Almudena Konrad and Anthony D. Joseph and Reiner Ludwig and Ben Y. Zhao

EECS Department, University of California, Berkeley

Technical Report No. UCB/CSD-01-1142

, 2001

http://www2.eecs.berkeley.edu/Pubs/TechRpts/2001/CSD-01-1142.pdf

Techniques for modeling and simulating channel conditions play an essential role in understanding network protocol and application behavior. We demonstrate that time-varying effects on wireless channels result in non-stationary wireless traces. We present an algorithm that divides traces into stationary components in order to provide analytical channel models that, relative to traditional approaches, more accurately represent characteristics, such as burstiness, statistical distribution of errors, and packet loss processes. In previous work, we demonstrated that inaccurate modeling using a traditional analytical model yielded significant errors in error control protocol parameters choices. <p>Our algorithm also generates artificial traces with the same statistical characteristics as actual collected network traces. Using these traces in a simulator environment enables future protocol and application testing under different controlled and repeatable conditions. <p>For validation, we develop a channel model for the circuit-switched data service in GSM and show that it: (1) more closely approximates GSM channel characteristics than a traditional Gilbert model and (2) generates artificial traces that closely match collected traces' statistics.

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BibTeX citation:

@techreport{Konrad:CSD-01-1142,
    Author= {Konrad, Almudena and Joseph, Anthony D. and Ludwig, Reiner and Zhao, Ben Y.},
    Title= {A Markov-Based Channel Model Algorithm for Wireless Networks},
    Year= {2001},
    Month= {May},
    Url= {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2001/5666.html},
    Number= {UCB/CSD-01-1142},
    Abstract= {Techniques for modeling and simulating channel conditions play an essential role in understanding network protocol and application behavior. We demonstrate that time-varying effects on wireless channels result in non-stationary wireless traces. We present an algorithm that divides traces into stationary components in order to provide analytical channel models that, relative to traditional approaches, more accurately represent characteristics, such as burstiness, statistical distribution of errors, and packet loss processes. In previous work, we demonstrated that inaccurate modeling using a traditional analytical model yielded significant errors in error control protocol parameters choices. <p>Our algorithm also generates artificial traces with the same statistical characteristics as actual collected network traces. Using these traces in a simulator environment enables future protocol and application testing under different controlled and repeatable conditions. <p>For validation, we develop a channel model for the circuit-switched data service in GSM and show that it: (1) more closely approximates GSM channel characteristics than a traditional Gilbert model and (2) generates artificial traces that closely match collected traces' statistics.},
}

EndNote citation:

%0 Report
%A Konrad, Almudena 
%A Joseph, Anthony D. 
%A Ludwig, Reiner 
%A Zhao, Ben Y. 
%T A Markov-Based Channel Model Algorithm for Wireless Networks
%I EECS Department, University of California, Berkeley
%D 2001
%@ UCB/CSD-01-1142
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2001/5666.html
%F Konrad:CSD-01-1142