Sensing-assisted communication is critical to enhance the system efficiency in integrated sensing and communication (ISAC) systems. However, most existing literature focuses on large-scale channel sensing, without considering the impacts of small-scale channel aging. In this paper, we investigate a dual-scale channel estimation framework for sensing-assisted communication, where both large-scale channel sensing and small-scale channel aging are considered. By modeling the channel aging effect with block fading and incorporating CRB (Cram\'er-Rao bound)-based sensing errors, we optimize both the time duration of large-scale detection and the frequency of small-scale update within each subframe to maximize the achievable rate while satisfying sensing requirements. Since the formulated optimization problem is non-convex, we propose a two-dimensional search-based optimization algorithm to obtain the optimal solution. Simulation results demonstrate the superiority of our proposed optimal design over three counterparts.

翻译：感知辅助通信对于提升集成感知与通信（ISAC）系统的效率至关重要。然而，现有文献大多聚焦于大尺度信道感知，并未考虑小尺度信道老化带来的影响。本文研究了一种面向感知辅助通信的双尺度信道估计框架，该框架同时考虑了大尺度信道感知与小尺度信道老化效应。通过采用块衰落模型刻画信道老化效应，并引入基于克拉美-罗下界（CRB）的感知误差模型，我们在每个子帧内联合优化大尺度检测的时间长度与小尺度更新的频率，以在满足感知要求的前提下最大化可达速率。由于所构建的优化问题具有非凸性，我们提出了一种基于二维搜索的优化算法以获取最优解。仿真结果表明，相较于三种对比方案，我们所提出的优化设计具有显著优越性。