6 citations · 11 across the 10 of their papers we have counts for
10 papers
DRL-Based Sidelobe Suppression for Multi-focus Reconfigurable Intelligent Surface
Wei Wang, Peizheng Li, Angela Doufexi +1
Reconfigurable intelligent surface (RIS) technology is receiving significant attention as a key enabling technology for 6G communications, with much attention given to coverage inf…
A DRL-based Reflection Enhancement Method for RIS-assisted Multi-receiver Communications
Wei Wang, Peizheng Li, Angela Doufexi +1
In reconfigurable intelligent surface (RIS)-assisted wireless communication systems, the pointing accuracy and intensity of reflections depend crucially on the 'profile,' represent…
Federated Meta-Learning for Traffic Steering in O-RAN
Hakan Erdol, Xiaoyang Wang, Peizheng Li +7
The vision of 5G lies in providing high data rates, low latency (for the aim of near-real-time applications), significantly increased base station capacity, and near-perfect qualit…
Transmit Power Control for Indoor Small Cells: A Method Based on Federated Reinforcement Learning
Peizheng Li, Hakan Erdol, Keith Briggs +7
Setting the transmit power setting of 5G cells has been a long-term topic of discussion, as optimized power settings can help reduce interference and improve the quality of service…
Variational Autoencoder Assisted Neural Network Likelihood RSRP Prediction Model
Peizheng Li, Xiaoyang Wang, Robert Piechocki +3
Measuring customer experience on mobile data is of utmost importance for global mobile operators. The reference signal received power (RSRP) is one of the important indicators for…
Sim2real for Reinforcement Learning Driven Next Generation Networks
Peizheng Li, Jonathan Thomas, Xiaoyang Wang +8
The next generation of networks will actively embrace artificial intelligence (AI) and machine learning (ML) technologies for automation networks and optimal network operation stra…
Bayesian Optimisation-Assisted Neural Network Training Technique for Radio Localisation
Xingchi Liu, Peizheng Li, Ziming Zhu
Radio signal-based (indoor) localisation technique is important for IoT applications such as smart factory and warehouse. Through machine learning, especially neural networks metho…
RLOps: Development Life-cycle of Reinforcement Learning Aided Open RAN
Peizheng Li, Jonathan Thomas, Xiaoyang Wang +8
Radio access network (RAN) technologies continue to evolve, with Open RAN gaining the most recent momentum. In the O-RAN specifications, the RAN intelligent controllers (RICs) are…
Deep Transfer Learning for WiFi Localization
Peizheng Li, Han Cui, Aftab Khan +4
This paper studies a WiFi indoor localisation technique based on using a deep learning model and its transfer strategies. We take CSI packets collected via the WiFi standard channe…
Wireless Localisation in WiFi using Novel Deep Architectures
Peizheng Li, Han Cui, Aftab Khan +4
This paper studies the indoor localisation of WiFi devices based on a commodity chipset and standard channel sounding. First, we present a novel shallow neural network (SNN) in whi…