All Outputs (27)

Model-Free Optimization and Experimental Validation of RIS-Assisted Wireless Communications Under Rich Multipath Fading (2023)
Journal Article
Chen, T., You, M., Zhang, Y., Zheng, G., Gros, J. B., Lerosey, G., …Gradoni, G. (2024). Model-Free Optimization and Experimental Validation of RIS-Assisted Wireless Communications Under Rich Multipath Fading. IEEE Wireless Communications Letters, 13(3), 627-631. https://doi.org/10.1109/lwc.2023.3337709

Reconfigurable intelligent surface (RIS) devices have emerged as an effective way to control the propagation channels for enhancing the end-users' performance. However, RIS optimization involves configuring the radio frequency response of a large num... Read More about Model-Free Optimization and Experimental Validation of RIS-Assisted Wireless Communications Under Rich Multipath Fading.

Blockchain and Artificial Intelligence Technologies for Smart Energy Systems (2023)
Book
Sun, H., Hua, W., & You, M. (2023). Blockchain and Artificial Intelligence Technologies for Smart Energy Systems. Chapman and Hall/CRC. https://doi.org/10.1201/9781003170440

Present energy systems are undergoing a radical transformation, driven by the urgent need to address the climate change crisis. At the same time, we are witnessing the sharp growth of energy data and a revolution of advanced technologies, with artifi... Read More about Blockchain and Artificial Intelligence Technologies for Smart Energy Systems.

Federated Learning Enabled Link Scheduling in D2D Wireless Networks (2023)
Journal Article
Chen, T., Zhang, X., You, M., Zheng, G., & Lambotharan, S. (2024). Federated Learning Enabled Link Scheduling in D2D Wireless Networks. IEEE Wireless Communications Letters, 13(1), 89-92. https://doi.org/10.1109/LWC.2023.3321500

Centralized machine learning methods for device-to-device (D2D) link scheduling may lead to a computing burden for a central server, transmission latency for decisions, and privacy issues for D2D communications. To mitigate these challenges, a federa... Read More about Federated Learning Enabled Link Scheduling in D2D Wireless Networks.

Protecting privacy in microgrids using federated learning and deep reinforcement learning (2022)
Conference Proceeding
Chen, W., Sun, H., Jiang, J., You, M., & Piper, W. J. (2022). Protecting privacy in microgrids using federated learning and deep reinforcement learning.

This paper aims to improve the energy management efficiency of home microgrids while preserving privacy. The proposed microgrid model includes energy storage systems, PV panels, loads, and the connection to the main grid. A federated multi-objective... Read More about Protecting privacy in microgrids using federated learning and deep reinforcement learning.

Towards Distributed Cell-less MIMO Testbed: An RFNoC Implementation (2022)
Presentation / Conference
You, M., Chen, T., & Zheng, G. (2022, June). Towards Distributed Cell-less MIMO Testbed: An RFNoC Implementation. Paper presented at 2022 EuCNC & 6G Summit, Grenoble, France & online

In this extended abstract, we will present a novel cell-less multiple-input multiple-output (MIMO) testbed design and an initial implementation based on the design. The key objective is to design a flexible and scalable architecture to facilitate the... Read More about Towards Distributed Cell-less MIMO Testbed: An RFNoC Implementation.

Downlink Cell-Free Fixed Wireless Access: Architectures, Physical Realities and Research Opportunities (2022)
Journal Article
Zhang, Y., You, M., Zheng, G., Rawi, A. A., & Tukmanov, A. (2023). Downlink Cell-Free Fixed Wireless Access: Architectures, Physical Realities and Research Opportunities. IEEE Wireless Communications, 30(2), 155-162. https://doi.org/10.1109/MWC.014.2100672

Recently a new paradigm of wireless access, termed as cell-free massive multiple-input multiple-output (MIMO), has drawn significant research interest. Its primary distinction from conventional massive MIMO aided cellular networks is the ability to e... Read More about Downlink Cell-Free Fixed Wireless Access: Architectures, Physical Realities and Research Opportunities.

Design and Analysis of SWIPT With Safety Constraints (2021)
Journal Article
Psomas, C., You, M., Liang, K., Zheng, G., & Krikidis, I. (2022). Design and Analysis of SWIPT With Safety Constraints. Proceedings of the IEEE, 110(1), 107-126. https://doi.org/10.1109/jproc.2021.3130084

Simultaneous wireless information and power transfer (SWIPT) has long been proposed as a key solution for charging and communicating with low-cost and low-power devices. However, the employment of radio frequency (RF) signals for information/power tr... Read More about Design and Analysis of SWIPT With Safety Constraints.

