• DocumentCode
    45818
  • Title

    Energy and Sampling Constrained Asynchronous Communication

  • Author

    Tchamkerten, Aslan ; Chandar, Venkat ; Caire, Giuseppe

  • Author_Institution
    Dept. of Commun. & Electron., Telecom ParisTech, Paris, France
  • Volume
    60
  • Issue
    12
  • fYear
    2014
  • fDate
    Dec. 2014
  • Firstpage
    7686
  • Lastpage
    7697
  • Abstract
    The minimum energy, and, more generally, the minimum cost, to transmit 1 bit of information was recently derived for bursty communication when the information is available infrequently at random times at the transmitter. This result assumes that the receiver is always in the listening mode and samples all channel outputs until it makes a decision. Since sampling is in practice one of the receiver´s most energy consuming functions, a natural question is to evaluate capacity per unit cost when the receiver is sampling constrained. This paper investigates such a setting where the receiver can sample only a given fraction ρ ∈ (0, 1] of the channel outputs. It is shown that regardless of ρ > 0, the asynchronous capacity per unit cost is the same as under full sampling, i.e., when ρ = 1. Moreover, a sparse output sampling does not even impact decoding delay-the elapsed time between when information is available and when it is decoded. Hence, surprisingly, it suffices to sample an arbitrarily small fraction of the channel outputs and yet achieve the same (asymptotic) performance as under full output sampling.
  • Keywords
    channel capacity; compressed sensing; decoding; asynchronous capacity per unit cost; bursty communication; capacity evaluation; channel outputs; decoding delay; energy consumption functions; information transmission; sampling constrained asynchronous communication; sparse output sampling; Asynchronous communication; Decoding; Delays; Noise; Receivers; Reliability; Transmitters; Asynchronous communication; bursty communication; capacity per unit cost; change-point detection; energy; error exponents; hypothesis testing; sensor networks; sequential decoding; sparse communication; sparse sampling; synchronization;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/TIT.2014.2360017
  • Filename
    6960771