430 citations · 442 across the 6 of their papers we have counts for
6 papers
Compressive Sensing-Based Grant-Free Massive Access for 6G Massive Communication
Zhen Gao, Malong Ke, Yikun Mei +4
The advent of the sixth-generation (6G) of wireless communications has given rise to the necessity to connect vast quantities of heterogeneous wireless devices, which requires adva…
Next-Generation URLLC with Massive Devices: A Unified Semi-Blind Detection Framework for Sourced and Unsourced Random Access
Malong Ke, Zhen Gao, Mingyu Zhou +3
This paper proposes a unified semi-blind detection framework for sourced and unsourced random access (RA), which enables next-generation ultra-reliable low-latency communications (…
An Edge Computing Paradigm for Massive IoT Connectivity over High-Altitude Platform Networks
Malong Ke, Zhen Gao, Yang Huang +4
With the advent of the Internet-of-Things (IoT) era, the ever-increasing number of devices and emerging applications have triggered the need for ubiquitous connectivity and more ef…
Massive Access in Cell-Free Massive MIMO-Based Internet of Things: Cloud Computing and Edge Computing Paradigms
Malong Ke, Zhen Gao, Yongpeng Wu +2
This paper studies massive access in cell-free massive multi-input multi-output (MIMO) based Internet of Things and solves the challenging active user detection (AUD) and channel e…
Compressive Massive Access for Internet of Things: Cloud Computing or Fog Computing?
Malong Ke, Zhen Gao, Yongpeng Wu
This paper considers the support of grant-free massive access and solves the challenge of active user detection and channel estimation in the case of a massive number of users. By…
Compressive Sensing Based Adaptive Active User Detection and Channel Estimation: Massive Access Meets Massive MIMO
Malong Ke, Zhen Gao, Yongpeng Wu +2
This paper considers massive access in massive multiple-input multiple-output (MIMO) systems and proposes an adaptive active user detection and channel estimation scheme based on c…