RIS辅助的以用户为中心的ICSC系统框架：时延优化与设计
A Framework of RIS-assisted ICSC User-centric Based Systems: Latency Optimization and Design
AI总结：
本文提出RIS辅助的以用户为中心ICSC系统框架，通过将时延最小化问题解耦为计算设置与波束成形两个子问题交替优化，推导卸载量闭式解并提出低复杂度算法，仿真验证了框架有效性。
摘要：
本文研究了一个面向可重构智能表面（RIS）辅助的集成通信、感知与计算（ICSC）系统的综合框架，并以用户为中心。研究涵盖两种场景：通用多用户设备（UE）场景和简化的单UE场景。为满足对时间高效的感知的关键需求，我们研究了时延最小化问题，并受限于UE发射功率、雷达信号与干扰加噪声比（SINR）、RIS相移以及计算能力的约束。为解决多UE场景中形成的非凸问题，我们将原问题解耦为两个子问题，其中计算设置与波束成形设置交替优化。具体而言，对于计算设置，我们推导了卸载量的闭式解，并提出一种基于二分搜索法的低复杂度算法来优化边缘计算资源分配。此外，我们采用两种等价变换来应对与有源和无源波束成形相关的子问题目标函数（OF）中非凸比和形式带来的挑战。随后结合多种技术来处理这些子问题。进一步地，针对简化的单UE场景，开发了一种提供闭式解的低复杂度算法。最后，仿真结果证实了所提框架的有效性。
英文摘要：
This paper studies a comprehensive framework for reconfigurable intelligent surface (RIS)-assisted integrated communication, sensing, and computation (ICSC) systems with a User-centric focus. The study encompasses two scenarios: the general multi-user equipment (UE) scenario and the simplified single-UE scenario. To satisfy the critical need for time-efficient sensing, we investigate the latency minimization problem, subject to constraints on UEs' transmit power, radar signal-to-interference-plus-noise-ratio (SINR), RIS phase shift, and computation capability. To address the formulated non-convex problem in the multi-UE scenario, we decouple the original problem into two subproblems, where the computational and beamforming settings are optimized alternately. Specifically, for the computational settings, we derive a closed-form solution for the offloading volume and propose a low-complexity algorithm based on the bisection search method to optimize the edge computing resource allocation. Additionally, we employ two equivalent transformations to address the challenge posed by the non-convex sum-of-ratios form in the objective function (OF) of the subproblem related to active and passive beamforming. Several techniques are then combined to address these subproblems. Furthermore, a low-complexity algorithm that offers closed-form solutions is developed for the simplified single UE scenario. Finally, simulation results substantiate the effectiveness of the proposed framework.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
