Integrated sensing and communication (ISAC) is a promising paradigm to provide both sensing and communication (S&C) services in vehicular networks. However, the power of echo signals reflected from vehicles may be too weak to be used for future precise positioning, due to the practically small radar cross section of vehicles with random reflection/scattering coefficient. To tackle this issue, we propose a novel mutual assistance scheme for intelligent surface-mounted vehicles, where S&C are innovatively designed to assist each other for achieving an efficient win-win integration, i.e., sensing-assisted phase shift design and communication-assisted high-precision sensing. Specifically, we first derive closed-form expressions of the echo power and achievable rate under uncertain angle information. Then, the communication rate is maximized while satisfying sensing requirements, which is proved to be a monotonic optimization problem on time allocation. Furthermore, we unveil the feasible condition of the problem and propose a polyblock-based optimal algorithm. Simulation results validate that the performance trade-off bound of S&C is significantly enlarged by the novel design exploiting mutual assistance in intelligent surface-aided vehicular networks.

翻译：集成感知与通信（ISAC）是车载网络中同时提供感知与通信（S&C）服务的一种有前景的范式。然而，由于实际车辆具有随机反射/散射系数的雷达散射截面较小，从车辆反射的回波信号功率可能过于微弱，难以用于未来的高精度定位。为解决这一问题，我们针对搭载智能表面的车辆提出了一种新颖的互惠辅助方案，其中S&C被创新性地设计为相互辅助，以实现高效的共赢集成，即感知辅助的相移设计与通信辅助的高精度感知。具体而言，我们首先推导了在角度信息不确定条件下回波功率和可达速率的闭式表达式。随后，在满足感知需求的同时最大化通信速率，该问题被证明是关于时间分配的单调优化问题。此外，我们揭示了该问题的可行条件，并提出了一种基于多边形块的最优算法。仿真结果验证了，通过利用智能表面辅助车载网络中的互惠辅助这一新颖设计，S&C的性能权衡边界得到了显著扩展。