91 citations · 103 across the 8 of their papers we have counts for
8 papers
Exploiting Tensor-based Bayesian Learning for Massive Grant-Free Random Access in LEO Satellite Internet of Things
Ming Ying, Xiaoming Chen, Xiaodan Shao
With the rapid development of Internet of Things (IoT), low earth orbit (LEO) satellite IoT is expected to provide low power, massive connectivity and wide coverage IoT application…
Exploiting Simultaneous Low-Rank and Sparsity in Delay-Angular Domain for Millimeter-Wave/Terahertz Wideband Massive Access
Xiaodan Shao, Xiaoming Chen, Caijun Zhong +1
Millimeter-wave (mmW)/Terahertz (THz) wideband communication employing a large-scale antenna array is a promising technique of the sixth-generation (6G) wireless network for realiz…
A Bayesian Tensor Approach to Enable RIS for 6G Massive Unsourced Random Access
Xiaodan Shao, Lei Cheng, Xiaoming Chen +2
This paper investigates the problem of joint massive devices separation and channel estimation for a reconfigurable intelligent surface (RIS)-aided unsourced random access (URA) sc…
Feature-Aided Adaptive-Tuning Deep Learning for Massive Device Detection
Xiaodan Shao, Xiaoming Chen, Yiyang Qiang +2
With the increasing development of Internet of Things (IoT), the upcoming sixth-generation (6G) wireless network is required to support grant-free random access of a massive number…
Cooperative Activity Detection: Sourced and Unsourced Massive Random Access Paradigms
Xiaodan Shao, Xiaoming Chen, Derrick Wing Kwan Ng +2
This paper investigates the issue of cooperative activity detection for grant-free random access in the sixth-generation (6G) cell-free wireless networks with sourced and unsourced…
Covariance-Based Cooperative Activity Detection for Massive Grant-Free Random Access
Xiaodan Shao, Xiaoming Chen, Derrick Wing Kwan Ng +2
This paper designs a cooperative activity detection framework for massive grant-free random access in the sixth-generation (6G) cell-free wireless networks based on the covariance…