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Unmanned aerial vehicle (UAV) nowadays is a promising technology for boosting wireless connectivity, especially for upcoming 5G wireless networks. Due to its aerial feature, potential mobility and flexible deployment, the UAV can provide service in some specific scenarios such as post-disaster network recovery or no-infrastructure terrains. However, the problem of interference management between deployed UAV and underlaying heterogeneous networks, which guarantees the quality of service, is still a challenging task. In this paper, we address the outage probability for UAV connected users and device-to-device (D2D) receivers simultaneously operating in D2D underlaying NOMA UAV-assisted networks, and we derive its closed-form expressions, which turns out to be very accurate. We also solve the power control optimization problem via relaxing the non-convex problem into solving successive low-complexity linear programs to obtain a sub-optimal solution to the problem. The simulation results in confirm the superiority of the proposed approach in the terms of computational complexity and its compromise in the terms of sum rate. INDEX TERMS UAV, outage probability, power control, D2D, NOMA.

The deployment of femtocells in current and future communication systems promises an effective solution for limited indoor coverage problem and a possible gateway for mobile data offloading. In this paper, we cast a cognitive interference align ment approach (IA) suitable for heterogeneous cellular networks with a mixed macrocell and femtocell deployment Specifically, in our approach a restricted waterfflling (RWF) algorithm is used to maximize the downlink data rate, while reserving some eigenmodes for giving the femtocell basestations the opportunity to do their transmissions even at high signal-to-noise power ratio (SNR) for the macrocell basestation. Additionally, both the cross-tier and co-tier interference is to be aligned at each femtocell user's receiver using an Iterative Reweighted Least Squares(IRLS) algorithm. The simulation results show that the proposed IA approach provides an improved sum rate for the femtocell users, compared to the conventional IA techniques, Uke, the leakage minimization approach and the nuclear norm based rank constraint rank minimization approach.

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