Joint Channel Allocation and Power Control for Uplink NOMA-Assisted Multi-UAV Networks

The explosive growth of data leads to that the traditional wireless networks cannot enable various quality of service (QoS) communication for cellular-connected multi-UAV (unmanned aerial vehicle) networks. To overcome this obstacle, we solve the joint optimization problem of channel allocation and power control for uplink NOMA-assisted multi-UAV networks. Firstly, we design a mixed integer nonlinear programming framework, where the channel gains are characterized with integral form in time interval and sorted in nondescending order as the priority index of the decoded signal. In order to propose a feasible algorithm, the initial power levels of UAVs are obtained and integrated into the original problem which is reduced to integer programming problem. Then, the UAVs whose channel gain differences satisfy the constraints will be divided into a group to share the same channel, while the initial power levels of UAVs are adjusted to get a more satisfactory initial solution for power control. Combining the solution of channel allocation and the initial power levels, we solve power control problem with asynchronous update mechanism until the power levels of UAVs remain unchanged. Finally, we propose a channel allocation algorithm and a power control algorithm with the asynchronous optimization mechanism, respectively. Simulation results show that the proposed algorithms can effectively improve the network performance in terms of the aggregated rate.

Energy-Efficient Secure Communications for Wireless-Powered Cognitive Radio Networks

In this study, we investigate energy-efficient secure communications for wireless-powered cognitive ratio networks, in which multiple secondary users (SUs) share the same frequency band with primary users (PUs) and energy harvesting (EH) nodes harvest energy from the transmitted signals, even though information decoding is not permitted. To maximize the average secrecy energy efficiency (SEE) of SUs while ensuring acceptable interference on PUs and the required amount of energy for the EH nodes, we propose an energy-efficient transmit power control algorithm using dual decomposition, wherein suboptimal transmit powers are determined in an iterative manner with low complexity. Through extensive simulations in various scenarios, we verify that the proposed scheme has a higher average SEE than conventional schemes and a considerably shorter computation time than the optimal scheme.

Distributed Transmit Power Control for Energy-Efficient Wireless-Powered Secure Communications

In this study, we consider energy-efficient wireless-powered secure communications, in which N sets of transmitter, receiver, and energy harvesting (EH) nodes exist; each EH node is allowed only to harvest energy from the transmitted signals but is not to permitted to decode information. To maximize the sum secrecy energy efficiency (SEE) of the node sets while ensuring minimum EH requirement for each EH node, we propose a distributed transmit power control algorithm using a dual method, where each transmitter adjusts its transmit power iteratively until convergence without sharing information with the other node sets. Through simulations under various environments, we show that the proposed scheme surpasses conventional schemes in terms of the sum SEE and has significantly reduced computation time compared with the optimal scheme, which suggests the effectiveness and applicability of the proposed distributed method.