标题： 多载波ISAC：非理想条件下的波形设计、信号处理和学习进展 显示英文标题

标题： Multicarrier ISAC: Advances in Waveform Design, Signal Processing and Learning under Non-Idealities

摘要： 本文探讨了5G和新兴6G无线网络中的集成感知与通信(ISAC)主题。 ISAC系统在共享、拥塞甚至竞争的频谱中运行，旨在同时实现无线通信和射频(RF)感知的高性能。 预期的好处包括更高效地利用频谱、功率、硬件(HW)和天线资源。 聚焦于多载波(MC)系统，这是最常用的通信波形，它探索了波形与多天线收发器信号处理的协同设计和优化，用于ISAC的单基地和双基地感知应用。 此外，还考虑了在实际收发器实现中的非理想性所带来的挑战，以及如何克服甚至利用这些挑战的高实用性的技术。 为了在高度动态的无线电环境和目标场景中运行，涵盖了基于模型的结构化优化和基于学习的方法论，评估它们在现实条件下的适应性和学习能力。 本文展示了以通信为中心和以雷达感知为中心的方法之间的权衡，旨在密集使用的频谱中实现优化的平衡。 显示英文摘要

摘要： This paper addresses the topic of integrated sensing and communications (ISAC) in 5G and emerging 6G wireless networks. ISAC systems operate within shared, congested or even contested spectrum, aiming to deliver high performance in both wireless communications and radio frequency (RF) sensing. The expected benefits include more efficient utilization of spectrum, power, hardware (HW) and antenna resources. Focusing on multicarrier (MC) systems, which represent the most widely used communication waveforms, it explores the co-design and optimization of waveforms alongside multiantenna transceiver signal processing for communications and both monostatic and bistatic sensing applications of ISAC. Moreover, techniques of high practical relevance for overcoming and even harnessing challenges posed by non-idealities in actual transceiver implementations are considered. To operate in highly dynamic radio environments and target scenarios, both model-based structured optimization and learning-based methodologies for ISAC systems are covered, assessing their adaptability and learning capabilities under real-world conditions. The paper presents trade-offs in communication-centric and radar-sensing-centric approaches, aiming for an optimized balance in densely used spectrum.