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This paper investigates a cognitive unmanned aerial vehicle (UAV) enabledInternet of Things (IoT) network, where secondary/cognitive IoT devices uploadtheir data to the UAV hub following a non-orthogonal multiple access (NOMA)protocol in the spectrum of the primary network. We aim to maximize the minimumlifetime of IoT devices by jointly optimizing the UAV location, transmit power,and decoding order subject to interference-power constraints in presence of theimperfect channel state information (CSI). To solve the formulated non-convexmixed-integer programming problem, we first jointly optimize the UAV locationand transmit power for a given decoding order and obtain the globally optimalsolution with the assistance of Lagrange duality and then obtain the bestdecoding order by exhaustive search, which is applicable to relativelysmall-scale scenarios. For large-scale scenarios, we propose a low-complexitysub-optimal algorithm by transforming the original problem into a moretractable equivalent form and applying the successive convex approximation(SCA) technique and penalty function method. Numerical results demonstrate thatthe proposed design significantly outperforms the benchmark schemes.

Lifetime Maximization for UAV-Enabled Cognitive-NOMA IoT Networks: Joint Location, Power, and Decoding Order Optimization