60 citations · 159 across the 20 of their papers we have counts for
20 papers
Communication Resources Constrained Hierarchical Federated Learning for End-to-End Autonomous Driving
Wei-Bin Kou, Shuai Wang, Guangxu Zhu +4
While federated learning (FL) improves the generalization of end-to-end autonomous driving by model aggregation, the conventional single-hop FL (SFL) suffers from slow convergence…
Edge-Assisted V2X Motion Planning and Power Control Under Channel Uncertainty
Zongze Li, Shuai Wang, Shiyao Zhang +4
Edge-assisted vehicle-to-everything (V2X) motion planning is an emerging paradigm to achieve safe and efficient autonomous driving, since it leverages the global position informati…
Phase Shift Design in RIS Empowered Wireless Networks: From Optimization to AI-Based Methods
Zongze Li, Shuai Wang, Qingfeng Lin +4
Reconfigurable intelligent surfaces (RISs) have a revolutionary capability to customize the radio propagation environment for wireless networks. To fully exploit the advantages of…
Reconfigurable Intelligent Surface Assisted OFDM Relaying: Subcarrier Matching with Balanced SNR
Tong Zhang, Shuai Wang, Yufan Zhuang +3
This paper considers a reconfigurable intelligent surface (RIS) aided orthogonal frequency division multiplexing (OFDM) relaying system, and investigates the joint design of RIS pa…
Robotic Wireless Energy Transfer in Dynamic Environments: System Design and Experimental Validation
Shuai Wang, Ruihua Han, Yuncong Hong +5
Wireless energy transfer (WET) is a ground-breaking technology for cutting the last wire between mobile sensors and power grids in smart cities. Yet, WET only offers effective tran…
Unit-Modulus Wireless Federated Learning Via Penalty Alternating Minimization
Shuai Wang, Dachuan Li, Rui Wang +3
Wireless federated learning (FL) is an emerging machine learning paradigm that trains a global parametric model from distributed datasets via wireless communications. This paper pr…
Distributed Dynamic Map Fusion via Federated Learning for Intelligent Networked Vehicles
Zijian Zhang, Shuai Wang, Yuncong Hong +2
The technology of dynamic map fusion among networked vehicles has been developed to enlarge sensing ranges and improve sensing accuracies for individual vehicles. This paper propos…
Space Shift Keying with Reconfigurable Intelligent Surfaces: Phase Configuration Designs and Performance Analysis
Qiang Li, Miaowen Wen, Shuai Wang +2
Reconfigurable intelligent surface (RIS)-assisted transmission and space shift keying (SSK) appear as promising candidates for future energy-efficient wireless systems. In this pap…
Edge Federated Learning Via Unit-Modulus Over-The-Air Computation
Shuai Wang, Yuncong Hong, Rui Wang +3
Edge federated learning (FL) is an emerging paradigm that trains a global parametric model from distributed datasets based on wireless communications. This paper proposes a unit-mo…
Reconfigurable Intelligent Surface Assisted Mobile Edge Computing with Heterogeneous Learning Tasks
Shanfeng Huang, Shuai Wang, Rui Wang +2
The ever-growing popularity and rapid improving of artificial intelligence (AI) have raised rethinking on the evolution of wireless networks. Mobile edge computing (MEC) provides a…
Learning Centric Wireless Resource Allocation for Edge Computing: Algorithm and Experiment
Liangkai Zhou, Yuncong Hong, Shuai Wang +4
Edge intelligence is an emerging network architecture that integrates sensing, communication, computing components, and supports various machine learning applications, where a fund…
Secure Massive RIS aided Multicast with Uncertain CSI: Energy-Efficiency Maximization via Accelerated First-Order Algorithms
Zongze Li, Shuai Wang, Miaowen Wen +1
Reconfigurable intelligent surface (RIS) has the potential to significantly enhance the network secure transmission performance by reconfiguring the wireless propagation environmen…
Edge Learning with Unmanned Ground Vehicle: Joint Path, Energy and Sample Size Planning
Dan Liu, Shuai Wang, Zhigang Wen +3
Edge learning (EL), which uses edge computing as a platform to execute machine learning algorithms, is able to fully exploit the massive sensing data generated by Internet of Thing…
Learning Centric Power Allocation for Edge Intelligence
Shuai Wang, Rui Wang, Qi Hao +2
While machine-type communication (MTC) devices generate massive data, they often cannot process this data due to limited energy and computation power. To this end, edge intelligenc…
Angle Aware User Cooperation for Secure Massive MIMO in Rician Fading Channel
Shuai Wang, Miaowen Wen, Minghua Xia +3
Massive multiple-input multiple-output communications can achieve high-level security by concentrating radio frequency signals towards the legitimate users. However, this system is…
Machine Intelligence at the Edge with Learning Centric Power Allocation
Shuai Wang, Yik-Chung Wu, Minghua Xia +2
While machine-type communication (MTC) devices generate considerable amounts of data, they often cannot process the data due to limited energy and computational power. To empower M…
Joint Communication and Motion Energy Minimization in UGV Backscatter Communication
Shuai Wang, Minghua Xia, Yik-Chung Wu
While backscatter communication emerges as a promising solution to reduce power consumption at IoT devices, the transmission range of backscatter communication is short. To this en…
Massive MIMO Multicast Beamforming Via Accelerated Random Coordinate Descent
Shuai Wang, Lei Cheng, Minghua Xia +1
One key feature of massive multiple-input multiple-output systems is the large number of antennas and users. As a result, reducing the computational complexity of beamforming desig…
Backscatter Data Collection with Unmanned Ground Vehicle: Mobility Management and Power Allocation
Shuai Wang, Minghua Xia, Yik-Chung Wu
Collecting data from massive Internet of Things (IoT) devices is a challenging task, since communication circuits are power-demanding while energy supply at IoT devices is limited.…
Multi-Pair Two-Way Relay Network with Harvest-Then-Transmit Users: Resolving Pairwise Uplink-Downlink Coupling
Shuai Wang, Minghua Xia, Yik-Chung Wu
While two-way relaying is a promising way to enhance the spectral efficiency of wireless networks, the imbalance of relay-user distances may lead to excessive wireless power at the…