Integrated sensing and communication (ISAC) is a rapidly evolving and highly promising technology for wireless networks, enabling the concurrent execution of communication and sensing functions within constrained spectrum resources. This paper examines a secure ISAC system assisted by an uncrewed aerial vehicle (UAV), in which the extended Kalman filter is incorporated for accurate estimation and prediction of eavesdropper states. Radar signals are transmitted to track and jam potential eavesdroppers while communication services are simultaneously provided to ground users. Under practical constraints—including maximum UAV velocity, transmit power, and propulsion energy consumption—the achievable uplink rate is maximized through joint optimization of the transmit beamforming and UAV trajectory. To address the computationally complex and inherently non-convex optimization problem, an efficient iterative algorithm combining block coordinate descent with successive convex approximation is designed, yielding a high-quality suboptimal solution. Finally, comprehensive simulations are conducted to evaluate the effectiveness of the proposed scheme against benchmark methods and to elucidate the inherent trade-off between communication and sensing performance.

Integrated sensing and communication (ISAC), an emerging technology for wireless networks, enables efficient use of scarce spectrum resources by supporting simultaneous communication and sensing. This work investigates the secrecy performance of an uncrewed aerial vehicle (UAV)-assisted ISAC system, in which a UAV operates as an aerial base station to serve multiple ground users while simultaneously transmitting sensing signals to detect potential eavesdroppers. To maximize the average secrecy rate, we jointly optimize the user scheduling, transmit beamforming, receive filtering vector, and the UAV’s flight trajectory. The formulated optimization problem is decomposed into four subproblems, which are transformed into convex forms via successive convex approximation, and is solved iteratively using the block coordinate descent method. Simulation results demonstrate the correctness and effectiveness of the proposed scheme.

Low Earth Orbit (LEO) satellite systems with sensing capabilities are widely regarded as promoting reliable and efficient communication services globally. This paper proposes a Multi-Satellite Collaborative Security System with Integrated Sensing and Communication (ISAC-MSC). Considering the potential benefits of LEO satellites and ISAC, we exploit sensing performance in the MSC system by jointly optimizing LEO satellite assignments, communication Beamforming (BF) vectors, and sensing BF vectors. Specifically, we design improved Continuous Particle Swarm (CP) optimization and Discrete Particle Swarm (DP) optimization algorithms to maximize the target sensing Signal-to-Noise Ratio (SNR) for LEO satellite assignments. Additionally, with respect to the BF vector optimization, we develop Power Approximation (PA) optimization algorithm, Inner Approximation (IA) optimization algorithm, and Joint Sensing and Communication BF (JSC-BF) optimization algorithm. Multiple algorithms are tightly integrated and alternately iterated. Numerical results show that: 1) the JSC-BF algorithms outperform the PA and IA algorithms in terms of sensing performance and communication secrecy rate; 2) compared to the single satellite case, the ISAC-MSC system performance approximately linear growth, and has strong extensibility; 3) with imperfect MSC synchronization case, the communication secrecy rate appears inflection point and stabilization, but the JSC-BF algorithms still have excellent performance.

In vehicular communication and mobile edge computing (MEC) networks, limited storage resources and challenges related to vehicles data security pose significant concerns. To address these issues while reducing communication latency and enhancing network security, blockchain technology is introduced. Additionally, deep reinforcement learning (DRL) is leveraged to optimize content caching strategies. By formulating a Markov decision process (MDP) model and applying the proximal policy optimization (PPO) algorithm, efficient cache management and optimal resource allocation are achieved. Simulation results demonstrate that the proposed approach effectively improves cache hit rates and significantly reduces latency in vehicular communication environments, yielding superior performance.

