• DocumentCode
    1001120
  • Title

    On the capacity of network coding for random networks

  • Author

    Ramamoorthy, Aditya ; Shi, Jun ; Wesel, Richard D.

  • Author_Institution
    Dept. of Electr. Eng., Univ. of California, Los Angeles, CA, USA
  • Volume
    51
  • Issue
    8
  • fYear
    2005
  • Firstpage
    2878
  • Lastpage
    2885
  • Abstract
    We study the maximum flow possible between a single-source and multiple terminals in a weighted random graph (modeling a wired network) and a weighted random geometric graph (modeling an ad-hoc wireless network) using network coding. For the weighted random graph model, we show that the network coding capacity concentrates around the expected number of nearest neighbors of the source and the terminals. Specifically, for a network with a single source, l terminals, and n relay nodes such that the link capacities between any two nodes is independent and identically distributed (i.i.d.) ∼X, the maximum flow between the source and the terminals is approximately nE[X] with high probability. For the weighted random geometric graph model where two nodes are connected if they are within a certain distance of each other we show that with high probability the network coding capacity is greater than or equal to the expected number of nearest neighbors of the node with the least coverage area.
  • Keywords
    ad hoc networks; channel capacity; channel coding; graph theory; multicast communication; random codes; multicast network; network coding capacity; probability; weighted random geometric graph; weighted random graph; Capacity planning; Communication networks; Forward contracts; Information rates; Nearest neighbor searches; Network coding; Relays; Routing; Solid modeling; Wireless networks; Minimum cut; multicast; network coding; random geometric graphs; random graphs;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/TIT.2005.851725
  • Filename
    1468306