Dr Yansha Deng's Home Page

Research Fundings & Projects

  • Sep. 2022 – Aug. 2026: Single PI “Network Automation for Cellular-Connected UAV Swarms”, awarded £88,862 from EPSRC and £32,591 from Toshiba Europe Ltd., EPSRC Industrial CASE Doctoral Research Studentship.
  • May. 2022 – April. 2024: PI “SiriusInsight: Enhancing AI for the Maritime Domain – AI-enabled Autonomous Vessels Monitoring, Navigation, and Persecution via Aerial and Ground Observations”, £204,671, Innovate UK KTP.
  • April. 2022 – Mar. 2025: Lead-PI “Smart Solutions Towards Cellular-Connected Unmanned Aerial Vehicles System”, £1,193,293, EPSRC Standard Grant
  • March 2021 – March 2022: Single PI “Artificial Intelligence-based Channel Access in Unlicensed Band”, £164,930, Industrial Fund.
  • Jan. 2020 – March 2023: Single PI “Microfluidic Molecular Communications: Design, Theory, and Manufacture (MIMIC)”, £266,109, EPSRC New Investigator Award.
  • Feb. 2019 – Feb. 2020: Lead-PI “Wiring the Smart City: Autonomous Monitoring of Safety and Health in London”,£25,000, King’s Together Equipment Grant.
  • Feb. 2020 – Dec. 2020: PI “A unified framework for autonomous monitoring of urban pollution and mental health”, £21,724, King’s Together Grant.
  • Oct. 2017 – Sep. 2020: “Communications Signal Processing Based Solutions for Massive Machine-to-Machine Networks (M3NETs)”‘ £317,872, EPSRC Standard Grant.
  • Microfluidic Molecular Communications

Molecular communication (MC) provides a way for nano/microdevices to communicate information over distance via chemical signals in nanometer to micrometer scale environments. The successful realization of MC will allow its future main applications, including drug delivery and environmental monitoring. The main hindrance for the MC application stands in the lack of nano/micro-devices capable of processing the time-varying chemical concentration signals in the biochemical environment. One promising solution is to design and implement programmable digital and analog building blocks, as they are fundamental building blocks for the signal processing at MC transceivers. This project aims to design the chemical reaction-based microfluidic MC prototypes with time-varying chemical signal processing functionalities, including modulation and demodulation, encoding and decoding, emission and detection. This also facilitates the microfluidic drug delivery prototype design and cancer cell on chip testing under time-varying drug concentration signal.

Fig. 1 Microfluidic MC System

[1] Y. Deng, M. Pierobon, A. Nallanathan, “A Microfluidic Feed Forward Loop Pulse Generator for Molecular Communication,” in Proc. of IEEE GLOBECOM’17, Singapore, Dec. 2017. (Best Paper Award  (15/2600 submissions) ) [PDF]

[2] D. Bi, Y. Deng*, M. Pierobon, A. Nallanathan, “Chemical Reactions-based Microfluidic Transmitter and Receiver Design for Molecular Communications ”  in IEEE Trans. on Communications, vol. 68, no. 9, pp. 5590-5605, Sept. 2020. [PDF]

[3] D. Bi, Y. Deng*, “Digital Signal Processing for Molecular Communication via Chemical Reactions-based Microfluidic Circuits,”  in IEEE Communications Magazine, 2021. [PDF]

[4] D. Bi, A. Apostolos, A. Noel, Y. Deng*, R. Schober, “A Survey of Molecular Communication in Cell Biology: Establishing a New Hierarchy for Interdisciplinary Applications,” in IEEE Communications Surveys and Tutorials, 2021. [PDF]

[5] D. Bi, Y. Deng*, “Microfluidic QCSK Transmitter and Receiver Design for Molecular Communication,” major revision, 2021. [PDF]

  • Cellular-connected UAVs Systems in 5G and Beyond

The 5G-and-Beyond cellular networks promise UAVs with ultra-reliable low-latency control, ubiquitous coverage, and seamless swarm connectivity under complex and highly flexible multi-UAV behaviours in three-dimension (3D), which will unlock the full potential of UAVs. This so-called cellular-connected UAVs (C-UAVs) system creates a radically different and rapidly evolving networking and control environment compared to conventional terrestrial networks. This project aims to develop artificial intelligence (AI)-powered for C-UAVs system with full network automation and conditional control automation, that allow for joint design and optimization of the network operation and the UAVs control in real-time with minimum human supervision and the target of mission completion under the long-term quality of service (QoS) guarantees.

Fig. 2 Diagram of Cellular-connected UAV Testbed [1]
Fig. 3 Hardware Setup [1]

[1] H. Zhou, F. Hu, M. Juras, A. B. Mehta and Y. Deng, “Real-time Video Streaming and Control of Cellular-Connected UAV System: Prototype and Performance Evaluation,” in IEEE Wireless Communications Letters, 2021. [PDF]

[2] J. Hou, Y. Deng, M Shikh-Bahaei, “Joint Beamforming, User Association, and Height Control for Cellular-Enabled UAV Communications”, IEEE Trans. on Communications, 2020. [PDF]

[3] D. Fan, F. Gao, B. Ai, G. Wang, Z. Zhong, Y. Deng, and A. Nallanathan, “Channel Estimation and Self-Positioning for UAV Swarm”,  IEEE Trans. on Communications, 2019. [PDF]