Lifetime Maximization for UAV-Enabled IoT Networks with Cognitive NOMA Transmissions

This paper investigates spectrum sharing communications in unmanned aerial vehicle (UAV) enabled internet of things (IoT) networks, where secondary/cognitive IoT devices simultaneously upload their data to the UAV following a non-orthogonal multiple access (NOMA) protocol in the pre-allocated spectrum to the primary network. We aim to maximize the minimum lifetime of IoT devices by jointly optimizing the UAV location, decoding order, and transmit power subject to probabilistic interference-power constraints at the primary base station (BS) while considering the imperfect channel state information (CSI). To solve the formulated non-convex mixed-integer programming problem, we first jointly optimize the UAV location and transmit power for given decoding order and obtain the globally optimal solution with the assistance of Lagrange duality. Then, by exhaustively searching all possible decoding orders, we obtain the global optimum to the formulated problem, which is applicable to relatively small-scale scenarios. For large-scale scenarios, we propose a low-complexity sub-optimal algorithm by transforming the original problem into a more tractable equivalent form and applying the successive convex approximation (SCA) technique and penalty function method. Numerical results demonstrate that the proposed design significantly outperforms the benchmark schemes.