All Outputs (11)

An Unsupervised Domain Adaptation-Based Device-Free Sensing Approach for Cross-Weather Target Recognition in Foliage Environments (2024)
Conference Proceeding

In recent years, the emerging technique of device-free sensing (DFS) has gained popularity for foliage penetration (FOPEN) target recognition. This popularity is primarily attributed to its inherent advantage of not requiring specialized sensing equi... Read More about An Unsupervised Domain Adaptation-Based Device-Free Sensing Approach for Cross-Weather Target Recognition in Foliage Environments.

Protecting privacy in microgrids using federated learning and deep reinforcement learning (2022)
Conference Proceeding

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.

Graph Neural Network Based Beamforming in D2D Wireless Networks (2021)
Conference Proceeding

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.

A Data Augmentation based DNN Approach for Outage-Constrained Robust Beamforming (2021)
Conference Proceeding

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.

Real-Time Price Elasticity Reinforcement Learning for Low Carbon Energy Hub Scheduling Based on Conditional Random Field (2019)
Conference Proceeding

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

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.

A Cognitive Radio Enabled Smart Grid Testbed Based on Software Defined Radio and Real Time Digital Simulator (2018)
Conference Proceeding

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

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.

L-Index Sensitivity Based Voltage Stability Enhancement (2017)
Conference Proceeding

Voltage stability is a long standing issue in power systems. Due to the requirements of on-line monitoring and high computation efficiency, L-index is used as voltage stability metric in this paper. We propose a novel L-index sensitivity based contro... Read More about L-Index Sensitivity Based Voltage Stability Enhancement.

Realising energy-aware communication over fading channels under QoS constraints (2016)
Conference Proceeding

There exists a trade-off between energy consumption and spectral efficiency in wireless communication systems under quality of service (QoS) constraints. This paper studies the use of effective capacity theory to characterise the maximum supported ch... Read More about Realising energy-aware communication over fading channels under QoS constraints.

Effective capacity analysis of smart grid communication networks (2015)
Conference Proceeding

Smart grid represents a significant new technology of improving the efficiency, reliability and economics of the production, transmission and distribution of electricity that helps reduce carbon emissions. Communication networks become a key to achie... Read More about Effective capacity analysis of smart grid communication networks.