Research Projects

This research project aims to develop novel artificial intelligence (AI)-aided integrated adaptive sensing, computing, and communication techniques in UAV networks. UAVs are used as mobile sensing agents due to uncertain sensing environments, energy constraints, and unpredictable channel availability. The communication bandwidth resource is uncertain due to spectrum sharing and in-band coexistence of cooperative co-channel spectrum users in the presence of adversarial interference. The sensing context and communication channel constraints influence local/remote computing requirements, which in turn influence UAV mobility planning. The project proposes four modular cross-layer optimization tasks: (1) AI-aided mobile integrated sensing and communications: focusing on adaptive multi-sensing, data processing, sensor data fusion, channel/resource uncertainty versus delay and energy tradeoff, joint sensing and radar communication tradeoffs, multi-UAV coordination and shared data processing via spatio-temporal sensing, cooperative stochastic trajectory optimization, and edge computing optimization.(2) UAV for intelligent communication support: utilizing UAVs as mobile RIS (reconfigurable intelligent surface) and optimal beamforming to ground users for connectivity. (3) AI-aided UAV localization and swarm packing: utilizing data-driven impulse noise channel modeling for GPS satellites and AI-aided improved localization strategy for better UAV swarm coordination and interference management. (4) Learning-aided spectrum sharing and coexistence: exploring learning-aided spectrum sharing and in-band coexistence strategies to achieve higher channel capacity and communication under adversarial jamming scenarios. Some aspects of the research will be implemented using SDRs and Raspberry-Pi integrated UAV controllers.