Dr Wenqiang Yi
-
Email
w.yi@essex.ac.uk -
Location
Colchester Campus
-
Academic support hours
ACADEMIC SUPPORT HOURS [Spring Term] Time: Tuesday 15.00-16.00; Wednesday 13.30 - 14.30 Office: 5B.522 If you wish to contact me to arrange a meeting outside of these hours, please feel free to do so at: w.yi@essex.ac.uk
Profile
Biography
Dr Wenqiang Yi is a Lecturer (Assistant Professor) at the School of Computer Science and Electronic Engineering, University of Essex. He received his Ph.D. degree in electrical engineering from the Queen Mary University of London, U.K., in 2020. From 2020 to 2023, he was a Post-Doctoral Researcher with the Communication Systems Research Group at the Queen Mary University of London. He was working on millimetre-wave communications and non-orthogonal multiple access techniques from the stochastic geometry-based network analysis and AI-aided resource allocation perspective. Based on previous research experience, his current research interests focused on radio frequency sensing in wireless systems, including communication and sensing mutual-interference management, communication resource management, wireless signal/channel feature characterising, physical-layer security, etc. He serves as an Associate Editor for IEEE OJ-COMS, in the area of Big Data and Machine Learning for Communications. He received the Exemplary Reviewer of the IEEE Communication Letters and the IEEE Transactions on Communications in 2019 and 2020. He served as the symposium chair on reconfigurable intelligent surfaces at IEEE ICCT. He has served as a TPC Member for many IEEE conferences, e.g., GLOBECOM and ICC. He also served as the Secretary of the Special Interest Group on Next Generation Multiple Access (NGMA) by the SPCC Technical Committee and the Emerging Technologies Initiatives on NGMA by the Emerging Technologies Committee till 2022.
Qualifications
-
PhD in Electronic Engineering Queen Mary University of London,
-
MSc in Wireless Communications and Signal Processing University of Bristol,
-
BSc in Optical Information Science and Technology Wuhan University of Technology,
Appointments
University of Essex
-
Lecturer (Assistant Professor), Computer Science and Electronic Engineering (15/10/2023 - present)
Other academic
-
Associate Editor, IEEE Open Journal of the Communications Society (11/12/2023 - 11/12/2026)
-
Post-Doctoral Researcher, Queen Mary University of London (1/6/2020 - 14/10/2023)
Research and professional activities
Research interests
Radio Frequency Sensing
Distributed Learning in Wireless Networks
Design and Analysis of Wireless Networks
Conferences and presentations
Exploiting Index Modulation for Enhanced NOMA
IEEE Global Communications Conference, 2023, Kuala Lumpur, Malaysia, 6/12/2023
Teaching and supervision
Current teaching responsibilities
-
High Level Digital Design (CE339)
-
High Level Logic Design (CE869)
Publications
Publications (20)
Chen, Z., Yi, W., Nallanathan, A. and Li, GY., (2022). Efficient Wireless Federated Learning with Partial Model Aggregation
Zhang, C., Yi, W., Liu, Y. and Hanzo, L., (2022). Semi-Integrated-Sensing-and-Communication (Semi-ISaC): From OMA to NOMA
Chen, Z., Yi, W., Alam, AS. and Nallanathan, A., (2022). Dynamic Task Software Caching-assisted Computation Offloading for Multi-Access Edge Computing
Xie, Z., Yi, W., Wu, X., Liu, Y. and Nallanathan, A., (2022). Is the Envelope Beneficial to Non-Orthogonal Multiple Access?
