High-speed low-complexity sensing/storage/processing/coding of information

高速低复杂度信息传感/存储/处理/编码

• 批准号: RGPIN-2019-06401
• 负责人: Banihashemi, Amir
• 金额: $ 3.35万
• 依托单位: Carleton University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=689290
• 关键词: speed; low; complexity; sensing; storage

We live in an information age where every aspect of our lives is influenced and empowered by information that is being collected and communicated at ever increasing rates. Whether the information is collected through millions of sensors that are deployed every single day in our appliances, security/surveillance systems and infrastructure, or through social media, the information needs to be stored, processed and communicated. The goal of this research is to address some of the most pressing challenges in today's information systems and push the existing limits of such systems in terms of speed, complexity and reliability. On the topic of sensing, we devise compressed sensing techniques that combine the operations of sensing and compression, and lend themselves to simple implementations at high speeds. For the storage, we develop coding/processing algorithms for the state--of--the--art high--speed high-density memory architectures that would make the reliable application of such architectures possible. On the topic of coding/processing for the reliable communication of information, we devise error correction and coded modulation schemes that can accommodate high--speed transmission at very low error rates. Since many communication scenarios involve multiple users that communicate through a network, we also extend our results to such cases, and consider techniques such as network coding. Our general approach in research is to first use our extensive industrial collaborations together with our knowledge of the state--of--the--art literature to identify some of the major challenges/problems that face today's information systems. We then use a variety of mathematical tools including probability theory, stochastic processes, graph theory and combinatorics along with Monte Carlo simulations to investigate such problems, develop mathematical models, and devise viable solutions. Many of the proposed topics fall into a unifying framework that describes the system as a graph with many interconnections. An important aspect of the proposed research is to investigate the structure of such graphs and examine the relationships between the properties of the graph, such as the cycle distribution, and the properties of the system, such as the error rate. In addition to the theoretical aspects of problems, we also consider implementations of our proposed techniques and algorithms both in hardware and software. The outcomes of this research are technologies and algorithms that enable faster communication links and devices, as well as smart phones and sensors that not only communicate faster and more reliably but also have a longer battery life.

我们生活在一个信息时代，我们生活的每一个方面都受到信息的影响和授权，这些信息正在以越来越快的速度收集和传播。无论信息是通过每天部署在我们的设备、安全/监控系统和基础设施中的数百万个传感器收集的，还是通过社交媒体收集的，都需要存储、处理和传达信息。这项研究的目标是解决当今信息系统中一些最紧迫的挑战，并推动这些系统在速度，复杂性和可靠性方面的现有限制。在传感的主题，我们设计的压缩传感技术，结合联合收割机的传感和压缩的操作，并借给自己简单的高速实现。对于存储，我们开发的状态--关于信息可靠通信的编码/处理的主题，我们设计了纠错和编码调制方案，可以以非常低的错误率适应高速传输。由于许多通信场景涉及多个用户通过网络进行通信，我们也将我们的结果扩展到这种情况下，并考虑网络编码等技术。我们在研究中的一般方法是首先使用我们广泛的工业合作，以及我们对最先进文献的了解，以确定当今信息系统面临的一些主要挑战/问题。然后，我们使用各种数学工具，包括概率论，随机过程，图论和组合学沿着与蒙特卡洛模拟来研究这些问题，开发数学模型，并制定可行的解决方案。许多建议的主题都属于一个统一的框架，该框架将系统描述为具有许多互连的图。所提出的研究的一个重要方面是调查这样的图的结构，并检查之间的关系的图形的属性，如周期分布，和系统的属性，如错误率。除了理论方面的问题，我们还考虑我们提出的技术和算法在硬件和软件中的实现。这项研究的成果是实现更快通信链路和设备的技术和算法，以及智能手机和传感器，不仅通信更快，更可靠，而且电池寿命更长。