ConSenT: Connected Sensing Techniques: Cooperative Radar Networks Using Joint Radar and Communication Waveforms

目前，信息和通信技术(ICT)占全球温室气体(GHG)排放量的4%。尽管欧盟的脱碳计划要求到2030年减少40%的温室气体排放，但由于移动设备和无线网络设施的数量不断增加，ICT引发的温室气体排放量预计将增加。在这种背景下，集成传感和通信(ISAC)技术作为一种潜在的解决方案受到了人们的关注，使无线硬件能够同时用于传感和通信功能。虽然ISAC的最新进展为无线系统开辟了新的机遇，但多个ISAC系统的共存和合作以实现低功耗的扩展无线网络迄今尚未被探索。因此，研究项目旨在设计和开发互联传感技术(同意)，为即将到来的ISAC网络提供独特的机会。通过协作集成相邻和/或分布式网络实现的增强传感能力有助于构建高效的ISAC网络。我们设定了两个目标，以在不同的连接感知场景中提供同意。非相干连接感知方法允许多个ISAC节点通过利用多静态反射进行协作。探讨了ISAC的联合收发信机设计，为ISACS的网络化奠定了基础。此外，还研究了同步的ISAC节点之间的相干协作，以实现多个ISAC节点的最优通信和感知度量。同意方法侧重于通过利用跨学科方法来发展节能网络，包括通信和雷达信号处理、发射/接收波束形成优化、随机几何建模和机器学习。这项研究项目将产生

Currently, information and communication technology (ICT) accounts for 4% of global greenhouse gas (GHG) emissions. Although EU's decarbonization planrequires 40% reduction of GHG emissions by 2030, those evoked by ICT are predicted to increase due to the growing number of mobile devices and wirelessnetwork facilities. In this context, Integrated sensing and communication (ISAC) technology has been gaining attention as a potential solution, enabling thereuse of wireless hardware for both sensing and communication functionalities. While recent progresses of ISAC open up new opportunities for wirelesssystems, co-existence and cooperation of multiple ISAC systems to realize extended wireless networks with reduced power consumption have not beenexplored to date. Therefore, research project aims to design and develop connected sensing techniques (ConSenT), which provide unique opportunities forupcoming ISAC networks. Enhanced sensing capabilities achieved by cooperatively integrating adjacent and/or distributed networks contribute to build powerefficientISAC networks. We set two objectives to deliver ConSenT in different connected sensing scenarios. Non-coherent connected sensing approach allowsmultiple ISAC nodes cooperating by exploiting multi-static reflections. Joint transceiver design of ISAC is explored to establish the foundation of networkedISACs. Also, coherent cooperation of the synchronized ISAC nodes is investigated to achieve the optimal communication and sensing metrics of the multipleISAC nodes. ConSenT approaches focus on developing energy-efficient networks by exploiting interdisciplinary methodologies, including communication andradar signal processing, transmit/receive beamforming optimization, modeling of stochastic geometry, and machine learning. The research project will result