CIF: Small: Collaborative Research: Between Shannon and Hamming

CIF:小:香农和汉明之间的合作研究

基本信息

  • 批准号:
    1909468
  • 负责人:
  • 金额:
    $ 25万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2019
  • 资助国家:
    美国
  • 起止时间:
    2019-10-01 至 2023-09-30
  • 项目状态:
    已结题

项目摘要

Over the last 70 years, information theory and coding have enabled communication technologies that have had an astounding impact on everyday lives. This is possible due to the match between encoding/decoding strategies and corresponding models of the communication channel. Traditional models fall at two ends of a spectrum. Models which assume that the channel is random, such as those involving channel noise governed by a memoryless stochastic process, take an average-case view of the channel: such models are the basis of Shannon theory. At the other extreme, "Hamming"-like models take a worst-case view of the channel: the noise can be chosen adversarially with respect to the communication scheme. However, for several existing and emerging communication systems, the Shannon/average-case view may be too optimistic, whereas the Hamming/worst-case view may be too pessimistic. This project takes up the challenge of studying models that lie between the Shannon and Hamming extremes. The outcomes of this research will inform the design of codes for a multitude of practical settings where average-case interference models may be too optimistic and worst-case models may be too pessimistic, such as wireless multiple-frame communication systems in vehicular networks (VANETS) or the Internet of Things (IoT).The common way to view the distinction between average-case and worst-case analysis is operational: it is a difference in error criterion. This project takes a different perspective: the difference is in how the interference can depend on the transmitted codeword. This is modeled by assuming the interference is controlled by a jammer. A dependent jammer corresponds to the Hamming model while an independent one corresponds to that of Shannon. Restricting how jammer interference can depend on the codeword transmitted gives rise to models that lie between those of Shannon and Hamming. The project develops theoretical foundations for the study of communication models in which the jammer acts under varying degrees of uncertainty, and identifies new channel models, code designs, and capacity concepts. The project will develop a unified treatment of channel models that lie between the Shannon and Hamming model and abilities to (a) design optimal rate coding schemes that utilize the limitations posed on the jammer; (b) design secure communication schemes that leverage the jammer's constraints to improve traditional tradeoffs between capacity and security; and (c) inform the design of future practical codes.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
在过去的70年中,信息理论和编码使通信技术对日常生活产生了惊人的影响。由于编码/解码策略与通信通道的相应模型之间的匹配,这是可能的。传统模型落在光谱的两端。假设通道是随机的模型,例如涉及由无内存随机过程控制的通道噪声的模型,对通道的平均视图进行视图:这样的模型是香农理论的基础。在另一个极端情况下,“锤子”样模型对通道的最坏情况进行了最糟糕的视野:可以根据通信方案对噪声进行对抗。但是,对于几种现有和新兴的通信系统,香农/平均案例视图可能太乐观了,而锤击/最差的视图可能太悲观了。该项目面临着研究香农和极端锤击之间的模型的挑战。 The outcomes of this research will inform the design of codes for a multitude of practical settings where average-case interference models may be too optimistic and worst-case models may be too pessimistic, such as wireless multiple-frame communication systems in vehicular networks (VANETS) or the Internet of Things (IoT).The common way to view the distinction between average-case and worst-case analysis is operational: it is a difference in error criterion.该项目具有不同的观点:区别在于干扰如何取决于传输的代码字。这是通过假设干扰器控制干扰的来建模的。依赖的干扰器对应于锤式模型,而独立的干扰器则对应于香农的模型。限制干扰干扰如何取决于传输的代码字会导致Shannon和Hamming之间的模型。该项目为研究模型的研究开发了理论基础,其中干扰器以不同程度的不确定性作用,并确定新的渠道模型,代码设计和容量概念。该项目将开发统一的渠道模型处理,该渠道模型位于香农和锤模模型之间,以及(a)设计最佳速率编码方案,以利用Jammer上的限制; (b)设计安全的沟通计划,以利用干扰者的限制来改善能力和安全之间的传统权衡; (c)告知未来实用代码的设计。该奖项反映了NSF的法定任务,并被认为是值得通过基金会的知识分子优点和更广泛影响的评论标准来评估值得支持的。