Ahsan, W., Yi, W., Liu, Y. and Nallanathan, A., (2022). A Reliable Reinforcement Learning for Resource Allocation in Uplink NOMA-URLLC Networks
Xie, Z., Yi, W., Wu, X., Liu, Y. and Nallanathan, A., (2021). STAR-RIS Aided NOMA in Multi-Cell Networks: A General Analytical Framework with Gamma Distributed Channel Modeling
Liu, Y., Yi, W., Ding, Z., Liu, X., Dobre, O. and Al-Dhahir, N., (2021). Developing NOMA to Next Generation Multiple Access (NGMA): Future Vision and Research Opportunities
Fayaz, M., Yi, W., Liu, Y. and Nallanathan, A., (2021). A Power-Pool-Based Power Control in Semi-Grant-Free NOMA Transmission
Xie, Z., Yi, W., Wu, X., Liu, Y. and Nallanathan, A., (2021). Modeling and Coverage Analysis for RIS-aided NOMA Transmissions in Heterogeneous Networks
Fayaz, M., Yi, W., Liu, Y. and Nallanathan, A., (2020). Transmit Power Pool Design for Grant-Free NOMA-IoT Networks via Deep Reinforcement Learning
Zhang, C., Yi, W. and Liu, Y., (2020). Reconfigurable Intelligent Surfaces Aided Multi-Cell NOMA Networks: A Stochastic Geometry Model
Yi, W., Yu, W., Liu, Y., Foh, CH., Ding, Z. and Nallanathan, A., (2020). Multiple Transmit Power Levels based NOMA for Massive Machine-type Communications
Yi, W., Liu, Y. and Nallanathan, A., (2020). Signal Fractions Analysis and Safety-Distance Modeling in V2V Inter-lane Communications
Zhang, C., Yi, W., Liu, Y., Qin, Z. and Chai, KK., (2020). Downlink Analysis for Reconfigurable Intelligent Surfaces Aided NOMA Networks
Yi, W., Liu, Y., Bodanese, E., Nallanathan, A. and Karagiannidis, GK., (2019). A Unified Spatial Framework for UAV-aided MmWave Networks
Yi, W., Liu, Y., Nallanathan, A. and Elkashlan, M., (2019). Clustered Millimeter Wave Networks with Non-Orthogonal Multiple Access
Yi, W., Liu, Y. and Nallanathan, A., (2018). Cache-enabled HetNets With Millimeter Wave Small Cells
Yi, W., Liu, Y. and Nallanathan, A., (2018). Exploiting Multiple Access in Clustered Millimeter Wave Networks: NOMA or OMA?
Yi, W., Liu, Y. and Nallanathan, A., (2018). Modeling and Analysis of MmWave Communications in Cache-enabled HetNets
Yi, W., Liu, Y. and Nallanathan, A., (2018). Modeling and Analysis of D2D Millimeter-Wave Networks with Poisson Cluster Processes
Journal articles (39)
Chen, Z., Yi, W. and Nallanathan, A., (2024). Exploring Representativity in Device Scheduling for Wireless Federated Learning. IEEE Transactions on Wireless Communications. 23 (1), 720-735
Xie, Z., Yi, W., Wu, X., Liu, Y. and Nallanathan, A., (2024). Is the Envelope Beneficial to Non-Orthogonal Multiple Access?. IEEE Transactions on Communications. 72 (3), 1625-1640
Fayaz, M., Yi, W., Liu, Y., Thayaparan, S. and Nallanathan, A., (2024). Toward Autonomous Power Control in Semi-Grant-Free NOMA Systems: A Power Pool-Based Approach. IEEE Transactions on Communications. 72 (6), 3273-3289
Chen, Z., Yi, W., Nallanathan, A. and Chambers, J., (2024). Distributed Digital Twin Migration in Multi-tier Computing Systems. IEEE Journal of Selected Topics in Signal Processing. 18 (1), 109-123
Chen, Z., Yi, W., Liu, Y. and Nallanathan, A., (2024). Robust Federated Learning for Unreliable and Resource-limited Wireless Networks. IEEE Transactions on Wireless Communications. 23 (8), 9793-9809
Zhang, C., Yi, W., Liu, Y., Ma, Z. and Zhang, X., (2024). NOMA for Multi-Cell RIS Networks: A Stochastic Geometry Model. IEEE Transactions on Wireless Communications. 23 (8), 10398-10413
Wu, N., Jiang, R., Wang, X., Yang, L., Zhang, K., Yi, W. and Nallanathan, A., (2024). AI-Enhanced Integrated Sensing and Communications: Advancements, Challenges, and Prospects. IEEE Communications Magazine. 62 (9), 144-150
