In this paper, we consider an unmanned aerial vehicle (UAV) equipped with an air-to-ground friendly jammer assisting secure communications between a legitimate transmitter-receiver pair for unknown eavesdropper location. To enhance the reliability and security of this system, we examine the impact of the UAV jamming power and its three-dimensional (3D) spatial deployment on the outage probability (OP) of the legitimate receiver and the intercept probability (IP) of the eavesdropper. Based on the IP, we develop a new security measure, which we refer to as the intercept probability security region (IPSR). The IPSR defines the region within a target area where the IP is less than a given threshold. We design a low-complexity iterative algorithm to maximize the IPSR subject to an OP constraint by jointly optimizing the 3D deployment and jamming power of the UAV jammer. Numerical results show that our proposed iterative algorithm performs close to an exhaustive search with significantly reduced complexity.

This paper considers computation offloading for mobile applications with task-dependency requirements in mobile edge computing (MEC) systems. Based on the online arrival patterns and various delay constraints of practical applications, we focus on minimizing the system deadline violation ratio (DVR) to improve the overall reliability performance. Specifically, we propose a DVR minimization computation offloading scheme with task migration and merging, in which the task migration and merging model is designed to construct an overall directed acyclic graph (DAG) for all currently dependent tasks. We consider a multi-slot MEC system where applications arrive slot-by-slot without prior knowledge of future arrivals. Then given the number of application arrivals at each time slot, we equivalently transform the DVR minimization problem into a problem that maximizes the number of completed applications in a finite time horizon. The above problem is challenging to determine the optimal task execution order for different applications with various task dependencies and delay constraints. To address this, we develop a migration-enabled multi-priority task sequencing algorithm, which creatively introduces several task priority metrics and determines the optimal task execution order. Then, a deep deterministic policy gradient (DDPG)-based learning algorithm is developed to find the optimal offloading policy. Experimental results demonstrate that the proposed scheme can reduce the system DVR by 60.34%~70.3% compared with existing benchmark schemes under various network scenarios.

We propose and analyze secret key generation using intelligent reflecting surface (IRS) assisted wireless communication networks. To this end, we first formulate the minimum achievable secret key capacity for an IRS acting as a passive beamformer in the presence of multiple eavesdroppers. Next, we develop an optimization framework for the IRS reflecting coefficients based on the secret key capacity lower bound. To derive a tractable and efficient solution, we design and analyze a semidefinite relaxation (SDR) and successive convex approximation (SCA) based algorithm for the proposed optimization. Simulation results show that employing our IRS-based algorithm can significantly improve the secret key generation capacity for a wide-range of wireless channel parameters.

In this paper, we address the problem of joint covert communication and secure transmission in untrusted relaying networks when multiple wardens exist in the network. We first consider a system model consisting of one source, one untrusted amplify-and-forward relay, one destination, and one warden. For covert communications, our aim is to prevent the warden from detecting the presence of communications via the source-relay-destination link. For secure transmission, our aim is to prevent the untrusted relay from decoding the source signal. To satisfy these requirements, we propose that the destination and the source inject jamming signals during the source-to-relay and relay-to-destination transmission phases, respectively. For the considered system model, we propose a power allocation strategy to maximize the secrecy rate and satisfy the covert requirements in both of the phases. Given that the proposed optimization problem is non-convex, we employ the successive convex approximation (SCA) approach to derive a tractable solution. To obtain further insights, we generalize our analytical results to consider multiple untrusted relays and multiple wardens. We focus on two scenarios of non-colluding and colluding wardens. Our results highlight that as the number of relays increases, the achievable secrecy rate increases while the average detection error probability decreases. This is a novel observation of a fundamental trade-off between covert requirement and secrecy performance.

In mobile systems with low-altitude vehicles, integrated sensing and communication (ISAC) is considered an effective approach to increase the transmission rate due to limited spectrum resources. To further improve the ISAC performance, this paper proposes a novel method called integrated sensing and communication-movable antenna (ISAC-MA) to optimize the antenna’s position. Our goal is to support low-space vehicles by optimizing radar and communication joint beamforming and antenna position in the presence of clutter. This scheme not only guarantees the required signal-to-noise ratio (SNR) for sensing but also further improves the SNR for communication. A successive convex approximation (SCA)-based block coordinate descent (BCD) algorithm is proposed to maximize communication capacity under the condition of sensing SNR. Numerical results show that, compared with the traditional ISAC system and various benchmark schemes, the proposed ISAC-MA system can achieve higher communication capacity under the same sensing SNR constraints.