Non-orthogonal multiple access (NOMA) allows multiple users to share link resource for higher spectrum efficiency. It can be applied to unmanned aerial vehicle (UAV) and mobile edge computing (MEC) networks to provide convenient offloading computing service for ground users (GUs) with large-scale access. However, due to the line-of-sight (LoS) of UAV transmission, the information can be easily eavesdropped in NOMA-based UAV-MEC networks. In this paper, we propose a secure communication scheme for the NOMA-based UAV-MEC system towards a flying eavesdropper. In the proposed scheme, the average security computation capacity of the system is maximized while guaranteeing a minimum security computation requirement for each GU. Due to the uncertainty of the eavesdropper’s position, the coupling of multi-variables and the non-convexity of the problem, we first study the worst security situation through mathematical derivation. Then, the problem is solved by utilizing successive convex approximation (SCA) and block coordinate descent (BCD) methods with respect to channel coefficient, transmit power, central processing unit (CPU) computation frequency, local computation and UAV trajectory. Simulation results show that the proposed scheme is superior to the benchmarks in terms of the system security computation performance.

With the maneuverability and mobility control of unmanned aerial vehicle (UAV), carrying mobile edge computing (MEC) servers on UAVs is able to effectively alleviate the explosive growth of data traffic pressure. However, UAV adopts line-of-sight transmission which has broadcasting characteristics. Malicious eavesdroppers can easily take advantage of the characteristics to eavesdrop information during the UAV edge computing. Therefore, the security of the UAV-MEC systems is a challenging problem. This article proposes a secure communication scheme for the dual-UAV-MEC system. In the proposed scheme, UAV server assists ground users in calculating the offloading tasks. In order to reduce the eavesdropping of offloading information by UAV eavesdropper, jammer sends interference signals on the ground. We aim to maximize the user's minimum secure calculation capacity by optimizing resources and trajectory of the UAV server. We first transform the optimization problem into a tractable form through mathematical methods and use successive convex approximation and block coordinate descent algorithms to solve it in an iterative manner. The final numerical results show that, compared with the benchmark schemes, the method proposed in this article effectively increases the secure calculation capacity of the system.

UAV communication has received widespread attention in MEC systems due to its high flexibility and line-of-sight transmission. Users can reduce their local computing pressures and computation delay by offloading tasks to the UAV as an edge server. However, the coverage capability of a single UAV is very limited. Moreover, the data offloaded to the UAV will be easily eavesdropped. Thus, in this paper, we propose two secure transmission methods for multi-UAV-assisted mobile edge computing based on the single-agent and multi-agent reinforcement learning, respectively. In the proposed methods, we first utilize the spiral placement algorithm to optimize the deployment of UAVs, which covers all users with the minimum number of UAVs. Then, to reduce the information eavesdropping by a flying eavesdropper, we utilize the reinforcement learning to optimize the secure offloading to maximize the system utility by considering different types of users’ tasks with diverse preferences for residual energy of computing equipment and processing delay. Simulation results indicate that compared with the single-agent method and the benchmark, the multi-agent method can optimize the offloading in a better manner and achieve larger system utility.

With the evolutional development of maritime networks, the explosive growth of maritime data has put forward elevated demands for the computing capabilities of maritime devices (MDs). Unmanned aerial vehicle (UAV) is able to alleviate the computing pressure of MDs by forwarding the computing tasks to the edge server on the coast. However, UAV relaying introduces a significant security challenge due to the vulnerability of line-of-sight (LoS) communication channels, which can be exploited for eavesdropping on computing tasks. In this paper, an efficient secure communication scheme is proposed for UAV-relay-assisted maritime mobile edge computing (MEC) with a flying eavesdropper. The secure computing capacity of MDs is maximized by jointly optimizing the transmit power, time slot allocation factor, computation optimization and UAV trajectory. Due to multi-variable coupling, the formulated optimization problem (OP) is non-convex. We first transform OP by introducing auxiliary variables. Then, the transformed OP is decomposed and solved in an iterative manner by applying block coordinate descent (BCD) and successive convex approximation (SCA). Numerical results show that the secure computing capability of the UAV-relay-assisted maritime MEC system of proposed secure communication scheme can be effectively improved compared with benchmarks.

To supporting the systematic requirements of higher spectrum efficiency and user deployment density in future industrial internet-of-things (IIoT), traditional orthogonal multiple access schemes, such as orthogonal frequency division multiplex, are quite limiting. Non-orthogonal multiple access has been recognized as one of enabling technologies for IIoT in 5G network. In this paper, we have proposed an alternative non-orthogonal multiple access scheme called interleave-grid multiple access (IGMA). Depending on interleaving and grid-mapping process, IGMA is capable to provide reliable block error rate performance, marvelous user multiplexing capability, as well as robustness against inter-cell interference. Interleave-grid multiple access can apply various detection and decoding techniques at receiver sides to improve the detection performance with acceptable complexity. Both of link-level and system level results show the promising benefits of interleave-grid multiple access, in particular that nearly seven times user multiplexing gain compared with orthogonal frequency division multiple access has been observed in the system-level simulation. In addition, a hardware test-bed has been implemented to verify the interleave-grid multiple access performance and the testing results proved the strong competitiveness of interleave-grid multiple access over orthogonal frequency division multiple access in terms of block error rate performance in user overloading scenarios.