Blind Carbon Copy on Dirty Paper: Seamless Spectrum Underlay made Practical

脏纸上的盲文复写：无缝频谱底层变得实用

基本信息

批准号：
2118002
负责人：
Nikolaos Sidiropoulos
金额：
$ 38.8万
依托单位：
University of Virginia Main Campus
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-07-01 至 2025-06-30
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2118002&HistoricalAwards=false
关键词：
Blind Carbon Copy Dirty Paper

项目摘要

From smart homes to smart cars and highways, and from smart health to precision agriculture, emerging technologies will soon demand ubiquitous connectivity for billions of wireless devices. The demand for more spectrum has finally started to outweigh resistance to spectrum reuse. There is currently strong impetus for introducing innovative spectrum sharing modalities that enable improved spectrum utilization and seamless cohabitation, without requiring tight coordination across legacy, scientific, government, military, and commercial users. Spectrum underlay is a promising paradigm towards this end. It provisions secondary transmissions that operate without disturbing the primary user. Practical means of accomplishing this without requiring tight coordination between the primary and the secondary system have remained elusive, however. This project develops practical spectrum underlay solutions which enable reliable secondary communication in scenarios where this would otherwise seem untenable: without primary-secondary coordination or channel state information, under potentially strong and time-varying interference from the primary system. The scope of potential applications includes Internet of Things (IoT), vehicular, and local area (e.g., WiFi) networks in congested spectrum areas.Ensuring United States leadership in spectrum research, technologies, and commercial/scientific applications requires investments in spectrum sharing innovations and developing a well-educated and diverse spectrum workforce. This projects makes contributions towards both of these goals. The proposed research builds upon the principal investigator's prior work on statistical signal processing, machine learning, and matrix theory, as well as practical communications engineering -- an ideal combination to educate and engage diverse graduate and undergraduate students on the board and in the lab. The research will develop state-of-the-art theory and engineering solutions geared towards practical implementation. The scope of the work includes the following synergistic components, organized in five thrusts: T1) Incorporating finite alphabet and error control coding constraints into the basic algebraic framework. T2) Developing multi-access and random interleaving solutions to ``orthogonalize'' multiple secondary transmissions in multiuser settings. T3) Analyzing performance under fading scenarios, with adaptive modulation and coding. T4) Addressing key engineering issues, namely, secondary user synchronization and analog-to-digital conversion, which are challenging when the secondary signal is much weaker than the interfering primary signal. T5) Developing a software radio testbed and conducting experiments to validate the proposed solutions.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.

从智能家居到智能汽车和高速公路，从智能健康到精准农业，新兴技术很快将要求数十亿无线设备实现无处不在的连接。对更多频谱的需求终于开始超过对频谱重用的阻力。目前，人们大力推动引入创新的频谱共享模式，以提高频谱利用率和无缝共存，而无需传统、科学、政府、军事和商业用户之间的紧密协调。频谱底层是实现这一目标的一个有前途的范例。它提供了在不干扰主要用户的情况下运行的辅助传输。然而，在不需要主系统和辅助系统之间紧密协调的情况下实现这一目标的实用方法仍然难以实现。该项目开发了实用的频谱底层解决方案，可在看似站不住脚的场景中实现可靠的辅助通信：在没有主辅助协调或信道状态信息的情况下，在来自主系统的潜在强烈且随时间变化的干扰下。潜在应用范围包括物联网 (IoT)、车辆和频谱拥挤区域的局域（例如 WiFi）网络。确保美国在频谱研究、技术和商业/科学应用方面的领导地位需要对频谱共享创新进行投资培养一支受过良好教育、多元化的劳动力队伍。该项目为这两个目标做出了贡献。拟议的研究建立在首席研究员之前在统计信号处理、机器学习和矩阵理论以及实用通信工程方面的工作基础上，这是教育和吸引董事会和实验室的不同研究生和本科生的理想组合。该研究将开发面向实际实施的最先进的理论和工程解决方案。工作范围包括以下协同组成部分，分为五个主旨： T1）将有限字母表和错误控制编码约束纳入基本代数框架中。 T2) 开发多址和随机交织解决方案，以“正交化”多用户设置中的多个辅助传输。 T3) 使用自适应调制和编码来分析衰落场景下的性能。 T4) 解决关键工程问题，即辅助用户同步和模数转换，当辅助信号比干扰主信号弱得多时，这些问题就具有挑战性。 T5) 开发软件无线电测试台并进行实验以验证所提出的解决方案。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点和更广泛的影响审查标准进行评估，被认为值得支持。