By Dr Wei Ni

Preprints

Zhai Z; Ni W; Wang X; Niyato D; Hossain E, 2025, Integrated Sensing and Communication with UAV Swarms via Decentralized Consensus ADMM

Ma H; Liu E; Ni W; Fang Z; Wang R; Gao Y; Niyato D; Hossain E, 2025, Through-the-Earth Magnetic Induction Communication and Networking: A Comprehensive Survey, http://dx.doi.org/10.48550/arxiv.2510.14854

Ling Z; Liwang M; Wang X; Hosseinalipour S; Cheng Z; Zou S; Ni W; Xia X, 2025, Auctioning Future Services in Edge Networks with Moving Vehicles: N-Step Look-Ahead Contracts for Sustainable Resource Provision, http://dx.doi.org/10.48550/arxiv.2510.07333

Abdisarabshali P; Nadimi F; Borazjani K; Khosravan N; Liwang M; Ni W; Niyato D; Langberg M; Hosseinalipour S, 2025, Hierarchical Federated Foundation Models over Wireless Networks for Multi-Modal Multi-Task Intelligence: Integration of Edge Learning with D2D/P2P-Enabled Fog Learning Architectures, http://dx.doi.org/10.48550/arxiv.2509.03695

Lu Y; Zhang S; Liu C; Zhang R; Ai B; Niyato D; Ni W; Wang X; Jamalipour A, 2025, Agentic Graph Neural Networks for Wireless Communications and Networking Towards Edge General Intelligence: A Survey, http://dx.doi.org/10.48550/arxiv.2508.08620

Lin X; Ma B; Wang X; Yu G; He Y; Ni W; Liu RP, 2025, CAN-Trace Attack: Exploit CAN Messages to Uncover Driving Trajectories, http://dx.doi.org/10.48550/arxiv.2507.09624

Qi H; Liwang M; Hosseinalipour S; Fu L; Zou S; Ni W, 2025, Future Resource Bank for ISAC: Achieving Fast and Stable Win-Win Matching for Both Individuals and Coalitions, http://dx.doi.org/10.48550/arxiv.2502.08118

Zhao X; Cui Q; Ni W; Sheng QZ; Jamalipour A; Nan G; Tao X; Zhang P, 2025, A Novel Indicator for Quantifying and Minimizing Information Utility Loss of Robot Teams, http://dx.doi.org/10.48550/arxiv.2506.14237

Zhao X; Cui Q; Li W; Ni W; Hossain E; Sheng QZ; Tao X; Zhang P, 2025, Convergence-Privacy-Fairness Trade-Off in Personalized Federated Learning, http://dx.doi.org/10.48550/arxiv.2506.14251

Zhao X; Cui Q; Du Z; Li W; Yu X; Ni W; Zhang J; Tao X; Zhang P, 2025, Enhancing Convergence, Privacy and Fairness for Wireless Personalized Federated Learning: Quantization-Assisted Min-Max Fair Scheduling, http://dx.doi.org/10.48550/arxiv.2506.02422

Sun P; Liu E; Ni W; Wang R; Geng Y; Lai L; Jamalipour A, 2025, LAPA-based Dynamic Privacy Optimization for Wireless Federated Learning in Heterogeneous Environments, http://dx.doi.org/10.48550/arxiv.2505.19823

Li K; Li C; Yuan X; Li S; Zou S; Ahmed SS; Ni W; Niyato D; Jamalipour A; Dressler F; Akan OB, 2025, Zero-Trust Foundation Models: A New Paradigm for Secure and Collaborative Artificial Intelligence for Internet of Things, http://dx.doi.org/10.48550/arxiv.2505.23792

Sun P; Liu E; Ni W; Yu K; Wang R; Jamalipour A, 2025, Cluster-Aware Multi-Round Update for Wireless Federated Learning in Heterogeneous Environments, http://dx.doi.org/10.48550/arxiv.2505.06268

Yang H; Liu H; Yuan X; Wu K; Ni W; Zhang JA; Liu RP, 2025, Synergizing Intelligence and Privacy: A Review of Integrating Internet of Things, Large Language Models, and Federated Learning in Advanced Networked Systems, http://dx.doi.org/10.20944/preprints202504.2082.v1

Cao Y; Wang J; Shi X; Ni W, 2025, Lightweight and Self-Evolving Channel Twinning: An Ensemble DMD-Assisted Approach, http://dx.doi.org/10.48550/arxiv.2504.16376

Li W; Lv T; Ni W; Zhao J; Hossain E; Poor HV, 2025, Route-and-Aggregate Decentralized Federated Learning Under Communication Errors, http://dx.doi.org/10.48550/arxiv.2503.22186

