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，在这种时代，我们生活的各个方面都受到以不断增加的速度收集和传达信息的影响和赋权。是通过数百万传感器收集的信息，这些传感器每天都在我们的设备，安全/监视系统和基础架构中部署，还是通过社交媒体进行的，需要存储，处理和传达信息。这项研究的目的是解决当今信息系统中最紧迫的挑战，并在速度，复杂性和可靠性方面推动此类系统的现有限制。在感应的主题上，我们设计了结合感应和压缩操作的压缩感测技术，并将自己借助高速实现。对于存储，我们为状态的状态开发了编码/处理算法，即 - 艺术高速度高密度内存体系结构，这将使此类体系结构的可靠应用成为可能。关于可靠信息通信的编码/处理主题，我们设计了错误校正和编码调制方案，这些计划可以以非常低的错误率适应高速传输。由于许多通信方案都涉及通过网络通信的多个用户，因此我们还将结果扩展到此类情况，并考虑诸如网络编码之类的技术。我们的一般研究方法是首先使用我们广泛的工业合作，以及我们对国家的了解，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，包括概率理论，随机过程，图形论和组合学以及蒙特卡洛模拟来研究此类问题，开发数学模型并设计可行的解决方案。许多提出的主题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形。拟议的研究的一个重要方面是研究此类图的结构，并检查图形的性质（例如周期分布）和系统的性质（例如错误率）之间的关系。除了问题的理论方面外，我们还考虑了在硬件和软件中提出的技术和算法的实现。这项研究的结果是使通信链接和设备的技术和算法以及智能手机和传感器不仅可以更快，更可靠的，而且还具有更长的电池寿命。