Dual-Function Radar Communcation System: Joint Design and Optimization

联合通信和传感（JCAS）技术被认为是解决下一代无线网络及以后频谱拥塞问题的一种有前途的技术，其中通信和雷达系统将集成在一个硬件平台上，并在同一频率上同时运行。dfrc设计项目的总体目标是设计、分析和验证能够提高频谱效率的创新JCAS系统。与现有系统相比，为了在通信和传感功能之间有更好的权衡性能，我们将在系统的设计原则中进行范式转换，从基于系统主要功能实现第二功能的现有原则转变为同时考虑两种功能的联合设计原则。为了实现这一点，我们的设计中出现了以下挑战：i)如何定义JCAS的性能指标？ii)如何设计满足通信和传感所需特性的波形？iii)如何利用MIMO系统中波束的空间特性，同时探测目标并为不同方位的用户提供服务？iv)如何处理杂波信号以实现鲁棒和高精度传感？v)在实际情况下，JCAS系统在这两种功能上能获得多少性能增益？在本项目中，将利用优化理论、统计信号处理和深度学习技术，提出理论分析框架、新型波形设计、混合波束形成算法、杂波抑制和参数估计程序来解决这些问题。此外，还将在实际环境下建立一个试验台来验证所提出的方案。研究结果将透过多项宣传活动向公众公布，以提高公众对毫米波的认识，并促进相互了解和可持续发展。

The joint communication and sensing (JCAS) technology is considered as a promising technology for solving the spectrum congestion problem in next generation of wireless networks and beyond, where the communication and radar system will be integrated in one hardware platform and operate simultaneously over the same frequency. The overarching goal of the DFRC-DESIGNproject is to design, analyze and validate innovative JCAS systems capable of achieving improved spectrum efficiency. To have a better trade-off performance between communication and sensing functionalities compared to the existing systems, we will make aparadigm shift in the design principles of the system from the existing principle of realizing a second function based on the primaryfunction of the system to the joint design principle that considers both functions simultaneously. To achieve this, the following challenges arise in our design: i) How to define the performance metrics of JCAS? ii) How to design waveforms that satisfy the properties required for both communication and sensing? iii) How to exploit the spatial characteristics of the beam in a MIMO system to simultaneously detect targets and serve users in different orientations? iv) How to tackle the clutter signal for robust and highaccuracy sensing? v) How much performance gain can the JCAS system achieve for both functions in realistic situations? In this project, a theoretical analysis framework, novel waveform design, hybrid beamforming algorithms, clutter suppression and parameterestimation procedures will be proposed to address these issues, using optimization theory, statistical signal processing and deeplearning techniques. Furthermore, a testbed will be set up under realistic settings to demonstrate the proposed schemes. The results will be disseminated to the public through several communication activities to improve public awareness of milimeter waves and to promote mutual understanding and sustainable development.