li, Baihua Shi, Feng Shu +2
To improve the accuracy of direction-of-arrival (DOA) estimation, a deep learning (DL)-based method called CDAE-DNN is proposed for hybrid analog and digital (HAD) massive MIMO rec…
Active Reconfigurable Intelligent Surface for Mobile Edge Computing
Zhangjie Peng, Ruisong Weng, Zhenkun Zhang +2
This paper investigates an active reconfigurable intelligent surface (RIS)-aided mobile edge computing (MEC) system. Compared with passive RIS, the active RIS is equipped with acti…
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…