The development of integrated sensing and communication (ISAC) technique makes it possible to exploit echoes of communication signals to localize aerial eavesdropper (AE) and enhance the secrecy performance. In this paper, we investigate the sensing-assisted secure precoding design in rate-splitting multiple access (RSMA) systems. In particular, we aim at maximizing the minimum achievable rate among all users while satisfying the Cramér-Rao bound (CRB) constraint for AE’s 2-dimensional angle estimation and protecting both common stream and private streams from being intercepted. We first consider the ideal case where perfect CSI is available and propose an iterative optimization algorithm, where successive convex approximation technique, fractional programming, and the Schur complement condition are leveraged to handle the non-convex constraints and objective function. This scenario is further extended to a more general case with channel estimation errors, for which we propose a robust precoding design algorithm to ensure worst-case performance. Simulation results validate the effectiveness of leveraging the sensing capability to enhance secrecy performance and show that the RSMA scheme is able to achieve higher user rates and lower eavesdropping rates compared to spatial division multiple access (SDMA)-based sensing-assisted secure communication system. Furthermore, we demonstrate the trade-off between achievable minimum user rate and sensing accuracy.

In this paper, we investigate joint trajectory and beamforming design for unmanned aerial vehicle (UAV)-relayed integrated sensing and communication (ISAC) systems with mobile edge eomputing (MEC) under the clutter environment. Due to the limited on-board computing capability, the UAV has to offload sensing echoes to the base station (BS) for efficient processing. A novel relay-based ISAC-then-offload frame structure is considered. We aim to maximize the throughput of the BS-UAV-user relaying link while ensuring sensing accuracy and efficient sensing data offloading. The non-convex problem is solved using an alternating optimization algorithm based on successive convex approximation (SCA). Simulation results illustrate that our proposed algorithm achieves near-optimal communication performance while guaranteeing sensing accuracy, addressing the balance between the communication and sensing performance. Furthermore, we evaluate the impact of critical system parameters including sensing constraints, power control factor, and UAV flight duration on communication performance, and explore the trade-offs between energy efficiency and spectral efficiency under varying sensing data intensity and offloading duration.

Integrated sensing and communications (ISACs) technique is being considered as a promising technique for future networks. Facing the diverse services required for different nodes, in this article, we investigate the ISAC systems with simultaneous public and confidential transmission, where an ISAC base station simultaneously provides integrated public and confidential services for different nodes and performs target tracking using the echo of communication signals. We study the optimization of public, confidential signals, and artificial noise (AN) in both the time-invariant and time-varying channels. Our primary goal is to minimize the differences between the actual and desired beampatterns, while meeting the constraints of the public message rate (PMR) and confidential message secrecy rate (CMSR). For time-invariant channels with typically negligible estimation error of the channel state information (CSI), we aim to synthesize the target beampattern while satisfying the PMR and CMSR constraints. To this end, we first propose a successive convex approximation-based algorithm to jointly design the transmit covariance matrices and the AN covariance matrix; we then propose a low-complexity two-stage algorithm that is more suitable for the practical implementation. The proposed algorithms are further extended to the time-varying channels where the estimated may contain large errors. Simulation results are provided and verify the effectiveness of the proposed algorithms.

Directional antennas have received much attention recently in multihop ad hoc networks, due to such benefits as increased transmission range, reduced co-channel interference, improved spatial reuse, and reduced susceptibility to jamming. However, existing random access scheduling schemes with directional antennas suffer from the issues of deafness and high probability of collisions. Moreover, such schemes cannot provide throughput and delay guarantees. In this paper, we propose a topology-transparent scheduling algorithm in mobile multihop ad hoc networks with directional antennas, to overcome these deficiencies. The proposed algorithm fully exploits the benefits of directional antennas and utilizes both assigned and unassigned time slots efficiently. We study the performance of our algorithm analytically and by simulation. The results show that the performance of the proposed algorithm, in certain cases, can be comparable to that of some topology-dependent algorithms designed for static networks. Yet, the proposed algorithm also performs well even when the network topology is dynamic, as in mobile networks.