Space-air-ground integration has become paramount in the next generation of wireless communication systems in the era marked by the seamless integration of terrestrial and celestial domains. On the other hand, the age of information (AoI) has recently emerged as a vital metric for evaluating the timeliness and freshness of data in these multi-hop communication systems. This paper focuses on investigating the information freshness of multi-hop satellite IoT systems while considering several automatic repeat request (ARQ) and hybrid ARQ (HARQ) schemes over different hops to promise the reliability of data transmissions. Specifically, a group of remote sensors transmits their data to a terrestrial base station (B) via the code-division multiple access (CDMA) strategy to exploit CDMA’s natural merits, e.g., anti-jamming and simultaneous transmissions. Then, B sends these received data to a data destination (D) via a satellite (R) under the transparent forwarding strategy. We derive the closed form of the outage probability for the CDMA protocol considering multi-user interference (MUI) and the closed form of the end-to-end outage probability for the three kinds of ARQ and HARQ schemes on the dual-hopB-R-Dtransmission, and then finally derive the expression of the corresponding AoI. Finally, numerical results show that simulations match well with the theoretical results, proving the analysis’s correctness and the pros and cons of the different ARQ/HARQ schemes.

Low Earth orbit (LEO) Mega-constellations have emerged as a transformative approach to realize enhanced system capacity and improved coverage to satisfy the ever-increasing global demand for data services. Subsequently, the high density of satellites in a confined orbital region poses challenges, including potential interference among neighboring satellites. Further, it is vital to adequately address the impacts of safety distances in satellite communication systems on ensuring proper operation, collision avoidance, and interference management. Inspired by these observations, this work proposes a novel analysis tool, the Poisson arc hardcore point process (PAHPP), by extending the traditional Poisson line hardcore point process to characterize the unique orbiting properties of the satellites in LEO mega-constellations, accounting for factors such as the orbit, the satellite density, and spatial distribution. Specifically, this paper presents the PAHPP by enforcing a minimum separation between satellites operating in the same circular orbit to reflect the practical LEO mega-constellations. The imposed minimum inter-satellite separation in the proposed PAHPP model has also been applied to multi-orbit multi-satellite communication cases. Moreover, the discretization approximation technique is employed to analyze system performance, focusing on serving distance and outage probability. Numerical results provide valuable insights and conclusions for uncovering and recognizing LEO mega-constellations.

Underwater exploration, inspection, and surveillance have become more popular thanks to recent advancements in underwater wireless communication technologies, of which underwater wireless optical communication (UWOC) boasts increased bandwidth, reduced latency, and heightened security. Normally, once underwater sensors collect the data, it is transmitted to remote offices through a relay node stationed on the sea surface. In this study, our focus is on establishing and analyzing the performance of secrecy outage in an uplink hybrid radio frequency (RF)-UWOC space-ocean system that comprises a collection of underwater sensors, a relay floating on the ocean surface, a legitimate satellite receiver, and an eavesdropping satellite. In the considered system, the transmission performance from end-to-end is influenced by several factors. These include path loss, small-scale fading, position randomness of the satellites in RF links, propagation loss, turbulence-induced fading, and random location distribution of the underwater sensors in UWOC links. To enhance our understanding of system design, geometric probability theory is employed to investigate the end-to-end secrecy outage performance of the dual-hop RF-UWOC space-ocean uplink transmission while comprehensively considering the impacts of these factors. Finally, the accuracy of the proposed analysis models is verified through numerical results.

Millimeter wave (mmWave) signals are sensitive to blockages in wireless channels. Traditional mmWave transceiver designs intend to harvest both beamsteering and spatial multiplexing gains, but without considering the potential change in the channel state incurred by sudden blockages. In this paper, we propose a blockage-resilient hybrid transceiver design for supporting robust data transmissions in the face of dynamic blockages. Upon exploiting the spatial structure of mmWave channels, we formulate a weighted spectral efficiency maximization problem by utilizing the statistical information concerning the potential future blockages of different path clusters, which uniquely distinguishes this work from existing transceiver optimization problems. On the basis of alternating optimization, we propose a two-stage algorithm to deal with the resultant non-convex problem riddled with highly coupled variables. First, we alternatively optimize the fully digital transmit precoder and receive equalizer by transforming the optimization problem into a quadratic form. Based on the Block Successive Upper-bound Minimization (BSUM) framework, the optimal fully digital precoder and equalizer can be found by exploiting the Karush-Kuhn-Tucker (KKT) conditions and the matrix monotonic method. Then, inspired by the sparse signal recovery philosophy, the hybrid analog/digital transceiver structure is designed for approximating the fully digital solution. Our numerical results show that the proposed design strikes an improved throughput vs. blockage-resilience trade-off compared to existing schemes, which demonstrates its superiority.