Zhu, B., Zhao, L., Yi, W., Chen, Z. and Nallanathan, A., (2024). Cost-efficient Cooperative Video Caching Over Edge Networks. IEEE Internet of Things Journal. 11 (13), 23946-23960
Chen, Z., Yi, W., Shin, H., Nallanathan,, A. and Li, GY., (2024). Efficient Wireless Federated Learning with Partial Model Aggregation. IEEE Transactions on Communications. 72 (10), 6271-6286
Wang, Y., Ni, W., Yi, W., Xu, X., Zhang, P. and Nallanathan, A., (2024). Federated Contrastive Learning for Personalized Semantic Communication. IEEE Communications Letters. 28 (8), 1875-1879
Chen, Z., Yi, W., Shin, H. and Nallanathan, A., (2024). Adaptive Semi-Asynchronous Federated Learning over Wireless Networks. IEEE Transactions on Communications, 1-1
Fan, C., Zhou, X., Zhang, T., Yi, W. and Liu, Y., (2023). Cache-Enabled UAV Emergency Communication Networks: Performance Analysis With Stochastic Geometry. IEEE Transactions on Vehicular Technology. 72 (7), 9308-9321
Gao, X., Yi, W., Liu, Y., Zhang, J. and Zhang, P., (2023). DRL Enabled Coverage and Capacity Optimization in STAR-RIS-Assisted Networks. IEEE Transactions on Communications. 71 (11), 6616-6632
Chen, Z., Yi, W., Liu, Y. and Nallanathan, A., (2023). Knowledge-Aided Federated Learning for Energy-Limited Wireless Networks. IEEE Transactions on Communications. 71 (6), 3368-3386
Gao, X., Mu, X., Yi, W. and Liu, Y., (2023). Intelligent Trajectory Design for RIS-NOMA Aided Multi-Robot Communications. IEEE Transactions on Wireless Communications. 22 (11), 7648-7662
Pei, Y., Yue, X., Yi, W., Liu, Y., Li, X. and Ding, Z., (2023). Secrecy Outage Probability Analysis for Downlink RIS-NOMA Networks With On-Off Control. IEEE Transactions on Vehicular Technology. 72 (9), 11772-11786
Zhang, C., Yi, W., Liu, Y. and Hanzo, L., (2023). Semi-Integrated-Sensing-and-Communication (Semi-ISaC): From OMA to NOMA. IEEE Transactions on Communications. 71 (4), 1878-1893
Xie, Z., Liu, Y., Yi, W., Wu, X. and Nallanathan, A., (2023). Physical Layer Security for STAR-RIS-NOMA: A Stochastic Geometry Approach. IEEE Transactions on Wireless Communications. 23 (6), 6030-6044
Chen, Z., Yi, W., Shin, H. and Nallanathan, A., (2023). Adaptive Model Pruning for Communication and Computation Efficient Wireless Federated Learning. IEEE Transactions on Wireless Communications. 23 (7), 7582-7598
Gao, X., Yi, W., Liu, Y. and Hanzo, L., (2023). Multi-Objective Optimization of URLLC-Based Metaverse Services. IEEE Transactions on Communications. 71 (11), 6745-6761
Zhang, C., Yi, W., Liu, Y., Yang, K. and Ding, Z., (2022). Reconfigurable Intelligent Surfaces Aided Multi-Cell NOMA Networks: A Stochastic Geometry Model. IEEE Transactions on Communications. 70 (2), 951-966
Zhang, T., Wang, Y., Yi, W., Liu, Y., Feng, C. and Nallanathan, A., (2022). Two Time-Scale Caching Placement and User Association in Dynamic Cellular Networks. IEEE Transactions on Communications. 70 (4), 2561-2574
Ahsan, W., Yi, W., Liu, Y. and Nallanathan, A., (2022). A Reliable Reinforcement Learning for Resource Allocation in Uplink NOMA-URLLC Networks. IEEE Transactions on Wireless Communications. 21 (8), 5989-6002
Zhang, C., Yi, W., Liu, Y., Ding, Z. and Song, L., (2022). STAR-IOS Aided NOMA Networks: Channel Model Approximation and Performance Analysis. IEEE Transactions on Wireless Communications. 21 (9), 6861-6876
Xie, Z., Yi, W., Wu, X., Liu, Y. and Nallanathan, A., (2022). STAR-RIS Aided NOMA in Multicell Networks: A General Analytical Framework With Gamma Distributed Channel Modeling. IEEE Transactions on Communications. 70 (8), 5629-5644
Chen, Z., Yi, W., Alam, AS. and Nallanathan, A., (2022). Dynamic Task Software Caching-Assisted Computation Offloading for Multi-Access Edge Computing. IEEE Transactions on Communications. 70 (10), 6950-6965