Graph Neural Network Based Beamforming in D2D Wireless Networks (2021)
Conference Proceeding
Chen, T., You, M., Zheng, G., & Lambotharan, S. (2021). Graph Neural Network Based Beamforming in D2D Wireless Networks. In WSA 2021: 25th International ITG Workshop on Smart Antennas : 10-21 November, 2021, EURECOM, French Riviera

An unsupervised graph neural network (GNN) approach is proposed to solve the beamforming design problem in device-to-device (D2D) wireless networks. Instead of directly learning the beamforming, the GNN is utilized to learn primal power and dual vari... Read More about Graph Neural Network Based Beamforming in D2D Wireless Networks.

Digital twins based day-ahead integrated energy system scheduling under load and renewable energy uncertainties (2021)
Journal Article
You, M., Wang, Q., Sun, H., Castro, I., & Jiang, J. (2022). Digital twins based day-ahead integrated energy system scheduling under load and renewable energy uncertainties. Applied Energy, 305, Article 117899. https://doi.org/10.1016/j.apenergy.2021.117899

By constructing digital twins (DT) of an integrated energy system (IES), one can benefit from DT’s predictive capabilities to improve coordinations among various energy converters, hence enhancing energy efficiency, cost savings and carbon emission r... Read More about Digital twins based day-ahead integrated energy system scheduling under load and renewable energy uncertainties.

Model-driven Learning for Generic MIMO Downlink Beamforming With Uplink Channel Information (2021)
Journal Article
Zhang, J., You, M., Zheng, G., Krikidis, I., & Zhao, L. (2022). Model-driven Learning for Generic MIMO Downlink Beamforming With Uplink Channel Information. IEEE Transactions on Wireless Communications, 21(4), 2368-2382. https://doi.org/10.1109/twc.2021.3111843

Accurate downlink channel information is crucial to the beamforming design, but it is difficult to obtain in practice. This paper investigates a deep learning-based optimization approach of the downlink beamforming to maximize the system sum rate, wh... Read More about Model-driven Learning for Generic MIMO Downlink Beamforming With Uplink Channel Information.

A Data Augmentation based DNN Approach for Outage-Constrained Robust Beamforming (2021)
Conference Proceeding
You, M., Zheng, G., & Sun, H. (2021). A Data Augmentation based DNN Approach for Outage-Constrained Robust Beamforming. . https://doi.org/10.1109/ICC42927.2021.9500736

This paper studies the long-standing problem of outage-constrained robust downlink beamforming in multi-user multi-antenna wireless communications systems. State of the art solutions have very high computational complexity which poses a major challen... Read More about A Data Augmentation based DNN Approach for Outage-Constrained Robust Beamforming.

A GNN-Based Supervised Learning Framework for Resource Allocation in Wireless IoT Networks (2021)
Journal Article
Chen, T., Zhang, X., You, M., Zheng, G., & Lambotharan, S. (2022). A GNN-Based Supervised Learning Framework for Resource Allocation in Wireless IoT Networks. IEEE Internet of Things Journal, 9(3), 1712-1724. https://doi.org/10.1109/JIOT.2021.3091551

The Internet of Things (IoT) allows physical devices to be connected over the wireless networks. Although device-to-device (D2D) communication has emerged as a promising technology for IoT, the conventional solutions for D2D resource allocation are u... Read More about A GNN-Based Supervised Learning Framework for Resource Allocation in Wireless IoT Networks.

Delay Guaranteed Joint User Association and Channel Allocation for Fog Radio Access Networks (2021)
Journal Article
You, M., Zheng, G., Chen, T., Sun, H., & Chen, K. (2021). Delay Guaranteed Joint User Association and Channel Allocation for Fog Radio Access Networks. IEEE Transactions on Wireless Communications, 20(6), 3723-3733. https://doi.org/10.1109/twc.2021.3053155

In the Fog Radio Access Networks (F-RANs), the local storage and computing capability of Fog Access Points (FAPs) provide new communication resources to address the latency and computing constraints for delay-sensitive applications. To achieve the ul... Read More about Delay Guaranteed Joint User Association and Channel Allocation for Fog Radio Access Networks.

A Versatile Software Defined Smart Grid Testbed: Artificial Intelligence Enhanced Real-Time Co-Evaluation of ICT Systems and Power Systems (2020)
Journal Article
You, M., Zhang, X., Zheng, G., Jiang, J., & Sun, H. (2020). A Versatile Software Defined Smart Grid Testbed: Artificial Intelligence Enhanced Real-Time Co-Evaluation of ICT Systems and Power Systems. IEEE Access, 8, 88651-88663. https://doi.org/10.1109/access.2020.2992906

In Smart Grid, the integration of Information and Communications Technology (ICT) systems and power systems has enabled real-time services and distributed controls, while the fusion of technologies necessitates a profound and versatile platform for t... Read More about A Versatile Software Defined Smart Grid Testbed: Artificial Intelligence Enhanced Real-Time Co-Evaluation of ICT Systems and Power Systems.

