46 citations · 95 across the 16 of their papers we have counts for
16 papers
Digital Twin Based User-Centric Resource Management for Multicast Short Video Streaming
Xinyu Huang, Wen Wu, Shisheng Hu +3
Multicast short video streaming (MSVS) can effectively reduce network traffic load by delivering identical video sequences to multiple users simultaneously. The existing MSVS schem…
Digital Twin-Assisted Adaptive Preloading for Short Video Streaming
Shengbo Liu, Wen Wu, Shaofeng Li +3
We propose a digital twin-assisted adaptive preloading scheme to enhance bandwidth efficiency and user quality of experience (QoE) in short video streaming. We first analyze the re…
Digital Twin-Assisted Resource Demand Prediction for Multicast Short Video Streaming
Xinyu Huang, Wen Wu, Xuemin Sherman Shen
In this paper, we propose a digital twin (DT)-assisted resource demand prediction scheme to enhance prediction accuracy for multicast short video streaming. Particularly, we constr…
Beef up mmWave Dense Cellular Networks with D2D-Assisted Cooperative Edge Caching
Wen Wu, Ning Zhang, Nan Cheng +4
Edge caching is emerging as the most promising solution to reduce the content retrieval delay and relieve the huge burden on the backhaul links in the ultra-dense networks by proac…
Performance Analysis and Enhancement of Beamforming Training in 802.11ad
Wen Wu, Nan Cheng, Ning Zhang +4
Beamforming (BF) training is crucial to establishing reliable millimeter-wave communication connections between stations (STAs) and an access point. In IEEE 802.11ad BF training pr…
Holistic Network Virtualization and Pervasive Network Intelligence for 6G
Xuemin, Shen, Jie Gao +4
In this tutorial paper, we look into the evolution and prospect of network architecture and propose a novel conceptual architecture for the 6th generation (6G) networks. The propos…
Cost-Effective Two-Stage Network Slicing for Edge-Cloud Orchestrated Vehicular Networks
Wen Wu, Kaige Qu, Peng Yang +4
In this paper, we study a network slicing problem for edge-cloud orchestrated vehicular networks, in which the edge and cloud servers are orchestrated to process computation tasks…
Accuracy-Guaranteed Collaborative DNN Inference in Industrial IoT via Deep Reinforcement Learning
Wen Wu, Peng Yang, Weiting Zhang +3
Collaboration among industrial Internet of Things (IoT) devices and edge networks is essential to support computation-intensive deep neural network (DNN) inference services which r…
Digital Twin-Assisted Collaborative Transcoding for Better User Satisfaction in Live Streaming
Xinyu Huang, Mushu Li, Wen Wu +2
In this paper, we propose a digital twin (DT)-assisted cloud-edge collaborative transcoding scheme to enhance user satisfaction in live streaming. We first present a DT-assisted tr…
Personalized QoE Enhancement for Adaptive Video Streaming: A Digital Twin-Assisted Scheme
Xinyu Huang, Conghao Zhou, Wen Wu +4
In this paper, we present a digital twin (DT)-assisted adaptive video streaming scheme to enhance personalized quality-of-experience (PQoE). Since PQoE models are user-specific and…
Split Learning over Wireless Networks: Parallel Design and Resource Management
Wen Wu, Mushu Li, Kaige Qu +6
Split learning (SL) is a collaborative learning framework, which can train an artificial intelligence (AI) model between a device and an edge server by splitting the AI model into…
AI-Native Network Slicing for 6G Networks
Wen Wu, Conghao Zhou, Mushu Li +6
With the global roll-out of the fifth generation (5G) networks, it is necessary to look beyond 5G and envision the 6G networks. The 6G networks are expected to have space-air-groun…
Dynamic RAN Slicing for Service-Oriented Vehicular Networks via Constrained Learning
Wen Wu, Nan Chen, Conghao Zhou +4
In this paper, we investigate a radio access network (RAN) slicing problem for Internet of vehicles (IoV) services with different quality of service (QoS) requirements, in which mu…
Deep Reinforcement Learning for Delay-Oriented IoT Task Scheduling in Space-Air-Ground Integrated Network
Conghao Zhou, Wen Wu, Hongli He +5
In this paper, we investigate a computing task scheduling problem in space-air-ground integrated network (SAGIN) for delay-oriented Internet of Things (IoT) services. In the consid…
Efficient Hybrid Beamforming with Anti-Blockage Design for High-Speed Railway Communications
Meilin Gao, Bo Ai, Yong Niu +5
Future railway is expected to accommodate both train operation services and passenger broadband services. The millimeter wave (mmWave) communication is a promising technology in pr…
Fast mmwave Beam Alignment via Correlated Bandit Learning
Wen Wu, Nan Cheng, Ning Zhang +4
Beam alignment (BA) is to ensure the transmitter and receiver beams are accurately aligned to establish a reliable communication link in millimeter-wave (mmwave) systems. Existing…