Jing, Xiaoye; (2024) Energy-informed communication and sensing optimization for aerial networks. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

In recent years, compact base stations (BSs) mounted on unmanned aerial vehicles (UAVs) have emerged to construct portable aerial networks, playing an important role in wireless networks for easing the burden of terrestrial systems and facilitating emergency applications. A key challenge of aerial networks is the limited UAV energy, since the size of UAV onboard battery is constrained. Therefore, it becomes essential to consider the propulsion energy expended during UAV operations when designing UAV networks, with a focus on improving energy efficiency in UAV related researches. In the Thesis, we firstly focus on a UAV-based aerial network with multiple communication users (CUs), where the UAV acts as the aerial BS. We research on a UAV trajectory design method under energy constraint to enhance UAV coverage performance. By jointly designing the trajectory related parameters and optimizing downlink transmissions, the energy efficiency is improved in UAV communications. Integrated sensing and communication (ISAC) is a promising technology in six-generation (6G), which designs communication and sensing (C&S) systems in a joint manner, enabling to reduce the hardware cost and improve the resource efficiency. The separate C&S systems in UAVs incur a substantial payload, resulting in the degradation of UAV energy efficiency. To improve energy efficiency in UAV networks, applying the ISAC technology in UAV scenarios is a promising solution. In the Thesis, we research on the UAV trajectory design and bandwidth allocation to jointly improve C&S performances in an ISAC-based single UAV network. A weighted optimization problem is formulated to achieve a flexible tradeoff between C&S in the network. Subsequently, we focus on an ISAC-based multi-UAV network, where UAVs are deployed to perform a virtual antenna array (VAA). We propose a UAV deployment and beamforming method in this network to improve the sensing performance while guaranteeing the communication requirement. The Thesis models optimal/sub-optimal transmissions and UAV deployment/trajectory designs versus the energy awareness. The Thesis builds upon energy optimizations and balancing together with coordinated transmissions for UAV networks. Numerical results demonstrate that the proposed UAV deployment/trajectory design methods, along with the wireless techniques, can achieve flexible energy management in self-powered aerial networks.

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