• DocumentCode
    2042850
  • Title

    Stochastic dynamic models in PHY abstraction

  • Author

    Rey, Francesc ; Sala-Alvarez, Josep

  • Author_Institution
    Signal Theor. & Commun. Dept., Tech. Univ. of Catalonia (UPC), Barcelona, Spain
  • fYear
    2013
  • fDate
    3-6 Nov. 2013
  • Firstpage
    1639
  • Lastpage
    1643
  • Abstract
    Physical Layer (PHY) abstraction aims to model link performance and accelerate system-level analyses of communication systems by reducing simulation complexity and their associated computational costs. We examine a Physical Layer (PHY) abstraction approach based on Stochastic Dynamic Systems (SDS) for easing the requirement of expensive Monte Carlo system-level evaluations. We present the framework, recently applied in simplified models for Successive Interference Cancellation (SIC) receivers in the finite and large user limits, and refine the analysis for a related scheme named Successive Interference Blocking (SIB), with the objective of evaluating performance metrics such as the Packet Error Rate using a probability particle algorithm for approximating the equivalent SDS.
  • Keywords
    Monte Carlo methods; error statistics; interference suppression; radio links; radio receivers; Monte Carlo system-level evaluations; PHY abstraction; SDS; SIB; SIC receivers; accelerate system-level analyses; communication systems; computational costs; link performance; packet error rate; physical layer abstraction; probability particle algorithm; stochastic dynamic models; stochastic dynamic systems; successive interference blocking; successive interference cancellation receivers; Correlation; Decoding; Interference; Receivers; Signal to noise ratio; Silicon carbide; Packet Error Rate (PER); Physical Layer (PHY) abstraction; Stochastic Dynamic System (SDS); Successive Interference Cancellation (SIC);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signals, Systems and Computers, 2013 Asilomar Conference on
  • Conference_Location
    Pacific Grove, CA
  • Print_ISBN
    978-1-4799-2388-5
  • Type

    conf

  • DOI
    10.1109/ACSSC.2013.6810577
  • Filename
    6810577