Collaborative CoMP and trajectory optimization for energy minimization in multi-UAV-assisted IoT networks with QoS guarantee

For the Internet of Things (IoT) networks, the coverage may be drastically degraded when disasters or breakdowns occur due to the destroyed communication network. Using unmanned aerial vehicles (UAVs) as flying base stations for IoT emergency coverage is possible because of their agility and low-altitude deployment. With the deployment of UAVs, strong co-channel interference may be formed in the network because of the line-of-sight channels between UAVs and the ground terminals. To address this issue, in this paper, coordinated multi-point (CoMP) technique along with the proper deployment of UAVs is developed in a multi-UAV-assisted IoT network. However, CoMP is difficult to implement for the entire network due to its processing delay and overhead. Therefore, the network is splatted into overlapped clusters by employing a user-centric clustering approach. We aim to minimize the system's energy consumption, including propulsion and communication energy, while optimizing the CoMP clusters and beamforming vectors, as well as the UAVs' trajectories and velocities. The energy minimization problem is formulated subject to target information rate for IoT users, UAVs' mobility, and maximum transmit power constraints. Since the formulated problem suffers from nonconvexity, an efficient solution is proposed to deal with it. First, for fixed clusters and beamforming vectors, the UAVs' trajectories and velocities are optimized. Then, for fixed UAVs' deployment, we optimize the CoMP clusters and beamforming vectors. Finally, two sub-problems are solved alternatively using an alternating optimization technique. Numerical results verify that the proposed solution is effective.