In view of the scarce spectrum resources and inconvenient deployment in wireless communications, this work focuses on an unmanned aerial vehicle (UAV) enabled non-orthogonal multiple access (NOMA) system where a UAV deployed as a base station serves two users by NOMA. A joint power allocation and aerial jamming (PAAJ) scheme is proposed to achieve reliable and secure communications for the system in the presence of a malicious eavesdropper. To be specific, dynamic power allocation is adopted to ensure the reliability of the system and another friendly UAV jammer is introduced to improve the security of the system. The closed-form expressions of connection outage probability (COP), secrecy outage probability (SOP), and effective secrecy throughput (EST) are derived to evaluate the performance of the security-required user in the practical condition of probabilistic line-of-sight (LoS) and non-line-of-sight (NLoS) air-to-ground (A2G) channels. Moreover, the asymptotic EST is analyzed to obtain further insights. Numerical results show the validity of theoretical derivations and the superiority of the proposed PAAJ scheme over benchmark schemes. The EST of the UAV-enabled NOMA communication system outperforms the conventional terrestrial NOMA system at the low transmitting power from the UAV base station. There exists an optimal height of the UAV base station to maximize the EST, which provides a useful framework for designing UAV-enabled communication systems with heterogeneous service requirements.

This paper investigates the green and secure communications of multi-UAV NOMA systems. A joint energy transfer and artificial noise (ETAN) scheme is proposed to enhance the endurance and secrecy performance of the system. In particular, communication can be divided into two phases during each time frame. In the first phase, the multi-UAV system harvests energy from a power beacon. In the second phase, UAVs perform NOMA to transmit confidential messages uplink to a base station in the presence of eavesdropping UAVs. Simultaneously, to safeguard the multi-UAV system, the power beacon transmits artificial noise to degrade the eavesdropping channel. The closed-form expressions of connection outage probability (COP), secrecy outage probability (SOP) and effective secrecy throughput (EST) of the system are derived to evaluate the system performance. The asymptotic analysis of SOP and EST is also performed for further insights. Numerical results are presented to validate the correctness of theoretical derivations and the superiority of the proposed scheme. Analysis and simulation results demonstrate that the secrecy diversity order of the proposed scheme is determined by the jamming channel. When the number of UAVs increases, the time of energy harvesting should be appropriately extended. Moreover, substantial improvement to the system can be achieved by UAV pairing.

This letter investigates the minimum number of reflecting elements to achieve secure and energy-efficient unmanned aerial vehicle (UAV)-reconfigurable intelligent surface (RIS) systems. Specifically, we consider a UAV equipped with a RIS as a passive relay to assist communication from a source to users while avoiding terrestrial eavesdroppers. Taking account into phase estimation errors caused by imperfect conditions such as UAV jitter, the minimum number of reflecting elements under secrecy and energy efficiency constraints is derived in closed form. Our simulation results verify the correctness of theoretical derivation and demonstrate that the UAV-RIS systems outperform terrestrial RIS systems. Our research provides theoretical guidance for configuring reflecting elements in practical UAV-RIS systems.

Reconfigurable intelligent surface (RIS) is viewed as a promising technique that can be utilized to improve the performance of systems by reconfiguring signal propagation environments. This paper investigates green and secure unmanned aerial vehicle (UAV) Internet-of-Things (IoT) communications with the aid of RIS, where multiple UAVs harvest energy from a power beacon (PB) and send information uplink to access point (AP) with non-orthogonal multiple access (NOMA). In particular, communication can be divided into two phases during each time frame: energy transfer and information transmission. Three RIS deployment strategies are proposed. In mode I, RISs are deployed between UAVs and AP to enhance the information transmission. In mode II, RISs are deployed between PB and UAVs to enhance the energy transfer. In mode III, RISs are deployed between UAVs and a hybrid access point (HAP) to enhance energy transfer and information transmission simultaneously. Considering phase compensation error caused by imperfect conditions, we define and evaluate ergodic capacity (EC), ergodic capacity probability (ECP) and ergodic secrecy capacity (ESC) of three modes to measure the reliability and security of the system. The asymptotic expressions are also derived for further insights. Numerical results are presented to validate the correctness of theoretical derivations. Results demonstrate that the passive beamforming gain promised by RIS can significantly enhance the performance of systems. Mode III outperforms other modes in terms of reliability and security. When the transmission power and the number of UAVs increase, the ESCs of modes I and III converge to the same performance floor.

Intelligent reflecting surface (IRS)-assisted wireless communication has been recognized as an important way to enhance the security of unmanned aerial vehicle (UAV) networks. However, a single IRS may be unable to meet the transmission requirements in complex communication scenarios. In particular, due to the inherent instability of UAV platforms, the inevitable jitter caused by airflow and body vibration can have a great impact on transmission quality. In this paper, we study the multi-aerial IRS (AIRS) assisted secure simultaneous wireless information and power transfer (SWIPT) system with UAV jitter taken into account. For the purpose of exposition, two IRSs are deployed on two UAVs to reflect signals transmitted from the base station to an information user and an energy user; meanwhile an eavesdropper intends to eavesdrop on their messages. Angle estimation errors due to UAV jitter is transformed into the bounded channel state information (CSI) errors by applying linear approximations, and a joint optimization problem of the beamforming vector, AIRS phase shift matrices, and UAV trajectories is formulated to maximize the average secrecy rate (ASR). Since the problem is non-convex and the variables are strongly coupled, we propose an alternating optimization (AO) algorithm to deal with it. We decompose it into three sub-problems and adopt the Schur Complement, General S-Procedure, penalty dual decomposition (PDD), and successive convex approximation (SCA) methods to solve these non-convex sub-problems successfully. Numerical results show that UAV jitter could lead to system performance loss and demonstrate the performance gains of our proposed robust algorithm over other benchmark schemes.

This paper focuses on the unmanned aerial vehicle (UAV) enabled millimeter (mmWave) communications from physical layer security perspective. A UAV is arranged as an aerial base station to provide ubiquitous connectivity for terrestrial users in the presence of multiple eavesdroppers. With statistical channel state information (CSI) of eavesdroppers, the beamforming vector and trajectory of UAV as well as user scheduling are jointly optimized to minimize the weighted sum of UAV flight period and secrecy outage duration. The considered problem is a combinatorial optimization problem with complicated objective function, and thus difficult to be solved by convex optimization-based methods. To this end, we formulate this problem as a Markov decision process (MDP) and develop a deep reinforcement learning (DRL) based method to optimize all variables simultaneously. Simulation results validate superiority of the proposed method over benchmarks and demonstrate its ability to obtain a compromise between secure transmission and energy efficiency.