项目成果

期刊论文数量(5)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Privacy Leakage in Discrete-Time Updating Systems
离散时间更新系统中的隐私泄露
Computationally Efficient Codes for Adversarial Binary-Erasure Channels
对抗性二进制擦除通道的计算高效代码
  • DOI:
    10.1109/isit54713.2023.10206731
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Li, Sijie;Krishnan, Prasad;Jaggi, Sidharth;Langberg, Michael;Sarwate, Anand D.
  • 通讯作者:
    Sarwate, Anand D.
The Capacity of Causal Adversarial Channels
因果对抗渠道的容量
Symmetrizability for Myopic AVCs
近视 AVC 的对称性
Quadratically Constrained Myopic Adversarial Channels
二次约束近视对抗通道
  • DOI:
    10.1109/tit.2022.3167554
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    2.5
  • 作者:
    Zhang, Yihan;Vatedka, Shashank;Jaggi, Sidharth;Sarwate, Anand D.
  • 通讯作者:
    Sarwate, Anand D.
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Anand Sarwate其他文献

Ieee Information Theory Society Newsletter President's Column from the Editor Ieee Information Theory Society Newsletter the Historian's Column
IEEE 信息论学会通讯 主席编辑专栏 IEEE 信息论学会通讯 历史学家专栏
  • DOI:
  • 发表时间:
    2012
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Meir Feder;Tracey Ho;Joerg Kliewer;Anand Sarwate;Andy Singer
  • 通讯作者:
    Andy Singer
Ieee Information Theory Society Newsletter President's Column from the Editor It Society Member Honored Scholar One Website for Ieee Transactions on Information Theory Has Gone Live Throughput and Capacity Regions Coding for Noisy Networks
Ieee 信息论协会通讯 编辑主席专栏 It 协会会员 荣誉学者 IEEE 信息论交易网站已上线 吞吐量和容量 噪声网络区域编码
  • DOI:
  • 发表时间:
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Helmut Bölcskei;Giuseppe Caire;Meir Feder;Joerg Kliewer;Anand Sarwate;Andy Singer;Dave Forney;S. Shamai;Alexander Vardy;Sergio Verdú;F. Kschischang;Tracey Ho;Norman C Beaulieu;Icore Research Chair;Anthony Ephremides;A. E. Gamal
  • 通讯作者:
    A. E. Gamal

Anand Sarwate的其他文献

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{{ truncateString('Anand Sarwate', 18)}}的其他基金

RINGS: REALTIME: Resilient Edge-cloud Autonomous Learning with Timely Inferences
RINGS:实时:具有及时推理能力的弹性边缘云自主学习
  • 批准号:
    2148104
  • 财政年份:
    2022
  • 资助金额:
    $ 25万
  • 项目类别:
    Continuing Grant
CIF: Small: ESTRELLA: Exploiting Structure in Tensors for Representation, Estimation, and Limits of Learning Algorithms
CIF:小:ESTRELLA:利用张量结构进行表示、估计和学习算法的限制
  • 批准号:
    1910110
  • 财政年份:
    2019
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant
TWC: Small: PERMIT: Privacy-Enabled Resource Management for IoT Networks
TWC:小型:PERMIT:物联网网络的启用隐私的资源管理
  • 批准号:
    1617849
  • 财政年份:
    2016
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant
CAREER: Privacy-preserving learning for distributed data
职业:分布式数据的隐私保护学习
  • 批准号:
    1453432
  • 财政年份:
    2015
  • 资助金额:
    $ 25万
  • 项目类别:
    Continuing Grant
CIF: Small: Collaborative Research: Inference by social sampling
CIF:小型:协作研究:社会抽样推断
  • 批准号:
    1440033
  • 财政年份:
    2014
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant
CIF: Small: Collaborative Research: Inference by social sampling
CIF:小型:协作研究:社会抽样推断
  • 批准号:
    1218331
  • 财政年份:
    2012
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant

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Collaborative Research: CIF: Small: Mathematical and Algorithmic Foundations of Multi-Task Learning
协作研究:CIF:小型:多任务学习的数学和算法基础
  • 批准号:
    2343599
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Collaborative Research: CIF: Small: Mathematical and Algorithmic Foundations of Multi-Task Learning
协作研究:CIF:小型:多任务学习的数学和算法基础
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  • 批准号:
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Collaborative Research:CIF:Small:Fisher-Inspired Approach to Quickest Change Detection for Score-Based Models
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