Yu X; Lv T; Li W; Ni W; Niyato D; Hossain E, 2025, Multi-Task Semantic Communication With Graph Attention-Based Feature Correlation Extraction, http://dx.doi.org/10.48550/arxiv.2501.02006

Li K; Liang Y; Yuan X; Ni W; Crowcroft J; Yuen C; Akan OB, 2024, A Novel Framework of Horizontal-Vertical Hybrid Federated Learning for EdgeIoT, http://dx.doi.org/10.48550/arxiv.2410.01644

Emami Y; Li K; Almeida L; Zou S; Ni W, 2024, On the Use of Immersive Digital Technologies for Designing and Operating UAVs, http://dx.doi.org/10.48550/arxiv.2407.16288

Chen X; Li Z; Ni W; Wang X; Zhang S; Sun Y; Xu S; Pei Q, 2024, Towards Dynamic Resource Allocation and Client Scheduling in Hierarchical Federated Learning: A Two-Phase Deep Reinforcement Learning Approach, http://dx.doi.org/10.48550/arxiv.2406.14910

Cao Y; Dai L; Tan J; Wang J; Zheng T; Ni W; Hossain E; Niyato D, 2024, Advancing Ubiquitous Wireless Connectivity through Channel Twinning, http://dx.doi.org/10.48550/arxiv.2406.12268

Geng Y; Liu E; Ni W; Wang R; Liu Y; Xu H; Cai C; Jamalipour A, 2024, Balancing Performance and Cost for Two-Hop Cooperative Communications: Stackelberg Game and Distributed Multi-Agent Reinforcement Learning, http://dx.doi.org/10.48550/arxiv.2406.11265

Li W; Lv T; Ni W; Zhao J; Hossain E; Poor HV, 2024, Decentralized Federated Learning Over Imperfect Communication Channels, http://dx.doi.org/10.48550/arxiv.2405.12894

Li C; Ni W; Ding M; Qu Y; Chen J; Smith D; Zhang W; Rakotoarivelo T, 2024, Decentralized Privacy Preservation for Critical Connections in Graphs, http://dx.doi.org/10.48550/arxiv.2405.11713

Sun P; Liu E; Ni W; Yu K; Qu X; Wang R; Bi Y; Zhang C; Jamalipour A, 2024, Dual-Segment Clustering Strategy for Hierarchical Federated Learning in Heterogeneous Wireless Environments, http://dx.doi.org/10.48550/arxiv.2405.09276

Jin X; Lv T; Ni W; Lin Z; Zhu Q; Hossain E; Poor HV, 2024, A Reconfigurable Subarray Architecture and Hybrid Beamforming for Millimeter-Wave Dual-Function-Radar-Communication Systems, http://dx.doi.org/10.48550/arxiv.2404.15750

Li K; Yuan X; Zheng J; Ni W; Dressler F; Jamalipour A, 2024, Leverage Variational Graph Representation For Model Poisoning on Federated Learning, http://dx.doi.org/10.48550/arxiv.2404.15042

Bi S; Yuan X; Hu S; Li K; Ni W; Hossain E; Wang X, 2024, Failure Analysis in Next-Generation Critical Cellular Communication Infrastructures, http://dx.doi.org/10.48550/arxiv.2402.04448

Zhang H; Liu E; Wang R; Ni W; Xing Z; Liu Y; Jamalipour A, 2023, Reconfigurable Intelligent Surface-Assisted Localization in OFDM Systems with Carrier Frequency Offset and Phase Noise, http://dx.doi.org/10.48550/arxiv.2312.12534

Wan Y; Qu Y; Ni W; Xiang Y; Gao L; Hossain E, 2023, Data and Model Poisoning Backdoor Attacks on Wireless Federated Learning, and the Defense Mechanisms: A Comprehensive Survey, http://dx.doi.org/10.48550/arxiv.2312.08667

Li K; Zheng J; Yuan X; Ni W; Akan OB; Poor HV, 2023, Data-Agnostic Model Poisoning against Federated Learning: A Graph Autoencoder Approach, http://dx.doi.org/10.48550/arxiv.2311.18498

Gong Z; Hashash O; Wang Y; Cui Q; Ni W; Saad W; Sakaguchi K, 2023, UAV-Aided Lifelong Learning for AoI and Energy Optimization in Non-Stationary IoT Networks, http://dx.doi.org/10.48550/arxiv.2312.00334

