<abstract xmlns="http://www.w3.org/1999/xhtml"><p>A variety of complex techniques, such as forward error correction (FEC), automatic repeat request (ARQ), hybrid ARQ or cross-layer optimization, require in their design and optimization phase a realistic model of binary error process present in a specific digital channel. Past and more recent modeling approaches focus on capturing one or more stochastic characteristics with precision sufficient for the desired model application, thereby applying concepts and methods severely limiting the model applicability (<italic>eg</italic> in the form of modeled process prerequisite expectations). The proposed novel concept utilizing a Vector Quantization (VQ)-based approach to binary process modeling offers a viable alternative capable of superior modeling of most commonly observed small- and large-scale stochastic characteristics of a binary error process on the digital channel. Precision of the proposed model was verified using multiple statistical distances against the data captured in a wireless sensor network logical channel trace. Furthermore, the Pearson’s goodness of fit test of all model variants’ output was performed to conclusively demonstrate usability of the model for realistic captured binary error process. Finally, the presented results prove the proposed model applicability and its ability to far surpass the capabilities of the reference Elliot’s model.</p></abstract>

A variety of complex techniques, such as forward error correction (FEC), automatic repeat request (ARQ), hybrid ARQ or cross-layer optimization, require in their design and optimization phase a realistic model of binary error process present in a specific digital channel. Past and more recent modeling approaches focus on capturing one or more stochastic characteristics with precision sufficient for the desired model application, thereby applying concepts and methods severely limiting the model applicability (eg in the form of modeled process prerequisite expectations). The proposed novel concept utilizing a Vector Quantization (VQ)-based approach to binary process modeling offers a viable alternative capable of superior modeling of most commonly observed small- and large-scale stochastic characteristics of a binary error process on the digital channel. Precision of the proposed model was verified using multiple statistical distances against the data captured in a wireless sensor network logical channel trace. Furthermore, the Pearson’s goodness of fit test of all model variants’ output was performed to conclusively demonstrate usability of the model for realistic captured binary error process. Finally, the presented results prove the proposed model applicability and its ability to far surpass the capabilities of the reference Elliot’s model.

VQ-based model for binary error process

Slovak University of Technology in Bratislava

Journal of Electrical Engineering

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"VQ-based model for binary error process"}

A variety of complex techniques, such as forward error correction (FEC), automatic repeat request (ARQ), hybrid ARQ or cross-layer optimization, require in...

VQ-based model for binary error process

Publicado en línea: 06 jul 2017

Páginas: 167 - 179

Recibido: 03 ago 2016

DOI: https://doi.org/10.1515/jee-2017-0025

Palabras clave
binary error, VQ, wireless channel, logical channel, error model, wireless sensor network

© 2017 Faculty of Electrical Engineering and Information Technology, Slovak University of Technology

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

VQ-based model for binary error process

Publicado en línea: 06 jul 2017

Páginas: 167 - 179

Recibido: 03 ago 2016

DOI: https://doi.org/10.1515/jee-2017-0025

Palabras clavebinary error, VQ, wireless channel, logical channel, error model, wireless sensor network

© 2017 Faculty of Electrical Engineering and Information Technology, Slovak University of Technology

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Palabras clave
binary error, VQ, wireless channel, logical channel, error model, wireless sensor network