activity
20172021
most citedLightweight Convolutional Neural Networks for CSI Feedback in Massive MIMO

12 citations · 21 across the 4 of their papers we have counts for

collaborators

8 papers

cs.IT20211 cited

Model-based Learning Network for 3-D Localization in mmWave Communications

Jie Yang, Shi Jin, Chao-Kai Wen +3

This study considers the joint location and velocity estimation of UE and scatterers in a three-dimensional mmWave CRAN architecture. Several existing works have achieved satisfact…

cs.IT202012 cited

Lightweight Convolutional Neural Networks for CSI Feedback in Massive MIMO

Zheng Cao, Wan-Ting Shih, Jiajia Guo +2

In frequency division duplex mode of massive multiple-input multiple-output systems, the downlink channel state information (CSI) must be sent to the base station (BS) through a fe…

cs.IT2019

3-D Positioning and Environment Mapping for mmWave Communication Systems

Jie Yang, Shi Jin, Chao-Kai Wen +2

Millimeter-wave (mmWave) cloud radio access networks (CRANs) provide new opportunities for accurate cooperative localization, in which large bandwidths, large antenna arrays, and i…

cs.IT20194 cited

A Distributed Multi-RF Chain Hybrid mmWave Scheme for Small-cell Systems

Lou Zhao, Jiajia Guo, Zhiqiang Wei +2

This paper proposes a distributed hybrid millimeter wave (mmWave) scheme to exploit the structure of a Densely Deployed Distributed (DDD) small-cell-base-stations (SBSs) system for…

cs.IT2018

Enhancing Cellular Performance through Device-to-Device Distributed MIMO

Jiajia Guo, Wei Yu, Jinhong Yuan

The integration of local device-to-device (D2D) communications and cellular connections has been intensively studied to satisfy co-existing D2D and cellular communication demand. I…

cs.IT2018

Multi-Beam NOMA for Hybrid mmWave Systems

Zhiqiang Wei, Lou Zhao, Jiajia Guo +2

In this paper, we propose a multi-beam non-orthogonal multiple access (NOMA) scheme for hybrid millimeter wave (mmWave) systems and study its resource allocation. A beam splitting…