UAV-RIS-Assisted Coordinated Multipoint Finite Blocklength Transmission for MTC Networks

The integration of unmanned aerial vehicles (UAVs) and reconfigurable intelligent surfaces (RISs) is a promising solution to provide flexibility in deploying the networks while reconstructing the wireless propagation environment proactively and cost effectively. We propose a UAV-RIS-assisted finite blocklength transmission framework for machine-type communications (MTCs), where downlink nonorthogonal multiple access (NOMA)-based coordinated multipoint (CoMP) is considered to mitigate intercell-interference and improve cell-edge transmission performance. Considering the cell-edge performance, we aim to maximize the minimum achievable rate of cell-edge devices (CEDs) by jointly optimizing the base stations' transmission power allocation ratio, subchannel-device matching scheme, RIS reflecting coefficient, and UAV trajectory. To solve the highly coupled nonconvex optimization problem, we propose a double-layer alternating optimization algorithm for maximizing the minimum rate (DLAO-MM) in an iterative manner. Specifically, in the inner layer, we first derive the closed-form solution of power allocation, the propose a low-complexity priority-based subchannel-device matching scheme, and finally solve the RIS phase optimization subproblem. In the outer layer, we propose a successive convex approximation (SCA)-based optimization algorithm for the UAV trajectory planning subproblem. The convergence and effectiveness of the proposed DLAO-MM scheme for UAV-RIS-aided CoMP transmission are evaluated by simulations, which show that: 1) the proposed DLAO-MM scheme is capable of improving the cell-edge performance compared to the benchmark schemes; 2) the combination of UAV and RIS improves the cell-edge performance compared with RIS deployed in a fixed location; and 3) adopting the NOMA scheme in the UAV-RIS-aided CoMP system achieves a higher minimum CED rate than orthogonal multiple access.