Zhang, T., Wang, Y., Yi, W., Liu, Y. and Nallanathan, A., (2022). Joint Optimization of Caching Placement and Trajectory for UAV-D2D Networks. IEEE Transactions on Communications. 70 (8), 5514-5527
Xie, Z., Yi, W., Wu, X., Liu, Y. and Nallanathan, A., (2022). Downlink Multi-RIS Aided Transmission in Backhaul Limited Networks. IEEE Wireless Communications Letters. 11 (7), 1458-1462
Zhao, B., Zhang, C., Yi, W. and Liu, Y., (2022). Ergodic Rate Analysis of STAR-RIS Aided NOMA Systems. IEEE Communications Letters. 26 (10), 2297-2301
Liu, Y., Yi, W., Ding, Z., Liu, X., Dobre, OA. and Al-Dhahir, N., (2022). Developing NOMA to Next Generation Multiple Access: Future Vision and Research Opportunities. IEEE Wireless Communications. 29 (6), 120-127
Fayaz, M., Yi, W., Liu, Y. and Nallanathan, A., (2021). Transmit Power Pool Design for Grant-Free NOMA-IoT Networks via Deep Reinforcement Learning. IEEE Transactions on Wireless Communications. 20 (11), 7626-7641
Ahsan, W., Yi, W., Qin, Z., Liu, Y. and Nallanathan, A., (2021). Resource Allocation in Uplink NOMA-IoT Networks: A Reinforcement-Learning Approach. IEEE Transactions on Wireless Communications. 20 (8), 5083-5098
Yi, W., Liu, Y. and Nallanathan, A., (2021). Signal Fractions Analysis and Safety-Distance Modeling in V2V Inter-Lane Communications. IEEE Communications Letters. 25 (4), 1387-1390
Zhang, C., Liu, Y., Yi, W., Qin, Z. and Ding, Z., (2021). Semi-Grant-Free NOMA: Ergodic Rates Analysis With Random Deployed Users. IEEE Wireless Communications Letters. 10 (4), 692-695
Shen, H., Yi, W., Qin, Z., Liu, Y., Li, F. and Nallanathan, A., (2020). Coverage Analysis of mmWave Networks With Cooperative NOMA Systems. IEEE Communications Letters. 24 (7), 1544-1547
Yi, W., Liu, Y., Deng, Y. and Nallanathan, A., (2020). Clustered UAV Networks With Millimeter Wave Communications: A Stochastic Geometry View. IEEE Transactions on Communications. 68 (7), 4342-4357
Yi, W., Liu, Y., Bodanese, E., Nallanathan, A. and Karagiannidis, GK., (2019). A Unified Spatial Framework for UAV-Aided MmWave Networks. IEEE Transactions on Communications. 67 (12), 8801-8817
Yi, W., Liu, Y. and Nallanathan, A., (2018). Cache-Enabled HetNets With Millimeter Wave Small Cells. IEEE Transactions on Communications. 66 (11), 5497-5511
Yi, W., Liu, Y. and Nallanathan, A., (2017). Modeling and Analysis of D2D Millimeter-Wave Networks With Poisson Cluster Processes. IEEE Transactions on Communications. 65 (12), 5574-5588
Book chapters (1)
Yi, W., Liu, Y. and Ding, Z., (2024). Developing NOMA to Next-Generation Multiple Access. In: Signals and Communication Technology. Springer International Publishing. 291- 316. 9783031379192
Conferences (31)
Chen, Z., Yi, W. and Nallanathan, A., (2024). Multi-Agent Reinforcement Learning-Based Digital Twin Migration Over Wireless Networks
Chen, Z., Yi, W., Shin, H. and Nallanathan, A., (2024). Fast Wireless Federated Learning with Adaptive Synchronous Degree Control
Chen, Z., Yi, W., Liu, Y. and Nallanathan, A., (2023). Convergence Analysis for Wireless Federated Learning with Gradient Recycling
Gao, X., Yi, W., Agapitos, A., Wang, H. and Liu, Y., (2023). Coverage and Capacity Optimization in STAR-RISs Assisted Networks: A Machine Learning Approach
Zou, Y., Yi, W., Xu, X., Liu, Y., Chai, KK. and Liu, Y., (2023). Adaptive NGMA Scheme for IoT Networks: A Deep Reinforcement Learning Approach
Chen, Z., Yi, W., Liu, Y. and Nallanathan, A., (2023). Communication-Efficient Federated Learning with Heterogeneous Devices
Chen, Z., Yi, W., Nallanathan, A. and Li, GY., (2023). Is Partial Model Aggregation Energy-Efficient for Federated Learning Enabled Wireless Networks?
