All Outputs (3)

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.