Introducing friendly jammer to unmanned aerial vehicle (UAV) covert communication could further enhance the covert performance. However, due to the additional communication overhead required for information synchronization (IS) among cooperating parties, the security risk is further elevated. It is noteworthy that cognitive jamming (CJ) could sense the cooperating node signals without IS links. Therefore, in this paper, we propose the cooperative UAVs covert communication scheme assisted by the CJ that maximize the minimum average covert rate (MACR). Specifically, the UAV (Alice) tries to transmit its private message to legitimate users under the surveillance of the Wardens. Since the Warden is in passive surveillance, the practical location uncertainty of the Warden is considered, and we further analyze the worst-case situation that derives the minimal detection error probability of the Wardens. Moreover, we maximize the MACR by alternatively optimizing the sense time ratio and trajectory of CJ, the transmit power and trajectory of the Alice. To expedite algorithmic convergence, we further introduce a principled initialization scheme. The simulation results reveal that the covert performance of the proposed algorithm outperforms the other schemes, especially, in the multi-warden scenario. Furthermore, compared with the full-time jammer and probabilistic jammer, the CJ can not only achieve a higher covert rate with less average jamming power, but also require no information synchronization link with Alice based on spectrum sensing, which promises considerable application prospects in real-world systems.

The integrated communication and jamming system can integrate communication and jamming functionalities to reinforce each other in one system, arising from the increasing demand for equipment miniaturization and resource multiplexing. This paper proposes the integrated communication and jamming network (ICAJN) where multi-functional nodes serve asmobileaccess points, providing flexible communication and jamming coverage in the temporary, infrastructure-less scenarios. In addition to coverage, connectivity is also essential to ensure distributed coordination and signalling interaction among nodes. However, achieving simultaneous coverage and connectivity is challenging due to two main factors: on one hand, there exists an inherent tradeoff between coverage and connectivity in terms of node deployment; on the other hand, the dynamic electromagnetic environment complicates the real-time link gain estimation. The goal of this paper is to incorporate environment-awareness capabilities into the ICAJN, dynamically adjusting the working state to achieve simultaneous coverage and connectivity. To this end, the workflow of the ICAJN is structured into an environment-awareness phase and an execution phase, and the event-triggered sensing protocol (ETSP) is introduced to activate sensing function on demand. In the environment-awareness phase, the spatial interpolation is developed to estimate the gains of wireless links in the yet-to-reach locations, and further infer communication/jamming coverage boundaries. In the execution phase, the working state optimization algorithm is proposed to determine optimal node deployment locations, transmit power, and grouping policies in the current environment. Extended simulation results demonstrate that incorporating environment-awareness capabilities into ICAJN can significantly improve the network performance. And the designed protocol shows adaptability to the dynamic electromagnetic environments.

Autonomous aerial vehicle (AAV) covert communication could further enhance the quality and coverage of covert channels. However, in complex low-altitude environments, the air-to-ground (A2G) links are susceptible to the fading effects, which may degrade the performance of covert communication. In this paper, we investigate the fluid antenna (FA) enabled AAV covert communication, where a AAV equipped with FA serves multiple ground users in the presence of an active Warden. We aim to maximize the minimum average covert rate by jointly optimizing the beamforming vectors, AAV trajectory and fluid antenna positions. First, we derive closed-form expressions for the minimum detection error probability (MDEP) and the optimal detection threshold, accounting for uncertainties in both the noise variance and the self-interference channel coefficient. Secondly, we propose an alternating optimization algorithm subject to the covertness constraint, power constraint, and the Warden’s position uncertainty. Specifically, the original nonconvex problem is decomposed into tractable subproblems via the block coordinate descent, which could be solved successively by successive convex approximation, semidefinite relaxation, and Dinkelbach transformation. What’s more, a low-complexity algorithm is developed for the single-user scenario to improve the practical applicability of the proposed framework. Finally, simulation results validate the effectiveness of the proposed FA-AAV covert communication scheme. Moreover, compared to the fixed position antenna scheme, the FA-AAV could improve the covert performance, especially in strong channel fading environments, which is beneficial for practical application.

Unmanned-aerial-vehicles (UAVs)-enabled wireless communication for Internet-of-Things (IoT) applications has attracted increasing attention. This article studies a UAV-assisted data dissemination system, where a rotary-wing UAV is dispatched to disseminate data to terrestrial IoT devices. We target to minimize the completion time via a joint optimization of the UAV trajectory and transmit power, while considering the indispensable constraints which cover the maximum energy budget, speed, transmit power of the UAV, and data requirement for each IoT device. First, we formulate the UAV data dissemination as a completion time minimization problem. To tackle the nonconvex optimization problem, the original problem is transformed into two subproblems: 1) the trajectory optimization and 2) the transmit power optimization, respectively, by introducing auxiliary variables and leveraging the concave-convex procedure. Then, we develop a joint trajectory and transmit power algorithm via tailoring the successive convex approximation and alternating descent method. We further improve the algorithm by maximizing the throughput instead of minimizing the completion time in the transmit power optimization process. The improved algorithm not only reduces the computational complexity but also enhances the achieved performance. In addition, simulation results demonstrate the superior performance of the proposed algorithms under various parameter configurations.

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In this paper, a corner block list-a new efficient topological representation for non-slicing floorplan is proposed with applications to VLSI floorplan and building block placement. Given a corner block list, it takes only linear time to construct the floorplan. Unlike the O-tree structure, which determines the exact floorplan based on given block sizes, corner block list defines the floorplan independent of the block sizes. Thus, the structure is better suited for floorplan optimization with various size configurations of each block. Based on this new structure and the simulated annealing technique, an efficient floorplan algorithm is given. Soft blocks and the aspect ratio of the chip are taken into account in the simulated annealing process. The experimental results demonstrate the algorithm is quite promising.