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Enhancing Transmission Collision Detection for Distributed TDMA in Vehicular Networks

Published:14 July 2017Publication History
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Abstract

The increasing number of road accidents has led to the evolution of vehicular ad hoc networks (VANETs), which allow vehicles and roadside infrastructure to continuously broadcast safety messages, including necessary information to avoid undesired events on the road. To support reliable broadcast of safety messages, distributed time division multiple access (D-TDMA) protocols are proposed for medium access control in VANETs. Existing D-TDMA protocols react to a transmission failure without distinguishing whether the failure comes from a transmission collision or from a poor radio channel condition, resulting in degraded performance. In this article, we present the importance of transmission failure differentiation due to a poor channel or due to a transmission collision for D-TDMA protocols in vehicular networks. We study the effects of such a transmission failure differentiation on the performance of a node when reserving a time slot to access the transmission channel. Furthermore, we propose a method for transmission failure differentiation, employing the concept of deep-learning techniques, for a node to decide whether to release or continue using its acquired time slot. The proposed method is based on the application of a Markov chain model to estimate the channel state when a transmission failure occurs. The Markov model parameters are dynamically updated by each node (i.e., vehicle or roadside unit) based on information included in the safety messages that are periodically received from neighboring nodes. In addition, from the D-TDMA protocol headers of received messages, a node approximately determines the error in estimating the channel state based on the proposed Markov model and then uses this channel estimation error to further improve subsequent channel state estimations. Through mathematical analysis, we show that transmission failure differentiation, or transmission collision detection, helps a node to efficiently reserve a time slot even with a large number of nodes contending for time slots. Furthermore, through extensive simulations in a highway scenario, we demonstrate that the proposed solution significantly improves the performance of D-TDMA protocols by reducing unnecessary contention on the available time slots, thus increasing the number of nodes having unique time slots for successful broadcast of safety messages.

