CAREER: Towards Green Communications Using an Information-Lens: Foundations of the Joint Design of Communication Strategies and Circuits

职业:使用信息镜头迈向绿色通信:通信策略和电路联合设计的基础

基本信息

  • 批准号:
    1350314
  • 负责人:
  • 金额:
    $ 59.6万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2014
  • 资助国家:
    美国
  • 起止时间:
    2014-01-15 至 2018-12-31
  • 项目状态:
    已结题

项目摘要

This research project aims to develop a system-level theory of energy efficient communication that incorporates the energy consumed in transmission as well as in the supporting transmitter/receiver circuitry. The existing theoretical foundation that guides the design of practical communication systems -- traditional information theory -- focuses almost exclusively on the transmit energy. For many modern short-distance communication systems, however, the energy consumed in the processing circuitry dominates over the transmit energy. The proposed research will advance the existing theory and practice by examining flows of information in the supporting circuitry in order to obtain a fundamental understanding of total (transmit + circuit) energy. A three-layer approach will be adopted to reduce energy consumption: (i) The Foundational Layer for expanding the frontiers of traditional information theory by incorporating processing energy at the transmitting and receiving ends; (ii) The Design Layer for novel designs of strategies including error-correcting codes that minimize the total energy; and (iii) The Validation Layer for assessing the energy reductions for various applications through strategies proposed in the Design Layer.Applications ranging from education, healthcare, manufacturing, and commerce today rely on uninterrupted and ubiquitous connectivity. Consequently, it has become increasingly important to keep the energy consumed in communication networks low, both for improving battery life of wireless devices and for sustainability of high-energy wired communication (such as ethernet links in data centers). Broadly speaking, the traditional design approach follows a "division-of-labor": the transmission strategy is first chosen to best approach the information-theoretic limits on minimum transmit energy, and then the most energy-efficient circuits are built to support the chosen strategy. The proposed research rethinks this division-of-labor by jointly designing the transmission strategy and circuits to maximize system-level energy efficiency. This research necessitates simplification and synthesis of concepts in communication, computation, and circuits. The project incorporates several educational and outreach efforts, including organizing interactive workshops for K-12 students and developing new material for both theoretical and experimental classes towards educating cross-disciplinary leaders not just in research, but also in industry where such education is essential for increased innovation.
该研究项目旨在开发一种系统级的节能通信理论,该理论将传输中消耗的能量以及支持发射机/接收机电路中的能量结合起来。指导实际通信系统设计的现有理论基础--传统的信息论--几乎完全集中在发射能量上。然而,对于许多现代短距离通信系统,处理电路中消耗的能量超过发射能量。拟议的研究将通过检查支持电路中的信息流来推进现有的理论和实践,以获得对总(传输+电路)能量的基本理解。将采用三层方法来减少能源消耗:(i)基础层,通过在发送端和接收端引入处理能量来扩展传统信息理论的前沿;(ii)设计层,用于设计新的策略,包括使总能量最小化的纠错码;以及(iii)验证层,用于通过设计层中提出的策略来评估各种应用的能耗降低。应用范围包括教育、医疗保健、制造业,和商业都依赖于不间断和无处不在的连接。因此,为了提高无线设备的电池寿命以及为了高能量有线通信(诸如数据中心中的以太网链路)的可持续性,保持通信网络中消耗的能量较低变得越来越重要。一般来说,传统的设计方法遵循“分工”:首先选择传输策略,以最好地接近最小传输能量的信息理论限制,然后构建最节能的电路来支持所选择的策略。拟议的研究通过联合设计传输策略和电路来重新考虑这种分工,以最大限度地提高系统级的能源效率。这项研究需要简化和综合的概念,在通信,计算和电路。该项目结合了几项教育和推广工作,包括为K-12学生组织互动研讨会,并为理论和实验课程开发新材料,以教育跨学科领导者,不仅在研究领域,而且在行业中,这种教育对增加创新至关重要。

项目成果

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Pulkit Grover其他文献

Scaling of Algorithmic Bias in Pulse Oximetry with Signal-to-Noise Ratio
用信噪比缩放脉搏血氧饱和度中的算法偏差
EEG Source Imaging of Infarct Core and Penumbra for Ischemic Stroke Patients
缺血性中风患者梗塞核心和半暗带的脑电图源成像
Effect of electric field direction on neuronal activity: an ex-vivo study*
电场方向对神经元活动的影响:离体研究*
A vector version of witsenhausen’s counterexample: A convergence of control, communication and computation
维森豪森反例的矢量版本:控制、通信和计算的融合

Pulkit Grover的其他文献

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{{ truncateString('Pulkit Grover', 18)}}的其他基金

CIF: Medium: Collaborative Research: Coded Computing for Large-Scale Machine Learning
CIF:媒介:协作研究:大规模机器学习的编码计算
  • 批准号:
    1763561
  • 财政年份:
    2018
  • 资助金额:
    $ 59.6万
  • 项目类别:
    Continuing Grant
WiFiUS: Fault-Tolerant Cognitive IoT Systems Using Sensors of Limited Field-of-View: Fundamental Limits and Practical Strategies
WiFiUS:使用有限视场传感器的容错认知物联网系统:基本限制和实际策略
  • 批准号:
    1702694
  • 财政年份:
    2017
  • 资助金额:
    $ 59.6万
  • 项目类别:
    Standard Grant

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