CAREER: Scalable and reconfigurable time-based circuits and systems for high-resolution large antenna arrays

由数百个天线单元组成的超大型天线阵(LAA)有望提供前所未有的空间分辨率，不仅可以使许多关键基础设施技术使用毫米波无线通信，还会带来令人兴奋的概念，如用于多用户无线通信的全息表面、用于自动驾驶车辆的六维定位、用于深空行星探测的高速通信链路，以及用于探测多个物体的汽车雷达。然而，这些大规模阵列的信号处理带来了更高的能耗和更不准确的定位的挑战。由于高度复杂的信号处理和不完善的空间滤波，传统的与真实世界信号交互的相控阵收发信机在低延迟跟踪和定标方面面临着一些障碍。这些缺陷导致性能急剧下降，危及新兴无线技术的发展。为了克服这些根本的挑战，本研究试图使用结合可扩展的时基电路和系统的离散时间延迟补偿技术，以便未来的LAA能够精确地估计到达方向，有效地消除多个干扰，并自主地优化物理前端收发机。这项研究工作与首席研究员的教育职业目标相结合，即通过与国家实验室和行业的积极合作，通过提高学生的教育、意识和准备来增强高中和本科生的学习体验。这项研究的目的是利用离散时间延迟补偿时基电路和系统来变换多天线相控阵，具有宽延迟范围和高精度的能量高效的空间信号处理和低延迟波束捕获。基于非均匀采样的可扩展离散时间数据转换器的几种设计技术将构成能够处理千兆赫信号带宽的延迟补偿空间信号处理器的基础。首先，将演示一种离散时间延迟补偿空间信号处理器，其具有可变的近场和远场LAA的增益和延迟范围。其次，延迟补偿技术将在基于线性时间的矩阵乘法数据转换器中引入，该转换器使用基于人工智能的自初始化偏差优化技术进行优化，以展示更快和更节能的收敛。第三，发展可扩展的系统级空间阵列模型，包括宽扫描角度、高速信号带宽、大量天线单元、低延迟到达方向以及实时延迟阵列中的分段，以研究它们对未来LAA的频谱效率和能量效率的影响。通过这些全面的研究，该项目将在宽带局域网中确立离散时间延迟补偿的优势。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Extremely large antenna arrays (LAA) comprising hundreds of antenna elements promise to provide unprecedented spatial resolutions that can not only enable many critical infrastructure technologies using millimeter-wave wireless communications but also usher in exciting concepts such as holographic surfaces for multi-user wireless communications, six-dimensional positioning for autonomous vehicles, high-speed communication links for deep-space planetary explorations, and automobile radars for detecting multiple objects. However, the signal processing at these large-scale arrays bring challenges of higher energy consumption and less accurate localization. Conventional phased array transceivers, which interface with the real-world signals, face several impediments in low-latency tracking and scaling due to highly complex signal processing and imperfect spatial filtering. Such imperfections result in drastic performance degradation endangering evolution of emerging wireless technologies. To overcome these fundamental challenges, this research seeks to use discrete-time delay-compensating techniques incorporating scalable time-based circuits and systems so that future LAAs can estimate direction-of-arrival precisely, cancel multiple interferences efficiently, and optimize the physical front-end transceivers autonomously. This research effort is integrated with the principal investigator's educational career goal of enhancing high-school and undergraduate learning experience by increasing education, awareness and preparation of the students through active collaborations with national labs and industry. The objective of this research is to transform multi-antenna phased arrays using discrete-time delay-compensating time-based circuits and systems with wide delay ranges and high precision for both energy-efficient spatial signal processing and low-latency beam acquisition. Several design techniques with non-uniform-sampling-based scalable discrete-time data converters will form the basis of delay-compensating spatial signal processor capable of handling gigahertz signal bandwidth. First, a discrete-time delay-compensating spatial signal processor will be demonstrated with variable gain and delay ranges for near-field and far-field LAAs. Second, the delay-compensating technique will be instituted in linear time-based matrix-multiplying data converters optimized using artificial-intelligence based self-initializing bias optimization techniques to demonstrate faster and energy-efficient convergence. Third, scalable system-level models for spatial arrays incorporating wide scan angles, high-speed signal bandwidth, large number of antenna elements, low-latency direction-of-arrival, and segmentation in true-time-delay arrays will be developed to study their effects on both spectral efficiency and energy efficiency for future LAAs. Through these comprehensive studies, the project will establish the advantages of discrete-time delay-compensating in wideband LAAs.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.