References

  1. R. Baldessari, B. Bdekker, A. Brakemeier, M. Deegener, A. Festag, W. Franz, A. Hiller, et al. 2007. Car 2 Car Communication Consortium Manifesto. Technical Report Version 1.1. CAR 2 CAR Communication Consortium.Google ScholarGoogle Scholar
  2. S. Bharati and W. Zhuang. 2013. CAH-MAC: Cooperative ADHOC MAC for vehicular networks. IEEE Journal on Select Areas of Communication 31, 9, 470--479. Google ScholarGoogle ScholarCross RefCross Ref
  3. S. Bharati and W. Zhuang. 2016. CRB: A cooperative relay broadcasting framework to support safety applications in vehicular networks. IEEE Transactions on Vehicular Technology 65, 12, 9542--9553. Google ScholarGoogle ScholarCross RefCross Ref
  4. S. Bharati, W. Zhuang, L. V. Thanayankizil, and F. Bai. 2017. Link-layer cooperation based on distributed TDMA MAC for vehicular networks. IEEE Transactions on Vehicular Technology (to appear). Google ScholarGoogle ScholarCross RefCross Ref
  5. F. Borgonovo, L. Campelli, M. Cesana, and L. Coletti. 2003. MAC for ad-hoc inter-vehicle network: Services and performance. In Proceedings of the 2003 IEEE Vehicular Technology Conference (VTC’03 Fall).Google ScholarGoogle Scholar
  6. F. Borgonovo, L. Campelli, M. Cesana, and L. Fratta. 2005. Impact of user mobility on the broadcast service efficiency of the ADHOC MAC protocol. In Proceedings of the 2005 IEEE Vehicular Technology Conference (VTC’05 Spring). Google ScholarGoogle ScholarCross RefCross Ref
  7. F. Borgonovo, A. Capone, M. Cesana, and L. Fratta. 2004. ADHOC MAC: New MAC architecture for ad hoc networks providing efficient and reliable point-to-point and broadcast services. Wireless Networks 10, 4, 359--366. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. L. Cheng, B. Henty, F. Bai, and D. D. Stancil. 2008. Doppler spread and coherence time of rural and highway vehicle-to-vehicle channels at 5.9 GHz. In Proceedings of the IEEE Global Communications Conference (IEEE GLOBECOM’08).Google ScholarGoogle Scholar
  9. L. Cheng, B. E. Henty, D. D. Stancil, F. Bai, and P. Mudalige. 2007. Mobile vehicle-to-vehicle narrow-band channel measurement and characterization of the 5.9 GHz dedicated short range communication (DSRC) frequency band. IEEE Journal on Selected Areas in Communications 25, 8, 1501--1516. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Li Deng and Dong Yu. 2014. Deep Learning: Methods and Applications. Technical Report. Retrieved May 22, 2017, from https://www.microsoft.com/en-us/research/publication/deep-learning-methods-and-applications/Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. W. Ding, J. Wang, Y. Li, P. Mumford, and C. Rizos. 2008. Time synchronization error and calibration in integrated GPS/INS systems. ETRI Journal 30, 1, 59--67. Google ScholarGoogle ScholarCross RefCross Ref
  12. J. C. S. Santos Filho, M.D. Yacoub, and G. Fraidenraich. 2007. A simple accurate method for generating autocorrelated Nakagami-m envelope sequences. IEEE Communications Letters 11, 3, 231--233. Google ScholarGoogle ScholarCross RefCross Ref
  13. PTV Group. 2015. PTV Vissim. Retrieved May 22, 2017, from http://vision-traffic.ptvgroup.com/en-us/products/ptv-vissim/.Google ScholarGoogle Scholar
  14. M. Hadded, A. Laouiti, R. Zagrouba, P. Muhlethaler, and L. A. Saidane. 2015. A Fully Distributed TDMA Based MAC Protocol for Vehicular Ad Hoc Networks. Technical Report. Inria Paris Rocquencourt.Google ScholarGoogle Scholar
  15. M. Hadded, P. Muhlethaler, A. Laouiti, and L. A. Saidane. 2016. A centralized TDMA based scheduling algorithm for real-time communications in vehicular ad hoc networks. In Proceedings of the 2016 24th International Conference on Software, Telecommunications, and Computer Networks (SoftCOM’16). Google ScholarGoogle ScholarCross RefCross Ref
  16. M. I. Hassan, H. L. Vu, and T. Sakurai. 2011. Performance analysis of the IEEE 802.11 MAC protocol for DSRC safety applications. IEEE Transactions on Vehicular Technology 60, 8, 3882--3896. Google ScholarGoogle ScholarCross RefCross Ref
  17. J. J. Huang and Y. S. Chiu. 2013. A scheme to reduce merging collisions in TDMA-based VANETs. In Proceedings of the 2013 International Symposium on Wireless Pervasive Computing.Google ScholarGoogle Scholar
  18. IEEE. 2010. IEEE standard for information technology--local and metropolitan area networks--specific requirements--part 11: Wireless LAN medium access control (MAC) and physical layer (PHY) Specifications Amendment 6: Wireless Access in Vehicular Environments. IEEE Std 802.11p-2010 (Amendment to IEEE Std 802.11-2007 as amended by IEEE Std 802.11k-2008, IEEE Std 802.11r-2008, IEEE Std 802.11y-2008, IEEE Std 802.11n-2009, and IEEE Std 802.11w-2009)/ 1--51.Google ScholarGoogle Scholar
  19. William C. Jakes and Donald C. Cox (Eds.). 1994. Microwave Mobile Communications. Wiley-IEEE Press. Google ScholarGoogle ScholarCross RefCross Ref
  20. D. Jiang, V. Taliwal, A. Meier, W. Holfelder, and R. Herrtwich. 2006. Design of 5.9 GHz DSRC-based vehicular safety communication. IEEE Wireless Communications. 13, 5, 36--43. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. M. J. Khabbaz, W. F. Fawaz, and C. M. Assi. 2012. A simple free-flow traffic model for vehicular intermittently connected networks. IEEE Transactions on Intelligent Transportation Systems 13, 3, 1312--1326. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Y. Li and A. Boukerche. 2015. QuGu: A quality guaranteed video dissemination protocol over urban vehicular ad hoc networks. ACM Transactions on Multimedia Computing, Communications, and Applications 11, 4, 55:1--55:23.Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. S. Lin, Y. Li, Y. Li, B. Ai, and Z. Zhong. 2014. Finite-state Markov channel modeling for vehicle-to-infrastructure communications. In Proceedings of the 6th International Symposium on Wireless Vehicular Communications (WiVEC’14). Google ScholarGoogle ScholarCross RefCross Ref
  24. H. Liu, T. Mei, H. Li, J. Luo, and S. Li. 2013. Robust and accurate mobile visual localization and its applications. ACM Transactions on Multimedia Computing, Communications, and Applications 9, 1, 51:1--51:22.Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. F. J. Lopez-Martinez, D. Morales-Jimenez, E. Martos-Naya, and J. F. Paris. 2013. On the bivariate Nakagami-m cumulative distribution function: Closed-form expression and applications. IEEE Transactions on Communications 61, 4, 1404--1414. Google ScholarGoogle ScholarCross RefCross Ref
  26. NHTSA. 2005. Vehicle Safety Communications Project Task 3 Final Report. Technical Report DOT HS 809 859. CAMP Vehicle Safety Communications Consortium.Google ScholarGoogle Scholar
  27. NHTSA. 2012. DOT Launches Largest-Ever Road Test of Connected Vehicle Crash Avoidance Technology. Technical Report. U.S. Department of Transportation (USDoT).Google ScholarGoogle Scholar
  28. H. A. Omar, W. Zhuang, A. Abdrabou, and L. Li. 2013a. Performance evaluation of VeMAC supporting safety applications in vehicular networks. IEEE Transactions on Emerging Topics in Computing 1, 1, 69--83. Google ScholarGoogle ScholarCross RefCross Ref
  29. H. A. Omar, W. Zhuang, and L. Li. 2013b. VeMAC: A TDMA-based MAC protocol for reliable broadcast in VANETs. IEEE Transactions on Mobile Computing 12, 9, 1724--1736. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. Fabrício A. Silva, Azzedine Boukerche, Thais R. M. Braga Silva, Linnyer B. Ruiz, Eduardo Cerqueira, and Antonio A. F. Loureiro. 2016. Vehicular networks: A new challenge for content-delivery-based applications. ACM Computing Surveys 49, 1, 11:1--11:29.Google ScholarGoogle Scholar
  31. R. Wiedemann. 1974. Simulation Des Strassenverkehrsflusses. Schriftenreihe des Instituts fr Verkehrswesen der Universitt Karlsruhe, Band 8, Karlsruhe, Germany.Google ScholarGoogle Scholar
  32. Q. Wu and J. Zheng. 2016. Performance modeling and analysis of the ADHOC MAC protocol for vehicular networks. Wireless Networks 22, 3, 799--812. Google ScholarGoogle ScholarDigital LibraryDigital Library

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