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

我们生活在一个信息时代，我们生活的方方面面都受到信息的影响和增强，这些信息正在以越来越快的速度被收集和传播。无论这些信息是通过每天部署在我们的电器、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，这些信息都需要被存储、处理和交流。本研究的目标是解决当今信息系统中一些最紧迫的挑战，并在速度、复杂性和可靠性方面突破现有系统的限制。在传感的主题上，我们设计了压缩传感技术，它结合了传感和压缩的操作，并使它们能够在高速下实现简单。对于存储，我们为最先进的高速高密度存储体系结构开发编码/处理算法，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通过网络通信的多个用户，因此我们也将结果扩展到此类情况，并考虑网络编码等技术。我们的一般研究方法是首先利用我们广泛的工业合作以及我们对艺术文献的了解来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，以及蒙特卡罗模拟来研究这些问题，开发数学模型，并设计可行的解决方案。许多提出的主题都属于一个统一的框架，该框架将系统描述为具有许多相互联系的图。本研究的一个重要方面是研究这种图的结构，并研究图的性质（如周期分布）与系统的性质（如错误率）之间的关系。除了问题的理论方面，我们还考虑了我们提出的技术和算法在硬件和软件上的实现。这项研究的成果是实现更快的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，而且具有更长的电池寿命。

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.