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.

In this paper, we propose a transmit-receiver alternating minimization (TR-AltMin) algorithm for integrated sensing and communication (ISAC) systems in vehicular ad-hoc networks (VANETs) with hybrid analog-digital (HAD) beamforming structure. Given the ideal beamformer for radar and the channel information for communication, consider the minimum beamformer error for radar and the minimum mean square error (MMSE) or weighted MMSE (WMMSE) metric for communication, a weighted summation optimization problem is obtained, and the TR-AltMin algorithm is used to get the optimal results of the HAD beamformer and combiner. Numerical simulation results show that the proposed method has better performance in terms of the communication-radar (C-R) trade-off and C-R functionalities.