214 citations · 317 across the 15 of their papers we have counts for
16 papers
VoI-Driven Joint Optimization of Control and Communication in Vehicular Digital Twin Network
Lei Lei, Kan Zheng, Jie Mei +2
The vision of sixth-generation (6G) wireless networks paves the way for the seamless integration of digital twins into vehicular networks, giving rise to a Vehicular Digital Twin N…
Learning Value of Information towards Joint Communication and Control in 6G V2X
Lei Lei, Kan Zheng, Xuemin +1
As Cellular Vehicle-to-Everything (C-V2X) evolves towards future sixth-generation (6G) networks, Connected Autonomous Vehicles (CAVs) are emerging to become a key application. Leve…
Ambient IoT towards 6G: Standardization, Potentials, and Challenges
Kan Zheng, Rongtao Xu, Jie Mei +3
The Ambient Internet of Things (A-IoT) has emerged as a critical direction for achieving effective connectivity as the IoT system evolves to 6G. However, the introduction of A-IoT…
Multi-Timescale Control and Communications with Deep Reinforcement Learning -- Part I: Communication-Aware Vehicle Control
Tong Liu, Lei Lei, Kan Zheng +2
An intelligent decision-making system enabled by Vehicle-to-Everything (V2X) communications is essential to achieve safe and efficient autonomous driving (AD), where two types of d…
Multi-Timescale Control and Communications with Deep Reinforcement Learning -- Part II: Control-Aware Radio Resource Allocation
Lei Lei, Tong Liu, Kan Zheng +2
In Part I of this two-part paper (Multi-Timescale Control and Communications with Deep Reinforcement Learning -- Part I: Communication-Aware Vehicle Control), we decomposed the mul…
Optimal Scheduling in IoT-Driven Smart Isolated Microgrids Based on Deep Reinforcement Learning
Jiaju Qi, Lei Lei, Kan Zheng +3
In this paper, we investigate the scheduling issue of diesel generators (DGs) in an Internet of Things (IoT)-Driven isolated microgrid (MG) by deep reinforcement learning (DRL). Th…
Autonomous Platoon Control with Integrated Deep Reinforcement Learning and Dynamic Programming
Tong Liu, Lei Lei, Kan Zheng +1
Deep Reinforcement Learning (DRL) is regarded as a potential method for car-following control and has been mostly studied to support a single following vehicle. However, it is more…
Joint Energy Dispatch and Unit Commitment in Microgrids Based on Deep Reinforcement Learning
Jiaju Qi, Lei Lei, Kan Zheng +1
Nowadays, the application of microgrids (MG) with renewable energy is becoming more and more extensive, which creates a strong need for dynamic energy management. In this paper, de…
Deep Reinforcement Learning Aided Platoon Control Relying on V2X Information
Lei Lei, Tong Liu, Kan Zheng +1
The impact of Vehicle-to-Everything (V2X) communications on platoon control performance is investigated. Platoon control is essentially a sequential stochastic decision problem (SS…
Federated Reinforcement Learning: Techniques, Applications, and Open Challenges
Jiaju Qi, Qihao Zhou, Lei Lei +1
This paper presents a comprehensive survey of Federated Reinforcement Learning (FRL), an emerging and promising field in Reinforcement Learning (RL). Starting with a tutorial of Fe…
Performance Modeling and Analysis of a Hyperledger-based System Using GSPN
Pu Yuan, Kan Zheng, Xiong Xiong +2
As a highly scalable permissioned blockchain platform, Hyperledger Fabric supports a wide range of industry use cases ranging from governance to finance. In this paper, we propose…
Dynamic Energy Dispatch Based on Deep Reinforcement Learning in IoT-Driven Smart Isolated Microgrids
Lei Lei, Yue Tan, Glenn Dahlenburg +2
Microgrids (MGs) are small, local power grids that can operate independently from the larger utility grid. Combined with the Internet of Things (IoT), a smart MG can leverage the s…
Deep Reinforcement Learning for Autonomous Internet of Things: Model, Applications and Challenges
Lei Lei, Yue Tan, Kan Zheng +4
The Internet of Things (IoT) extends the Internet connectivity into billions of IoT devices around the world, where the IoT devices collect and share information to reflect status…
Multi-user Resource Control with Deep Reinforcement Learning in IoT Edge Computing
Lei Lei, Huijuan Xu, Xiong Xiong +3
By leveraging the concept of mobile edge computing (MEC), massive amount of data generated by a large number of Internet of Things (IoT) devices could be offloaded to MEC server at…
Patent Analytics Based on Feature Vector Space Model: A Case of IoT
Lei Lei, Jiaju Qi, Kan Zheng
The number of approved patents worldwide increases rapidly each year, which requires new patent analytics to efficiently mine the valuable information attached to these patents. Ve…
An In-Vehicle KWS System with Multi-Source Fusion for Vehicle Applications
Yue Tan, Kan Zheng, Lei Lei
In order to maximize detection precision rate as well as the recall rate, this paper proposes an in-vehicle multi-source fusion scheme in Keyword Spotting (KWS) System for vehicle…