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On the use of Hidden Markov Processes and auto-regressive filters to incorporate indoor bursty wireless channels into network simulation platforms

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Abstract

In this paper we thoroughly analyze two alternatives to replicate the bursty behavior that characterizes real indoor wireless channels within Network Simulation platforms. First, we study the performance of an improved Hidden Markov Process model, based on a time-wise configuration so as to decouple its operation from any particular traffic pattern. We compare it with the behavior of Bursty Error Model Based on an Auto-Regressive Filter, a previous proposal of ours that emulates the received Signal to Noise Ratio by means of an auto-regressive filter that captures the “memory” assessed in real measurements. We also study the performance of one of the legacy approaches intrinsically offered by most network simulation frameworks. By means of a thorough simulation campaign, we demonstrate that our two models are able to offer a much more realistic behavior, yet maintaining an affordable response in terms of computational complexity.

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Notes

  1. The standard establishes that up to seven retries could be used, but the Orinoco wireless cards that were used during the measurement campaign used three retransmissions, as was also verified in  [2].

  2. This function uses the Baum-Welch algorithm [4] to estimate the chain parameters (transition and emission matrices, as well as the initial probabilities).

  3. The legacy frame-based operation uses a geometric distribution.

  4. For example, the probability that a frame requires two retransmissions at state \(i\) can be calculated as \(p_i^2 \cdot (1 - p_i)\), i.e. there are two consecutive erroneous transmissions and then a correct one.

  5. We also studied configurations with higher number of states (i.e. eight and 16) and the resulting performance was alike.

  6. There is no relationship between the distance between nodes and the erroneous performance of the transmission.

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Acknowledgments

The authors would like to express their gratitude to the Spanish government for its funding in the project “Connectivity as a Service: Access for the Internet of the Future”, COSAIF (TEC2012-38574-C02-01). Besides, we would like to thank as well Mr. Juan Ramón Santana for his help during the development of this work. This work has been partially presented in part in the following conferences: IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob 2012), workshop on ns-3 (WNS3 2013), within the International ICST Conference on Simulation Tools and Techniques (Simutools 2013) and IEEE Wireless Days 2013.

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Authors and Affiliations

  1. Communications Engineering Department, Edificio José Luis García García, Plaza de la Ciencia, Avda. de Los Castros S/N, Santander, Cantabria, Spain

    David Gómez, Ramón Agüero, Marta García-Arranz & Luis Muñoz

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  1. David Gómez
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  2. Ramón Agüero
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  3. Marta García-Arranz
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  4. Luis Muñoz
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Correspondence to David Gómez.

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Gómez, D., Agüero, R., García-Arranz, M. et al. On the use of Hidden Markov Processes and auto-regressive filters to incorporate indoor bursty wireless channels into network simulation platforms. Wireless Netw 21, 2137–2154 (2015). https://doi.org/10.1007/s11276-015-0909-0

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