标题： 基于后向散射设备的集成感知与通信：帕累托优化框架 显示英文标题

标题： Backscatter Device-aided Integrated Sensing and Communication: A Pareto Optimization Framework

摘要： 集成感知与通信（ISAC）系统在密集遮挡的城市和非视距场景中可能会遇到显著的性能退化，从而限制了其在实际部署中的有效性。 为应对这些挑战，本文提出了一种背散射设备（BD）辅助的ISAC系统，该系统利用环境中自然分布的被动BD来提升性能。 这些环境设备可以通过提供额外的反射信号路径来提高感知精度和通信可靠性。 在该系统中，我们定义了描述感知互信息（SMI）与通信速率之间权衡的帕累托边界，以提供其设计的基本见解。 为了推导该边界，我们在正交频分复用（OFDM）框架内构建了一个性能优化问题，通过联合优化时间-频率资源元素（RE）分配、发射功率管理和BD调制决策来实现。 为解决该问题的非凸性，我们将其分解为三个子问题，并通过块坐标下降（BCD）算法迭代求解。 具体而言，RE子问题使用逐次凸逼近（SCA）方法解决，功率子问题使用增强拉格朗日结合水填充方法求解，BD调制子问题使用半定松弛（SDR）方法解决。 此外，我们通过展示其对双基地ISAC场景和MIMO设置的适应性，证明了所提系统的通用性。 最后，大量的仿真结果验证了所提系统的有效性及其相对于现有最先进ISAC方案的优越性能。 显示英文摘要

摘要： Integrated sensing and communication (ISAC) systems potentially encounter significant performance degradation in densely obstructed urban and non-line-of-sight scenarios, thus limiting their effectiveness in practical deployments. To deal with these challenges, this paper proposes a backscatter device (BD)-assisted ISAC system, which leverages passive BDs naturally distributed in underlying environments for performance enhancement. These ambient devices can enhance sensing accuracy and communication reliability by providing additional reflective signal paths. In this system, we define the Pareto boundary characterizing the trade-off between sensing mutual information (SMI) and communication rates to provide fundamental insights for its design. To derive the boundary, we formulate a performance optimization problem within an orthogonal frequency division multiplexing (OFDM) framework, by jointly optimizing time-frequency resource element (RE) allocation, transmit power management, and BD modulation decisions. To tackle the non-convexity of the problem, we decompose it into three subproblems, solved iteratively through a block coordinate descent (BCD) algorithm. Specifically, the RE subproblem is addressed using the successive convex approximation (SCA) method, the power subproblem is solved using an augmented Lagrangian combined water-filling method, and the BD modulation subproblem is tackled using semidefinite relaxation (SDR) methods. Additionally, we demonstrate the generality of the proposed system by showing its adaptability to bistatic ISAC scenarios and MIMO settings. Finally, extensive simulation results validate the effectiveness of the proposed system and its superior performance compared to existing state-of-the-art ISAC schemes.