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Multiple Description Coding and Scalable Video Coding Combined with Multiple Input Multiple Output Techniques: Two Strategies to Enhance Train to Wayside Video Transmissions in Tunnels

  • Conference paper
Communication Technologies for Vehicles (Nets4Cars/Nets4Trains 2011)

Abstract

Video monitoring applications for underground rely on wireless train-to-wayside communication systems which require high data rate as well as high Quality of Service (QoS) level. In order to satisfy both constraints we propose a combined source and channel coding approach in the context of MIMO (Multiple Input Multiple Output) video transmission. In the present case, MIMO transmission is based on the PHY layer of IEEE 802.11n Wi-Fi standard currently deployed in a railway tunnels. Two different strategies are studied: first, the association between Multiple Description Coding (MDC) and a STBC (Space Time Block Code) MIMO scheme is considered when no channel information is available at transmitter side. In the case when perfect channel information is available at transmitter side (CSIT), a Singular Value Decomposition of the MIMO channel is possible. This transmission scheme is then associated with scalable video coding, which consists here in the separation of the scene into different Regions Of Interest (ROI). The creation of the regions of interest is based on the Flexible Macroblock Ordering (FMO) technique introduced in the new H.264/AVC compression standard. The stream associated to the area with the maximal perceptual relevance is transmitted on the eigen-channel with the higher gain. Consequently, this strategy which provides unequal protection against channel errors, allows guaranteeing better robustness and acceptable reconstructed video quality at the control-centre. The two different strategies of transmission have been evaluated thanks to realistic simulations. Two antenna configurations representative of real cases encountered in railway tunnels are considered. The channel model is generated by using the correlation based Kronecker model obtained by computing the channel matrix with a 3D ray tracing tool. Simulation results show that the two proposed solutions allow enhancing the reconstructed video quality compared to conventional transmission schemes with no increase of the transmitted power and of the number of radio access points along the infrastructure, even in tunnels in presence of spatial correlation.

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References

  1. Alamouti, S.: A simple transmit diversity technique for wireless communications. IEEE J. Sel. Areas Commun. 16(8), 1451–1458 (1998)

    Article  Google Scholar 

  2. Almers, P., Bonek, E., Burr, A., et al.: Survey of channel and radio propagation models for wireless mimo systems. EURASIP Journal on Wireless Communications and Networking, 19 (2007)

    Google Scholar 

  3. Berezansky, Y., Sheftel, Z., Us, G.: Functional analysis, vol. 1. Birkhauser Verlag, Basel (1996)

    Book  MATH  Google Scholar 

  4. Chartois, Y., Pousset, Y., Vauzelle, R.: A siso and mimo radio channel characterization with 3d ray tracing propagation model in urban environment. In: Proceedings of ECPS 2005. IEEE, Brest (2005)

    Google Scholar 

  5. Chizhik, D., Foschini, G., Valenzuela, R.: Capacity of multi element transmit and received antennas: Correlation and keyholes. Electron. Lett., 1099–1100 (2000)

    Google Scholar 

  6. Cocheril, Y., Berbineau, M., Combeau, P., Pousset, Y.: On the importance of the mimo channel correlation in underground railway tunnels. Journal of Communications 4(4), 224–231 (2009)

    Article  Google Scholar 

  7. Cocheril, Y., Combeau, P., Berbineau, M., Pousset, Y.: MIMO channel propagation characteristics in tunnels. In: Proceedings of ITST 2007, pp. 405–410. IEEE, Sophia-Antipolis (2007)

    Google Scholar 

  8. Cocheril, Y., Langlais, C., Berbineau, M., Moniak, G.: Advantages of Simple MIMO Schemes for Robust or High Data Rate Transmission Systems in Underground Tunnels. In: 2008 IEEE 68th Vehicular Technology Conference, pp. 1–5. IEEE, Los Alamitos (2008), http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4656914

    Chapter  Google Scholar 

  9. Foschini, G.: Layered space-time architecture for wireless communication in a fading environment when using multi-element antennas. Bell Labs Technical Journal 1(2), 41–59 (1996)

    Article  Google Scholar 

  10. Golden, G.D., Foschini, C.J., Valenzuela, R.A., Wolnianski, P.W.: Detection algorithm and initial laboratory results using v-blast space-time communication architecture. Electronics Letters 35(1), 14–15 (1999)

    Article  Google Scholar 

  11. Goyal, V.K.: Multiple description coding: compression meets the network. IEEE Signal Processing Magazine 18(5), 74–93 (2001)

