In this paper, reconfigurable intelligent surface (RIS) is utilized to enhance the performance of the cooperative non-orthogonal multiple access (C-NOMA). The simultaneous wireless information and power transfer (SWIPT) technology is adopted at the cell-center user to relay information to the cell-edge user. We aim to maximize the data rate of the cell-edge user by jointly optimizing the beamforming vectors, the reflecting phase shifts, the power splitting (PS) ratio and the relaying power under the energy constraint and minimum data rate constraint of the cell-center user. To solve the established non-convex problem, an iterative algorithm based on alternate optimization is proposed to decompose the original problem into three sub-problems. In addition, successive convex approximation (SCA) and semi-definite relaxation (SDR) techniques are also employed to solve the sub-problems. Simulation results illustrate that the proposed RIS-assisted cooperative SWIPT NOMA scheme can effectively improve the performance of the cell-edge user compared with the traditional scheme without RIS.

Unmanned aerial vehicles (UAVs) are anticipated to be a potential data collection solution for wireless sensor networks (WSNs). The main challenges of integrating UAVs in WSNs are security threats and UAV’s onboard energy limitation. To cope with these two challenges, this article examines the secrecy energy efficiency (SEE) maximization problem in UAV-enabled WSN. Specifically, a full-duplex (FD) UAV gathers confidential information from ground sensor nodes (SNs) in the uplink while sending jamming signals to confound a ground eavesdropper (Eve) in the downlink. Considering a passive eavesdropping scenario lacking Eve’s instantaneous channel state information (CSI), the resulting problem is subject to the constraints of connection outage probability (COP), secrecy outage probability (SOP), securely collected bits, and flight trajectory. To tackle the intractable nonconvex problem, we first derive the optimal codeword rate and redundancy rate in closed-form expressions and then develop a low-complexity algorithm using the block coordinate descent (BCD) approach to alternatively optimize the SN scheduling, SN transmit power, UAV transmit power, and UAV trajectory. Simulation results verify the performance gains of the proposed scheme compared with the benchmark schemes. In particular, the proposed scheme achieves nearly the same secrecy rate gains at a lower UAV’s energy consumption cost than the sum secrecy rate maximization (SSRM) baseline. Moreover, it is revealed that trajectory optimization of the proposed scheme plays a crucial role in improving SEE performance compared with the circle trajectory (CT) baseline.

Despite its advantages of flexility and low-cost networking, unmanned aerial vehicle (UAV) communications face various attacks such as eavesdropping. Existing studies on secure UAV communications assume fixed-location eavesdroppers and rarely consider interactions between legitimate nodes and eavesdroppers. In this paper, we investigate eavesdropping and anti-eavesdropping interaction between a UAV-enabled eavesdropper (UAV-E) and a UAV-enabled base station (UAV-BS) in a downlink wiretap system. The UAV-E aims to wiretap downlink signals by adaptively adjusting its trajectory while the UAV-BS aims to maximize secrecy-sum-rate with minimum power consumption by jointly optimizing user scheduling, power control, and trajectory. Dynamic differential equations are formulated to characterize motions of UAVs, following which a zero-sum differential game is formulated to model the “pursuit-evasion” interaction between the UAV-BS and the UAV-E. Definition and existence of Nash equilibrium (NE) are provided. To obtain the NE, Pontryagins minimum principle is leveraged to solve the trajectory design problem. Further, Gauss-Seidel-like implicit finite-difference method is leveraged to obtain saddle-point strategies at NE. Finally, numerical results are provided to verify the effectiveness of the proposed game model. It is revealed that the differential game can well-characterize the strategy interactions between UAVs. Moreover, results show that the initial positions and weights of UAVs, the energy consumption factor, and the user scheduling have key impacts on motion interactions between the UAV-BS and the UAV-E and further on UAV-BS’s power control.

In this paper, we investigate the time minimization in the downlink (DL) wireless powered transmission network (WPCN) consisting of one base station (BS) and two energy harvesting (EH) users. The hybrid non orthogonal multiple access (H-NOMA) and hybrid EH scheme are adopted, in which each user can harvest energy from both the dedicated energy signal and the information signal for the other user. We aim to minimize the total time consumption under the data rate and energy consumption constraints. To solve the formulated non-convex problem, we propose a two-layer iterative algorithm. The problem in the inner layer is transformed to convex and the problem in the outer layer focused on the power allocation coefficient can be solved by binary search. Simulation results show that H-NOMA can achieve the best performance compared with time-division multiple access (TDMA) and NOMA, and NOMA also outperforms TDMA under the zero circuit power and little decoding power.

This paper studies the secrecy energy efficiency (SEE) maximization problem in a full-duplex (FD) bidirectional system, where an FD base station (BS) communicates with an FD user equipment (UE) with the existence of an external user who harvests energy from the ambient radio frequency (RF) signal with SWIPT and acts as a potential eavesdropper. To balance the secrecy rate and the energy efficiency, an SEE maximization problem is formulated subject to the minimum secrecy rate, the maximum transmitted power and the minimum harvested energy. The formulated non-convex problem is solved with a two-layer optimization algorithm, where Dinkelbach method is employed to deal with the fractional programming of the outer problem and a convex approximation method based on Taylor expansion is applied to transfer the inner problem into a convex iterative program. Numerical results demonstrate the effectiveness of the proposed algorithm and the advantages of FD operation in improving SEE.