6 citations · 11 across the 4 of their papers we have counts for
5 papers
A General Deep Reinforcement Learning Framework for Grant-Free NOMA Optimization in mURLLC
Yan Liu, Yansha Deng, Hui Zhou +2
Grant-free non-orthogonal multiple access (GF-NOMA) is a potential technique to support massive Ultra-Reliable and Low-Latency Communication (mURLLC) service. However, the dynamic…
RACH in Self-Powered NB-IoT Networks: Energy Availability and Performance Evaluation
Yan Liu, Yansha Deng, Maged Elkashlan +3
NarrowBand-Internet of Things (NB-IoT) is a new 3GPP radio access technology designed to provide better coverage for a massive number of low-throughput low-cost devices in delay-to…
Analysis of Random Access in NB-IoT Networks with Three Coverage Enhancement Groups: A Stochastic Geometry Approach
Yan Liu, Yansha Deng, Nan Jiang +2
NarrowBand-Internet of Things (NB-IoT) is a new 3GPP radio access technology designed to provide better coverage for Low Power Wide Area (LPWA) networks. To provide reliable connec…
Deep Reinforcement Learning-Based Beam Tracking for Low-Latency Services in Vehicular Networks
Yan Liu, Zhiyuan Jiang, Shunqing Zhang +1
Ultra-Reliable and Low-Latency Communications (URLLC) services in vehicular networks on millimeter-wave bands present a significant challenge, considering the necessity of constant…
Analyzing Grant-Free Access for URLLC Service
Yan Liu, Yansha Deng, Maged Elkashlan +2
5G New Radio (NR) is expected to support new ultra-reliable low-latency communication (URLLC) service targeting at supporting the small packets transmissions with very stringent la…