Hu S; Yuan X; Ni W; Wang X; Hossain E; Poor HV, 2023, OFDMA-F$^2$L: Federated Learning With Flexible Aggregation Over an OFDMA Air Interface, http://dx.doi.org/10.48550/arxiv.2311.15141

Li K; Lau BPL; Yuan X; Ni W; Guizani M; Yuen C, 2023, Towards Ubiquitous Semantic Metaverse: Challenges, Approaches, and Opportunities, http://dx.doi.org/10.48550/arxiv.2307.06687

Xiao B; Yu X; Ni W; Wang X; Poor HV, 2023, Over-The-Air Federated Learning: Status Quo, Open Challenges, and Future Directions, http://dx.doi.org/10.48550/arxiv.2307.00974

Qu Y; Yuan X; Ding M; Ni W; Rakotoarivelo T; Smith D, 2023, Learn to Unlearn: A Survey on Machine Unlearning, http://dx.doi.org/10.48550/arxiv.2305.07512

Wang Y; Sun T; Li S; Yuan X; Ni W; Hossain E; Poor HV, 2023, Adversarial Attacks and Defenses in Machine Learning-Powered Networks: A Contemporary Survey, http://dx.doi.org/10.48550/arxiv.2303.06302

Yuan X; Ni W; Ding M; Wei K; Li J; Poor HV, 2023, Amplitude-Varying Perturbation for Balancing Privacy and Utility in Federated Learning, http://dx.doi.org/10.48550/arxiv.2303.04274

Yuan C; Ni W; Zhang K; Bai J; Shen J; AbbasJamalipour , 2023, User Pairing and Power Allocation in Untrusted Multiuser NOMA for Internet-of-Things, http://dx.doi.org/10.48550/arxiv.2302.05645

Cui Y; Lv T; Ni W; Jamalipour A, 2023, Digital Twin-Aided Learning for Managing Reconfigurable Intelligent Surface-Assisted, Uplink, User-Centric Cell-Free Systems, http://dx.doi.org/10.48550/arxiv.2302.05073

Hu S; Yuan X; Ni W; Wang X; Jamalipour A, 2023, RIS-Assisted Jamming Rejection and Path Planning for UAV-Borne IoT Platform: A New Deep Reinforcement Learning Framework, http://dx.doi.org/10.48550/arxiv.2302.04994

Yuan X; Hu S; Ni W; Liu RP; Wang X, 2023, Learning-based Intelligent Surface Configuration, User Selection, Channel Allocation, and Modulation Adaptation for Jamming-resisting Multiuser OFDMA Systems, http://dx.doi.org/10.48550/arxiv.2301.06223

ashtarinakhaei S; Abolhasan M; Lipman J; Shariati N; Ni W; Jamalipour A, 2023, A Location-Based Multi-Hop Routing Protocol for Future Wireless Cellular Networks, http://dx.doi.org/10.2139/ssrn.4380644

Kurunathan H; Huang H; Li K; Ni W; Hossain E, 2022, Machine Learning-Aided Operations and Communications of Unmanned Aerial Vehicles: A Contemporary Survey, http://dx.doi.org/10.48550/arxiv.2211.04324

Li K; Cui Y; Li W; Lv T; Yuan X; Li S; Ni W; Simsek M; Dressler F, 2022, When Internet of Things meets Metaverse: Convergence of Physical and Cyber Worlds, http://dx.doi.org/10.48550/arxiv.2208.13501

Zheng J; Tian H; Ni W; Ni W; Zhang P, 2022, Balancing Accuracy and Integrity for Reconfigurable Intelligent Surface-aided Over-the-Air Federated Learning, http://dx.doi.org/10.48550/arxiv.2207.08057

Zheng J; Li K; Mhaisen N; Ni W; Tovar E; Guizani M, 2022, Exploring Deep Reinforcement Learning-Assisted Federated Learning for Online Resource Allocation in Privacy-Persevering EdgeIoT, http://dx.doi.org/10.48550/arxiv.2202.07391

Wang Y; Li S; Ni W; Abbott D; Johnson M; Pei G; Hedley M, 2021, Three-dimensional Cooperative Localization of Commercial-Off-The-Shelf Sensors, http://dx.doi.org/10.48550/arxiv.2111.02040

Cao Y; Lv T; Ni W; Lin Z, 2021, Sum-Rate Maximization for Multi-Reconfigurable Intelligent Surface-Assisted Device-to-Device Communications, http://dx.doi.org/10.48550/arxiv.2108.07091

Wang X; Ni W; Zha X; Yu G; Liu RP; Georgalas N; Reeves A, 2021, Capacity Analysis of Public Blockchain, http://dx.doi.org/10.48550/arxiv.2106.14149

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