A generative model for burst error characterization in a fading channel

In this paper we present a novel generative model using universal prediction technique for burst error characterization in a fading environment. The proposed model has been used to generate burst error sequences as per the statistics of the error sequences observed in waveform level simulation of a link that follows the global system for mobile communication (GSM) standards with channel characteristics chosen as per COST 207 models for typical urban and rural areas. Simulation results show close match of the burst error statistics generated by the proposed model with that of the descriptive model which employs waveform level simulation, thereby validating the effectiveness of the proposed method.

[1]  Bruce D. Fritchman,et al.  A binary channel characterization using partitioned Markov chains , 1967, IEEE Trans. Inf. Theory.

[2]  E. Gilbert Capacity of a burst-noise channel , 1960 .

[3]  Andreas Willig,et al.  A new class of packet- and bit-level models for wireless channels , 2002, The 13th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications.

[4]  John G. Proakis,et al.  Probability, random variables and stochastic processes , 1985, IEEE Trans. Acoust. Speech Signal Process..

[5]  Paolo Gamba,et al.  Multipath channel modeling with chaotic attractors , 2002 .

[6]  Edward J. Delp,et al.  Wyner-Ziv video coding with universal prediction , 2006, Electronic Imaging.

[7]  Neri Merhav,et al.  Universal Prediction , 1998, IEEE Trans. Inf. Theory.

[8]  E. O. Elliott Estimates of error rates for codes on burst-noise channels , 1963 .

[9]  Cheng-Xiang Wang,et al.  A New Class of Generative Models for Burst-Error Characterization in Digital Wireless Channels , 2007, IEEE Transactions on Communications.

[10]  Javier Garcia-Frías,et al.  Stochastic context-free grammars and hidden Markov models for modeling of bursty channels , 2004, IEEE Transactions on Vehicular Technology.