    Article  Google Scholar 

  12. Hairoud, S., Combeau, P., Cailbault, J.F., Pousset, Y., Cocheril, Y., Berbineau, M.: Acceleration method for a radio propagation simulator based on 3d ray tracing to predict the performances of mimo channels in dynamical railway environment (November 2010)

    Google Scholar 

  13. Joint Video Team Reference Software, http://iphome.hhi.de/suehring/tml/download

  14. Kim, J., Mersereau, R., Altunbasak, Y.: Distributed video streaming using multiple description coding and unequal error protection. IEEE Transactions on Image Processing 14(7), 849–861 (2005)

    Article  Google Scholar 

  15. Kermoal, J., Schumacher, L., Pedersen, K., Mogensen, P., Frederiksen, F.: A stochastic MIMO radio channel model with experimental validation. IEEE J. Sel. Areas Commun. 20(6), 1211–1226 (2002)

    Article  Google Scholar 

  16. Lienard, M., Degauque, P., Molina-Garcia-Pardo, J.M., Maria, J.: Wave propagation in tunnels in a MIMO context – a theoretical and experimental study. Comptes Rendus Physique 7(7), 726–734 (2006)

    Article  Google Scholar 

  17. Mariage, P., Lienard, M., Degauque, P.: Theoretical and experimental approach of the propagation of high frequency waves in road tunnels. IEEE Transactions on Antennas and Propagation 42(1), 75–81 (1994)

    Article  Google Scholar 

  18. Masson, E., Combeau, P., Cocheril, Y., Berbineau, M., Aveneau, L., Vauzelle, R.: Radio wave propagation in arch-shaped tunnels: Measurements and simulations by asymptotic methods. Comptes Rendus Physique 11(1), 44–53 (2010)

    Article  Google Scholar 

  19. Park, J., Oh, T., Lee, S., Bovik, A.C.: Optimal power allocation for minimizing visual distortion over MIMO communication systems. In: IEEE ICIP, pp. 1833–1836 (November 2009)

    Google Scholar 

  20. Sampath, H., Stoica, P., Paulraj, A.: Generalized linear precoder and decoder design for MIMO channels using the weighted MMSE criterion. IEEE Trans. Commun. 49(12), 2198–2206 (2001)

    Article  Google Scholar 

  21. Schwarz, H., Marpe, D., Wiegand, T.: Overview of the Scalable Video Coding Extension of the H.264/AVC Standard. IEEE Transactions on Circuits and Systems for Video Technology 17(9), 1103–1120 (2007)

    Article  Google Scholar 

  22. Shiu, D., Foschini, G., Gans, M., Kahn, J.: Fading correlation and its effect on the capacity of multielement antenna systems. IEEE Trans. Commun. 48(3), 502–513 (2000)

    Article  Google Scholar 

  23. Bae, T.M., Thang, T.C., Kim, D.Y., Ro, Y.M., Kang, J.W., Kim, J.G.: Multiple Region-of-Interest Support in Scalable Video Coding. ETRI Journal 28(2), 239–242 (2006)

    Article  Google Scholar 

  24. Telatar, I.: Capacity of multi-antenna gaussian channels. European Transactions on telecommunications 10(6), 585–595 (1999)

    Article  Google Scholar 

  25. Tse, D., Viswanath, P., Zheng, L.: Diversity and multiplexing: A fundamental tradeoff in multiple antenna channels. IEEE Transactions on Information Theory 49(5), 1073–1096 (2003)

    Article  MATH  Google Scholar 

  26. Wang, Y., Reibman, A., Lin, S.: Multiple Description Coding for Video Delivery. Proceedings of the IEEE 93(1), 57–70 (2005)

    Article  Google Scholar 

  27. Wu, H.R., Rao, K.R.: Digital Video Image Quality and Perceptual Coding. CRC Press, Boca Raton (2006)

    Google Scholar 

  28. Yang, D., Nasruminallah, Yang, L.L., Hanzo, L.: SVD-aided unequal-protection spatial multiplexing for wireless video telephony. In: IEEE 69th Vehicular Technology Conference Spring (April 2009)

    Google Scholar 

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Fatani, I.F.E. et al. (2011). Multiple Description Coding and Scalable Video Coding Combined with Multiple Input Multiple Output Techniques: Two Strategies to Enhance Train to Wayside Video Transmissions in Tunnels. In: Strang, T., Festag, A., Vinel, A., Mehmood, R., Rico Garcia, C., Röckl, M. (eds) Communication Technologies for Vehicles. Nets4Cars/Nets4Trains 2011. Lecture Notes in Computer Science, vol 6596. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19786-4_8

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  • DOI: https://doi.org/10.1007/978-3-642-19786-4_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19785-7

  • Online ISBN: 978-3-642-19786-4

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