Processing and Coding for Efficient Sensing and Transmission of Information

用于高效传感和信息传输的处理和编码

• 批准号: 217239-2013
• 负责人: Banihashemi, Amir
• 金额: $ 3.72万
• 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: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=644579
• 关键词: Processing; Coding; Efficient; Sensing; Transmission

This proposal is for funding to support a continuing research program on digital and wireless communications, coding and information theory. The focus is on both sensing and sampling of the information as well as its transmission. For both cases, we are interested in devising efficient (low-complexity) algorithms and processes that can operate at very high speeds. We are also interested in implementing such algorithms in VLSI circuits. For sensing and sampling, our focus is a recent technique, called Compressed Sensing (CS). Using the graphical representation of the sensing process, we make connections to the widely popular and vastly explored area of iterative coding schemes, and propose new techniques to analyze CS algorithms, and devise new sensing matrices and recovery algorithms. The goal here is to reduce the complexity of the recovery process and yet be able to recover signals with relatively large fraction of nonzero (non-negligible) elements from a relatively small set of measurements. For information transmission, our proposal covers different layers of a communication system. At the physical layer, we devise iterative coding and processing schemes for low-complexity channel estimation/equalization/error correction. We focus on open problems in these areas such as the analysis of error floor and the design of codes with guaranteed low error floors. At the network layer, we analyze the performance of existing network coding (NC) solutions, and aim to devise new solutions with lower complexity and superior convergence behavior. Finally, we explore the cross-layer design involving two or more of the communication layers. One example would be the joint design of multiple access control (MAC) scheduling and NC for multicast scenarios in wireless multihop networks. The goal is to increase the throughput, reduce the consumed energy or decrease the delay. For the implementation part of this research, we are interested in devising new high-speed architectures and circuits with low power consumption for both sensing and processing of information. The outcome of this research translates to smaller faster more energy-efficient communication systems that are more reliable and provide a better quality of service.********

该建议是为了支持有关数字和无线通信，编码和信息理论的持续研究计划。重点放在信息的传感和采样及其传输上。在这两种情况下，我们都有兴趣设计有效的（低复杂性）算法和可以以非常高速运行的过程。我们也有兴趣在VLSI电路中实施此类算法。为了进行感测和采样，我们的重点是最近的技术，称为压缩传感（CS）。使用传感过程的图形表示，我们与广泛流行和广泛探索的迭代编码方案的领域建立联系，并提出了分析CS算法的新技术，并设计了新的传感矩阵和恢复算法。这里的目的是减少恢复过程的复杂性，但能够从相对较小的测量值中恢复具有相对较大的非零（不可忽略）元素的信号。对于信息传输，我们的建议涵盖了通信系统的不同层。在物理层，我们为低复杂通道估计/均衡/误差校正设计了迭代编码和处理方案。我们专注于这些领域的开放问题，例如误差地板的分析以及保证低误差地板的代码设计。在网络层，我们分析了现有网络编码（NC）解决方案的性能，并旨在设计具有较低复杂性和出色收敛行为的新解决方案。最后，我们探索涉及两个或多个通信层的跨层设计。一个示例是在无线多主网络中进行多播场景的多个访问控制（MAC）调度和NC的联合设计。目标是增加吞吐量，减少消耗能量或减少延迟。对于本研究的实施部分，我们有兴趣设计新的高速体系结构和电路，具有低功耗，用于感应和处理信息。 这项研究的结果转化为更快的更节能的通信系统，这些系统更可靠并提供更好的服务质量。********