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: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=765849
• 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.

我们生活在生活中的信息方面，并通过收集和同时发生的保证率授权。是否通过数百万传感器收集了这些信息，这些传感器每天都在我们的设备，安全/安全/监视系统和基础设施中部署或通过社交媒体来存储这些信息。感知，我们设计了结合感应和离子操作的压缩技术，并以高速含义对存储进行简单含义。内存架构可靠的架构应用程序。我们对这种情况的结果，并考虑了网络编码等技术多种数学工具，包括概率理论，随机过程，图理论和组合，以及蒙特卡洛模拟，以研究此类问题，开发数学模型s并设计可行的解决方案。关系属性属于循环分布，以及系统的属性，例如错误率。更可靠地，但电池寿命也更长。