Deep Learning Enabled Optimization of Downlink Beamforming Under Per-Antenna Power Constraints: Algorithms and Experimental Demonstration (2020)
Journal Article
Zhang, J., Xia, W., You, M., Zheng, G., Lambotharan, S., & Wong, K. (2020). Deep Learning Enabled Optimization of Downlink Beamforming Under Per-Antenna Power Constraints: Algorithms and Experimental Demonstration. IEEE Transactions on Wireless Communications, 19(6), 3738-3752. https://doi.org/10.1109/twc.2020.2977340

This paper studies fast downlink beamforming algorithms using deep learning in multiuser multiple-input-single-output systems where each transmit antenna at the base station has its own power constraint. We focus on the signal-to-interference-plus-no... Read More about Deep Learning Enabled Optimization of Downlink Beamforming Under Per-Antenna Power Constraints: Algorithms and Experimental Demonstration.

Real-Time Price Elasticity Reinforcement Learning for Low Carbon Energy Hub Scheduling Based on Conditional Random Field (2019)
Conference Proceeding
Hua, W., You, M., & Sun, H. (2019). Real-Time Price Elasticity Reinforcement Learning for Low Carbon Energy Hub Scheduling Based on Conditional Random Field. In 2019 IEEE/CIC International Conference on Communications Workshops in China (ICCC Workshops) (204-209). https://doi.org/10.1109/iccchinaw.2019.8849941

Energy hub scheduling plays a vital role in optimally integrating multiple energy vectors, e.g., electricity and gas, to meet both heat and electricity demand. A scalable scheduling model is needed to adapt to various energy sources and operating con... Read More about Real-Time Price Elasticity Reinforcement Learning for Low Carbon Energy Hub Scheduling Based on Conditional Random Field.

Energy Hub Scheduling Method with Voltage Stability Considerations (2019)
Conference Proceeding
You, M., Hua, W., Shahbazi, M., & Sun, H. (2019). Energy Hub Scheduling Method with Voltage Stability Considerations. In 2018 IEEE/CIC International Conference on Communications in China (ICCC Workshops) (196-200). https://doi.org/10.1109/iccchinaw.2018.8674468

Energy Hub is expected to be one of the most effective methods to address the integrated system with multiple energy carriers. In this work, an Energy Hub scheduling method is proposed, which could not only meet various energy load demands but also a... Read More about Energy Hub Scheduling Method with Voltage Stability Considerations.

On statistical power grid observability under communication constraints (invited paper) (2018)
Journal Article
You, M., Jiang, J., Tonello, A. M., Doukoglou, T., & Sun, H. (2018). On statistical power grid observability under communication constraints (invited paper). IET Smart Grid, 1(2), 40-47. https://doi.org/10.1049/iet-stg.2018.0009

Phasor Measurement Units (PMUs) have enabled real-time power grid monitoring and control applications realizing an integrated power grid and communication system. The communication network formed by PMUs has strict latency requirements. If PMU measur... Read More about On statistical power grid observability under communication constraints (invited paper).

A Cognitive Radio Enabled Smart Grid Testbed Based on Software Defined Radio and Real Time Digital Simulator (2018)
Conference Proceeding
You, M., Liu, Q., & Sun, H. (2018). A Cognitive Radio Enabled Smart Grid Testbed Based on Software Defined Radio and Real Time Digital Simulator. In 2018 IEEE International Conference on Communications Workshops (ICC Workshops). https://doi.org/10.1109/iccw.2018.8403790

With the development of Smart Grid, there is an increasing need for the inter discipline research, analysis and evaluation, especially in the joint research area of communication system and power system. In this paper, we propose a Cognitive Radio en... Read More about A Cognitive Radio Enabled Smart Grid Testbed Based on Software Defined Radio and Real Time Digital Simulator.

Power grid observability redundancy analysis under communication constraints (2017)
Conference Proceeding
You, M., Liu, Q., Jiang, J., & Sun, H. (2017). Power grid observability redundancy analysis under communication constraints. In 2017 IEEE/CIC International Conference on Communications in China (ICCC). https://doi.org/10.1109/iccchina.2017.8330320

The Phasor Measurement Units (PMUs) have largely empowered the current and future smart grid applications, which play important roles in both power systems and Information and Communication Technology (ICT) systems within smart grid. They can provide... Read More about Power grid observability redundancy analysis under communication constraints.