CIF: Small: Exploiting Interference via Data-Dependent Precoding

CIF：小：通过数据相关预编码利用干扰

基本信息

批准号：
2008724
负责人：
Arnold Swindlehurst
金额：
$ 50万
依托单位：
University of California-Irvine
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-10-01 至 2024-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2008724&HistoricalAwards=false
关键词：
CIF Small Exploiting Interference via

项目摘要

In wireless communications, managing interference is a key problem that has been studied for many years. When a cell tower or a WiFi access point sends signals simultaneously to several users, it has to ensure that these signals do not get so mixed up with each other that they can't be separated by the individual receivers. The most common approach is to encode the signals in a way that attempts to completely eliminate this multi-user interference, usually by assigning each signal to an "orthogonal" channel, e.g., sending the signals at different times, on different frequency bands, or using different transmission beams. The goal of this project is to exploit the observation that not all interference is "bad." When the signals are confined to a limited alphabet, it is unnecessary that the signal be received in exactly the form it was transmitted; it is only necessary that the receiver properly decode which symbol from the alphabet of signals was transmitted. While multi-user interference inevitably distorts the waveform, the transmitter can encode the waveform in such a way that the interference does not prevent (and in fact can enhance) the ability of the receivers to correctly decode their respective symbols. The key advantage of this approach is that it enables the transmitter to use much less power to get the same performance, since the interference essentially serves the purpose of adding extra power to the desired signals for each receiver. The significant energy savings that can result from this approach could have a revolutionary effect on the performance of wireless systems, and enable a much wider deployment of wireless network infrastructure and IoT devices at a fraction of the currently required energy consumption. Multi-antenna implementations have become standard in today’s WiFi and cellular communication networks, and are one of the key technologies for achieving the large throughputs and high reliability required by next-generation systems. This proposal is focused on a new symbol-level precoding paradigm that has recently emerged in which not only the channel state information is exploited, but also knowledge of the symbols to be transmitted. This approach provides a powerful extra dimension for optimization that can yield dramatic improvements in performance. While most precoding methods try to eliminate interference, symbol-level precoding (SLP) exploits useful or "constructive" interference and repurposes it as energy for the desired signals. This increases the robustness of the signal detection and enables wireless systems to operate with significantly less power, and thus makes constructive interference SLP a promising candidate for low-cost and high-reliability applications. This project seeks to study methods for reducing the complexity of SLP, operation of the algorithms in scenarios with constrained radio-frequency front ends (e.g., low-resolution quantization, per-antenna power constraints), physical layer security, user selection in large networks, theoretical analyses of performance, network settings other than broadcast, etc.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.

在无线通信中，管理干扰是多年来研究的关键问题。当单元塔或WiFi访问点仅向几个用户发送信号时，它必须确保这些信号不会彼此混淆，以免单个接收器分开。最常见的方法是以一种试图完全消除此多用户干扰的方式编码信号，通常是通过将每个信号分配给“正交”通道，例如在不同时间，不同的频带上或使用不同的传输梁发送信号。该项目的目的是利用并非所有干扰都是“不好”的观察。当信号局限于有限的字母内时，不需要以其传输的形式完全接收信号；只有接收器才能正确解码信号字母中哪个符号。虽然多用户干扰不可避免地会扭曲波形，但发射机可以以干扰不防止（实际上可以增强）接收器正确解码其各自符号的能力来编码波形。这种方法的关键优势在于，它使发射器能够使用更少的功率来获得相同的性能，因为干扰基本上有目的是为每个接收器的所需信号添加额外的功率。这种方法可以产生的大量节能可能会对无线系统的性能产生革命性的影响，并在当前所需的能源消耗的一小部分中可以更广泛地部署无线网络基础架构和IoT设备。在当今的wifi和蜂窝通信网络中，多人的实现已成为标准，并且是实现下一代系统所需的大量吞吐量和高可靠性的关键技术之一。该建议集中在一个新的符号级的预码范式上，该范式最近出现了，其中不仅利用了频道状态信息，而且还了解要传输的符号。这种方法为优化提供了强大的额外维度，可以在性能方面产生巨大的改进。虽然大多数预编码方法试图消除干扰，但符号级预码（SLP）利用有用或“建设性”干扰并将其重新利用为所需信号的能量。这增加了信号检测的鲁棒性，并使无线系统能够以较小的功率运行，从而使建设性的干扰SLP成为低成本和高可靠性应用的承诺候选者。该项目旨在研究降低SLP复杂性的方法，算法在场景中的运行，具有限制的射频前端（例如，低分辨率量化，每个量化的量，实体层的限制），物理层安全性，用户的选择，在大型网络中使用绩效和网络的宣布，均具有众多奖励等。基金会的智力优点和更广泛的影响审查标准。