CIF: Medium: Collaborative Research: Low-Resolution Sampling with Generalized Thresholds

到岸价：介质：合作研究：低分辨率采样与广义的samplingsJian Li，Lee Swindlehurst，和Mojtaba Soltanalian摘要在数字信号处理应用中，对感兴趣的信号进行量化是必要的第一步。当对宽频带上的信号感兴趣时，会遇到采样率、幅度量化精度、成本和功耗之间的基本折衷。研究人员研究了具有一般阈值的低分辨率采样技术，这些技术负担得起，技术上可行，易于应用，节能，符合技术趋势。例如，成功的毫米波（mm-wave）大规模多输入多输出实现可以提供容量和频谱效率的巨大增益，这可能对我们使用它们的几乎所有无线系统的性能产生革命性影响：在家里、在工作中、在学校、通过公共交通或飞机通勤、购物、在餐馆、娱乐场所、体育赛事，除了消费类应用，我们的系统还可以用于许多军事和安全相关的场景。该项目涉及开发动态节能和成本效益采样技术的基础知识，并应用工程原理来满足几个重要和相关应用的关键需求。具体而言，该项目涉及解决重大的开放性问题，包括确定性可识别性，性能界限，以及阈值模式对频谱感知和阵列处理，射频干扰缓解和毫米波通信的影响，以获得对具有一般阈值的低分辨率采样新范式的基本见解，设计新颖的信号处理算法，包括用于增强性能的有效和高效的稀疏信号恢复技术和参数最大似然方法，以及使用测量数据来评估和演示性能。该项目还涉及通过将实际设计和解决问题的技术纳入教育课程，为学生在21世纪的工程做好准备。

CIF: Medium: Collaborative Research:Low-Resolution Sampling with Generalized ThresholdsJian Li, Lee Swindlehurst, and Mojtaba Soltanalian AbstractQuantization of signals of interest is a necessary first step in digital signal processing applications. When signals across a wide frequency band are of interest, a fundamental tradeoff between sampling rate, amplitude quantization precision, cost, and power consumption is encountered. The investigators study low resolution sampling techniques with general thresholds, which are affordable, technically feasible, easy to apply, energy-efficient, and consistent with technological trends. The enormous gains in capacity and spectral efficiency, for example, that could be provided by a successful millimeter wave (mm-wave) massive multiple-input multiple output implementation could have a revolutionary effect on the performance of wireless systems nearly everywhere we use them: at home, at work, at school, commuting via public transportation or by plane, shopping, at restaurants, recreational venues, sporting events, and so on. Besides consumer applications, there are many military- and security-related scenarios where our systems could be used.This project involves advancing fundamental knowledge in developing dynamic energy-efficient and cost-effective sampling techniques and applies engineering principles to address the critical needs of several important and related applications. Specifically, this project involves addressing significant open questions, including deterministic identifiability, performance bounds, and impact of thresholding pattern on spectrum sensing and array processing, radio frequency interference mitigation, and mm-wave communications to gain fundamental insights into the novel paradigm of low resolution sampling with general thresholds, devising novel signal processing algorithms, including effective and efficient sparse signal recovery techniques and parametric maximum likelihood methods for enhanced performance, and evaluating and demonstrating the performance using measured data. This project also involves preparing students for engineering in the 21st century through the incorporation of practical design and problem-solving techniques into both the education curriculum.