• DocumentCode
    3607256
  • Title

    Euclidean Information Theory of Networks

  • Author

    Shao-Lun Huang ; Changho Suh ; Lizhong Zheng

  • Author_Institution
    Res. Lab. of Electron., Massachusetts Inst. of Technol., Cambridge, MA, USA
  • Volume
    61
  • Issue
    12
  • fYear
    2015
  • Firstpage
    6795
  • Lastpage
    6814
  • Abstract
    In this paper, we extend the information theoretic framework that was developed in earlier works to multi-hop network settings. For a given network, we construct a novel deterministic model that quantifies the ability of the network in transmitting private and common messages across users. Based on this model, we formulate a linear optimization problem that explores the throughput of a multi-layer network, thereby offering the optimal strategy as to what kind of common messages should be generated in the network to maximize the throughput. With this deterministic model, we also investigate the role of feedback for multi-layer networks, from which we identify a variety of scenarios in which feedback can improve transmission efficiency. Our results provide fundamental guidelines as to how to coordinate cooperation between users to enable efficient information exchanges across them.
  • Keywords
    information theory; linear programming; Euclidean information theoretic framework; linear optimization problem; novel deterministic model; transmission efficiency; Approximation methods; Couplings; Optimization; Receivers; Spread spectrum communication; Throughput; Deterministic Model; Divergence Transition Matrix (DTM); Feedback; Kullback-Leibler Divergence Approximation; Kullback-Leibler divergence approximation; Linear Information Coupling (LIC) Problem; Linear information coupling (LIC) problem; deterministic model; divergence transition matrix (DTM); feedback;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/TIT.2015.2484066
  • Filename
    7283641