迈向移动毫米波网络中可靠且准确的预测式ISAC

中文摘要 AI 辅助

集成感知与通信（ISAC）系统为波束跟踪提供了一种有前景的框架，该框架增强了信道感知能力，并提高了移动毫米波（mmWave）网络中的通信可靠性。受此启发，我们提出了一种低复杂度、模型驱动的信道状态信息（CSI）框架，该框架在支持ISAC的系统中集成了信道预测能力。为降低CSI获取和上行链路反馈的开销，所提出的框架利用预测的目标感知参数，从视距（LoS）和检测到的非视距（NLoS）分量构建部分CSI。利用该部分CSI，我们制定了一个波束成形优化问题，该问题在每用户通信约束下最小化最差目标的Cramér-Rao界（CRB）。该问题是非凸且高度非线性的；因此，我们利用连续凸近似（SCA）和基于Schur补的分解技术开发了一种高效的次优解，并与其他方法相比评估了其复杂度。此外，由于获取信道路径的绝对相位可能需要额外的导频资源，我们制定了一种不假设该知识的鲁棒波束成形设计，并提出了一种基于样本平均的解决方案。数值结果表明，与传统的方案（如基于通信的定位与跟踪以及分离的感知与通信）相比，基于ISAC的鲁棒信道预测与定位框架显著提高了预测精度和链路可靠性。这些结果凸显了ISAC在可靠、自适应、高频且易受阻塞的无线网络中的潜力。此外，所提出框架的性能在严重阻塞场景下进行了评估，进一步证明了其增强的网络可靠性。

英文摘要

Integrated sensing and communications (ISAC) systems offer a promising framework for beam tracking, which enhances channel awareness and improves communication reliability in mobile millimeter wave (mmWave) networks. Motivated by this, we propose a low-complexity, model-driven channel state information (CSI) framework with integrated channel prediction capability in ISAC-enabled systems. To reduce the overhead of CSI acquisition and uplink feedback, the proposed framework leverages predicted target sensing parameters to construct partial CSI from both line-of-sight (LoS) and detected non-line-of-sight (NLoS) components. Exploiting this partial CSI, we formulate a beamforming optimization problem that minimizes the worst targets' Cramér-Rao bound (CRB) under per-user communication constraints. This problem is non-convex and highly non-linear; therefore, we develop an efficient suboptimal solution using successive convex approximation (SCA) and Schur-complement-based decomposition techniques, and we evaluate its complexity in comparison with other approaches. Moreover, since obtaining the absolute phase of the channel paths may require additional pilot resources, we formulate a robust beamforming design that does not assume this knowledge, and propose a solution based on sample averaging. Numerical results demonstrate that the ISAC-based robust channel prediction and localization framework significantly improves prediction accuracy and link reliability compared with conventional schemes, such as communication-based localization and tracking and separated sensing and communication. These results highlight the potential of ISAC for reliable, adaptive, and high-frequency, blockage-prone wireless networks. Furthermore, the performance of the proposed framework is evaluated under severe blockage scenarios, which further demonstrates enhanced network reliability.

发表机构

• Technische Universität Berlin（柏林工业大学）
• Technische Universität Darmstadt（达姆施塔特工业大学）

机构由 AI 辅助整理，请以论文原文为准。