OFDM-ISAC系统中用于时延-多普勒感知的二维互素导频
2D Coprime Pilots for Delay-Doppler Sensing in OFDM-ISAC Systems
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中文总结 AI 辅助
针对OFDM-ISAC系统时延-多普勒参数估计的挑战，采用感知互信息为指标，提出二维互素导频条件与Adam引导迭代优化算法，提升感知性能。
中文摘要 AI 辅助
集成感知与通信（ISAC）被设想为赋予未来6G系统无缝感知能力。为支持以最小通信开销实现高效感知，嵌入通信帧的稀疏导频已成为有前景的解决方案。现有研究在最大化无歧义感知区域方面取得了良好成果，但由于缺乏统一性能指标和有效导频设计框架，同时最大化感知区域与感知精度仍具挑战性。本文针对正交频分复用（OFDM）-ISAC系统中时延-多普勒（DD）参数估计，联合优化无歧义感知区域与感知精度，采用感知互信息（SMI）作为统一性能指标表征整体感知能力。具体而言，通过系统解决感知歧义并优化感知精度，将联合优化建模为SMI最大化问题。特别地，基于广义贝祖恒等式，推导了二维（时频）互素条件，据作者所知，这是文献中首个实现DD参数唯一估计的充要条件。在该无歧义条件下，进一步提出Adam引导迭代优化（AGIR）算法以优化感知精度。数值结果表明，所提框架相较于现有设计具有优势，这得益于二维互素条件在优化感知精度方面提供的自由度。
英文摘要
Integrated Sensing and Communication (ISAC) is envisioned to endow future 6G systems with seamless sensing capabilities. To support efficient sensing with minimum communication overhead, sparse pilots embedded within communication frames have emerged as a promising solution. Along this line of research, existing studies have achieved engaging results in maximizing the unambiguous sensing region. However, jointly maximizing the sensing region and sensing accuracy remains challenging due to the lack of a unified performance metric and an effective pilot design framework. This paper jointly optimizes the unambiguous sensing region and sensing accuracy for estimating delay-Doppler (DD) parameters in Orthogonal Frequency Division Multiplexing (OFDM)-ISAC systems, where sensing mutual information (SMI) is adopted as a unified performance metric to characterize the overall sensing capability. Specifically, the joint optimization is formulated as an SMI maximization problem by systematically resolving sensing ambiguity and optimizing sensing accuracy. In particular, based on the generalized Bezout identity, we derive a 2D (timefrequency) coprime condition, which, as far as the authors know, is the first necessary and sufficient condition to achieve the unique estimation of DD parameters in the literature. Under this unambiguous condition, we further propose an Adam-Guided Iterative Refinement (AGIR) algorithm to optimize the sensing accuracy. Numerical results demonstrate the advantage of the proposed framework over existing designs, owing to the freedom offered by the 2D coprime condition in optimizing the sensing accuracy.
发表机构
- The Hong Kong University of Science and Technology（香港科技大学）
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