发表机构
San Diego State University; University of California, San Diego（圣地亚哥州立大学; 加州大学圣地亚哥分校）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对异步上行链路OFDM-ISAC系统，提出数据辅助的平均场变分贝叶斯框架，联合推断多类参数，利用检测数据符号细化传感参数，性能优于多种基线方法，凸显同步感知设计的重要性。
AI 中文摘要
集成传感与通信（ISAC）被视为第六代无线网络的关键技术，允许传感和通信操作共同利用同一频谱与硬件基础设施。然而，在实际上行链路ISAC系统中，定时偏移（TO）和载波频率偏移（CFO）会在子载波和OFDM符号间引入相位失真，严重降低数据检测和传感参数估计的性能。本文针对异步上行链路OFDM-ISAC系统，提出一种数据辅助的变分贝叶斯（VB）框架。具体而言，接收信号被建模为稀疏多径叠加，联合推断发送数据符号、复路径增益、空间频率、延迟-多普勒参数及同步参数。为实现可处理的推断，开发了一种平均场VB算法，其中采用von Mises分布对角度和延迟-多普勒相位参数进行无网格更新，同时采用Gamma-Gaussian先验以促进路径稀疏性。该框架的关键特性是其数据辅助传感能力：在基于导频的初始估计后，将检测到的数据符号用作额外观测以细化信道和传感参数，这大幅增加了有效传感资源，且无需额外导频开销。仿真结果表明，所提方法在符号错误率、信道重构精度、路径参数估计、TO/CFO估计及三维定位精度方面，优于SAGE、SBL、AB2FM和仅导频VB基线方法。结果还表明，忽略TO和CFO会导致传感性能严重下降，凸显了面向ISAC系统的同步感知且数据辅助的接收机设计的重要性。
英文摘要
Integrated sensing and communication (ISAC) is regarded as a key technology for sixth-generation wireless networks, allowing sensing and communication operations to jointly utilize the same spectrum and hardware infrastructure. However, in practical uplink ISAC systems, timing offset (TO) and carrier-frequency offset (CFO) introduce phase distortions across subcarriers and OFDM symbols, which can severely degrade both data detection and sensing-parameter estimation. In this paper, we propose a data-aided variational Bayesian (VB) framework for asynchronous uplink OFDM-ISAC systems. Specifically, the received signal is modeled as a sparse multipath superposition, where the transmitted data symbols, complex path gains, spatial frequencies, delay-Doppler parameters, and synchronization parameters are jointly inferred. To enable tractable inference, we develop a mean-field VB algorithm in which von Mises distributions are used for gridless updates of the angular and delay-Doppler phase parameters, while a Gamma-Gaussian prior is adopted to promote path sparsity. A key feature of the proposed framework is its data-aided sensing capability: after initial pilot-based estimation, the detected data symbols are exploited as additional observations to refine the channel and sensing parameters. This substantially increases the effective sensing resources without requiring extra pilot overhead. The simulation results demonstrate that the proposed approach achieves superior performance compared with SAGE, SBL, AB2FM, and pilot-only VB baselines in terms of symbol error rate, channel reconstruction accuracy, path-parameter estimation, TO/CFO estimation, and 3D localization accuracy. The results also demonstrate that ignoring TO and CFO leads to severe sensing degradation, highlighting the importance of synchronization-aware and data-aided receiver design for ISAC systems.