Chen, Z., Yi, W., Lambotharan, S. and Nallanathan, A., (2023). Efficient Wireless Federated Learning with Adaptive Model Pruning
Xie, Z., Yi, W., Wu, X., Liu, Y. and Nallanathan, A., (2023). Exploiting Index Modulation for Enhanced NOMA
Xie, Z., Liu, Y., Yi, W., Wu, X. and Nallanathan, A., (2023). Secrecy Performance Analysis in STAR-RIS-Aided NOMA Networks
Pei, Y., Yue, X., Yi, W., Liu, Y., Li, X. and Ding, Z., (2022). Secrecy Performance of RIS Aided NOMA Networks
Fayaz, M., Yi, W., Liu, Y. and Nallanathan, A., (2022). Multi-Agent DRL for Mitigating Power Collisions in SGF-NOMA Systems
Fayaz, M., Yi, W., Liu, Y. and Nallanathan, A., (2022). Load and Location Aware Resource Allocation in GF-NOMA IoT Networks
Chen, Z., Yi, W., Deng, Y. and Nallanathan, A., (2022). Device Scheduling for Wireless Federated Learning with Latency and Representativity
Gao, X., Zou, Y., Yi, W., Xu, J., Liu, R. and Liu, Y., (2022). Multi-objective Optimization of Energy and Latency in URLLC-enabled Wireless VR Networks
Fayaz, M., Yi, W., Liu, Y. and Nallanathan, A., (2022). Throughput Optimization for SGF-NOMA via Distributed DRL with Prioritized Experience Replay
Zhang, C., Yi, W. and Liu, Y., (2022). Semi-Integrated-Sensing-and-Communication (Semi-ISaC) Networks Assisted by NOMA
Zhang, C., Yi, W., Liu, Y. and Wang, Q., (2021). Multi-cell NOMA: Coherent Reconfigurable Intelligent Surfaces Model With Stochastic Geometry
Fayaz, M., Yi, W., Liu, Y. and Nallanathan, A., (2021). Transmit Power Pool Design for Uplink IoT Networks with Grant-free NOMA
Ahsan, W., Yi, W., Liu, Y. and Nallanathan, A., (2021). Reliable Reinforcement Learning Based NOMA Schemes for URLLC
Zhang, C., Yi, W., Han, K., Liu, Y., Ding, Z. and Di Renzo, M., (2021). Simultaneously Transmitting And Reflecting RIS Aided NOMA With Randomly Deployed Users
Zhang, C., Yi, W., Liu, Y., Qin, Z. and Chai, KK., (2020). Downlink Analysis for Reconfigurable Intelligent Surfaces Aided NOMA Networks
Ahsan, W., Yi, W., Liu, Y., Qin, Z. and Nallanathan, A., (2020). Reinforcement Learning for User Clustering in NOMA-Enabled Uplink IoT
Yi, W., Liu, Y., Nallanathan, A. and Elkashlan, M., (2019). Clustered Millimeter-Wave Networks With Non-Orthogonal Multiple Access
Yi, W., Liu, Y., Deng, Y., Nallanathan, A. and Heath, RW., (2019). Modeling and Analysis of MmWave V2X Networks With Vehicular Platoon Systems
Yi, W., Liu, Y. and Nallanathan, A., (2019). Coverage Analysis for mmWave-Enabled V2X Networks via Stochastic Geometry
Yi, W., Liu, Y., Elkashlan, M. and Nallanathan, A., (2019). Modeling and Coverage Analysis of Downlink UAV Networks with MmWave Communications
Yi, W., Liu, Y. and Nallanathan, A., (2018). Exploiting Multiple Access in Clustered Millimeter Wave Networks: NOMA or OMA?
Yi, W., Liu, Y. and Nallanathan, A., (2018). Modeling and Analysis of mmWave Communications in Cache-Enabled HetNets
Yi, W., Liu, Y., Nallanathan, A. and Karagiannidis, GK., (2018). A Unified Spatial Framework for Clustered UAV Networks Based on Stochastic Geometry
Yi, W., Liu, Y. and Nallanathan, A., (2018). Modeling and Analysis of Clustered D2D Millimeter-Wave Communications
Contact
Academic support hours:
ACADEMIC SUPPORT HOURS [Spring Term] Time: Tuesday 15.00-16.00; Wednesday 13.30 - 14.30 Office: 5B.522 If you wish to contact me to arrange a meeting outside of these hours, please feel free to do so at: w.yi@essex.ac.uk
Follow me on social media
