MIMO-OFDM ISAC教程：从远场到近场
A Tutorial on MIMO-OFDM ISAC: From Far-Field to Near-Field
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中文总结 AI 辅助
本文介绍了MIMO-OFDM ISAC系统，从远场到近场的参数估计方法及感知算法，探讨其基本原理和未来研究方向。
中文摘要 AI 辅助
集成感知与通信（ISAC）是未来第六代（6G）移动通信网络的关键应用场景之一，其中通信和感知（C&S）服务通过共享无线频谱、信号处理模块、硬件和网络基础设施同时提供。这种集成受到6G技术趋势的加强，如更密集的网络节点、更大的天线阵列、更宽的带宽、更高的频率带和更高效的频谱和硬件资源利用，这些趋势激励并增强了感知能力。作为当前通信系统中占主导地位的波形，正交频分复用（OFDM）仍预计将成为6G中非常有竞争力的技术，因此需要彻底研究OFDM ISAC的潜力和挑战。因此，本文旨在提供一个全面的ISAC系统教程，该系统由大规模多输入多输出（MIMO）和OFDM技术启用，并讨论其基本原理、优势和使能信号处理方法。为此，首先介绍了一个统一的MIMO-OFDM ISAC系统模型，随后介绍了四个用于在空间、延迟和多普勒域内估计参数的框架，包括并行一域、顺序一域、联合二域和联合三域参数估计。接下来，详细介绍了适用于远场场景的感知算法和性能分析，其中均匀平面波（UPW）传播有效，随后将其扩展到需要考虑均匀球面波（USW）特性的近场场景。最后，本文指出了开放挑战，并概述了MIMO-OFDM ISAC未来研究的有前途的研究方向。
英文摘要
Integrated sensing and communication (ISAC) is one of the key usage scenarios for future sixth-generation (6G) mobile communication networks, where communication and sensing (C&S) services are simultaneously provided through shared wireless spectrum, signal processing modules, hardware, and network infrastructure. Such an integration is strengthened by the technology trends in 6G, such as denser network nodes, larger antenna arrays, wider bandwidths, higher frequency bands, and more efficient utilization of spectrum and hardware resources, which incentivize and empower enhanced sensing capabilities. As the dominant waveform used in contemporary communication systems, orthogonal frequency division multiplexing (OFDM) is still expected to be a very competitive technology for 6G, rendering it necessary to thoroughly investigate the potential and challenges of OFDM ISAC. Thus, this paper aims to provide a comprehensive tutorial overview of ISAC systems enabled by large-scale multi-input multi-output (MIMO) and OFDM technologies and to discuss their fundamental principles, advantages, and enabling signal processing methods. To this end, a unified MIMO-OFDM ISAC system model is first introduced, followed by four frameworks for estimating parameters across the spatial, delay, and Doppler domains, including parallel one-domain, sequential one-domain, joint two-domain, and joint three-domain parameter estimation. Next, sensing algorithms and performance analyses are presented in detail for far-field scenarios where uniform plane wave (UPW) propagation is valid, followed by their extensions to near-field scenarios where uniform spherical wave (USW) characteristics need to be considered. Finally, this paper points out open challenges and outlines promising avenues for future research on MIMO-OFDM ISAC.
