1st International ICST Workshop On Wireless Network Measurement

Research Article

Frame error model in rural Wi-Fi networks

  • @INPROCEEDINGS{10.1109/WIOPT.2007.4480105,
        author={Paolo Barsocchi and Gabriele Oligeri and Francesco  Potorti},
        title={Frame error model in rural Wi-Fi networks},
        proceedings={1st International ICST Workshop On Wireless Network Measurement},
        publisher={IEEE},
        proceedings_a={WINMEE/WITMEMO},
        year={2008},
        month={3},
        keywords={AWGN  Additive white noise  Area measurement  Automatic repeat request  Context modeling  Error probability  Interference  Loss measurement  Mobile ad hoc networks  Propagation losses},
        doi={10.1109/WIOPT.2007.4480105}
    }
    
  • Paolo Barsocchi
    Gabriele Oligeri
    Francesco Potorti
    Year: 2008
    Frame error model in rural Wi-Fi networks
    WINMEE/WITMEMO
    IEEE
    DOI: 10.1109/WIOPT.2007.4480105
Paolo Barsocchi1,*, Gabriele Oligeri1,*, Francesco Potorti1,*
  • 1: ISTI - CNR, via Moruzzi 1, 1-56124 Pisa
*Contact email: Paolo.Barsocchi@isti.cnr.it, Gabriele.Oligeri@isti.cnr.it, Potorti@isti.cnr.it

Abstract

Commonly used frame loss models for simulations over Wi-Fi channels assume a simple double regression model with threshold. This model is widely accepted, but few measurements are available in the literature that try to validate it. As far as we know, none of them is based on field trials at the frame level. We present a series of measurements for relating transmission distance and packet loss on a Wi-Fi network in rural areas and propose a model that relates distance with packet loss probability. We show that a simple double regression propagation model like the one used in the ns-2 simulator can miss important transmission impairments that are apparent even at short transmitter-receiver distances. Measurements also show that packet loss at the frame level is a Bernoullian process for time spans of few seconds. We relate the packet loss probability to the received signal level using standard models for additive white Gaussian noise channels. The resulting model is much more similar to the measured channels than the simple models where all packets are received when the distance is below a given threshold and all are lost when the threshold is exceeded.