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Reducing handoff delay of wireless access in vehicular environments by artificial neural network-based geographical fingerprint

Reducing handoff delay of wireless access in vehicular environments by artificial neural network-based geographical fingerprint

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© The Institution of Engineering and Technology
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Wireless access in vehicular environments (WAVE) can offer service to improve traffic safety and efficiency, and to reduce vehicle pollution. Compared with handheld devices, the chief terminals in vehicular environments, vehicles, have higher mobility. Thus, it can be anticipated that in such environments, the terminal devices may often move from one WAVE mode basic service set (WBSS) to another to exchange data and its probability for the handoff to occur is undoubtedly higher than handheld terminal devices. However, without taking high mobility into consideration, traditional IEEE 802.11 wireless transmissions were insufficient under acute moves. Furthermore, vehicular communications usually take place outdoors and the transmission quality might be influenced by other factors, like the weather. Based on different vehicular environments, this paper probes into the handoff and proposes to establish the geographical fingerprint by artificial neural network (ANN) and adjust the transmitted power of access points (APs) according to the weathers to maintain the service region and signal strength. By the measurements in advance, the handoff points can be established to reduce the handoff delay and the suitable handoff points be adjusted in accordance with vehicle speed.

Inspec keywords: traffic engineering computing; neural nets; geographic information systems; telecommunication computing; radio access networks; mobility management (mobile radio)

Other keywords: wireless access; artificial neural network-based geographical fingerprint; vehicular environments; real-time traffic information; traffic safety improvement; IEEE 802.11 wireless transmissions; handoff delay reduction; vehicle pollution reduction; collision warning; access points

Subjects: Neural computing techniques; Traffic engineering computing; Communications computing; Mobile radio systems; Geography and cartography computing; Radio access systems

References

    1. 1)
      • Cao, D., Xu, J., Wang, P.: `Research on improvement in the handoff performance for high-speed mobile service', Canadian Conf. on Electrical and Computer Engineering, 2005, p. 1157–1160.
    2. 2)
    3. 3)
      • Minho, S., Arunesh, M., William, A.A.: `Improving the latency of 802.11 hand-offs using neighbor graphs', Presented at the Proc. Second Int. Conf. on Mobile Systems, Applications, and Services, 2004, Boston, MA, USA.
    4. 4)
    5. 5)
      • Ramani, I., Savage, S.: `SyncScan: practical fast handoff for 802.11 infrastructure networks', Proc. IEEE INFOCOM 2005, 24th Annual Joint Conf. of the IEEE Computer and Communications Societies, 2005, 1, p. 675–684.
    6. 6)
      • Leu, A.E., Mark, B.L.: `Analysis of handoff interference along arbitrary trajectories in cellular networks', IEEE Wireless Communications and Networking Conf., WCNC, 2004, 4, p. 1969–1974.
    7. 7)
      • Yunpeng, Z., Lothar, S., Georgios, O.: `An error model for inter-vehicle communications in highway scenarios at 5.9 GHz', Presented at the Proc. Second ACM Int. Workshop on Performance Evaluation of Wireless Ad Hoc, Sensor, and Ubiquitous Networks, 2005, Montreal, Quebec, Canada.
    8. 8)
      • Wellens, M., Westphal, B., Mahonen, P.: `Performance evaluation of IEEE 802.11-based WLANs in vehicular scenarios', IEEE 65th Vehicular Technology Conf., VTC2007-Spring, 2007, p. 1167–1171.
    9. 9)
      • T.S. Rappaport . (1996) Wireless communications: principles and practice.
    10. 10)
      • Khan, A.N., Sha Xue, J.: `A new handoff ordering and reduction scheme based on road topology information', Int. Conf. on Wireless Communications, Networking and Mobile Computing, WiCOM 2006, 2006, p. 1–4.
    11. 11)
      • Jun Seob, L., Seok Joo, K., Sang Ha, K.: `Analysis of handoff delay for Mobile IPv6', IEEE 60th Vehicular Technology Conf., VTC2004-Fall, 2004, 4, p. 2967–2969.
    12. 12)
      • Shengdong, X., Meng, W.: `Adaptive variable threshold vertical handoff algorithm', Int. Conf. on Neural Networks and Signal Processing, 2008, p. 366–369.
    13. 13)
    14. 14)
      • Choi, N., Choi, S., Seokt, Y.: `A solicitation-based IEEE 802.11p MAC protocol for roadside to vehicular networks', Mobile Networking for Vehicular Environments, 2007, p. 91–96.
    15. 15)
    16. 16)
      • Velayos, H., Karlsson, G.: `Techniques to reduce the IEEE 802.11b handoff time', IEEE Int. Conf. on Communications, 2004, 7, p. 3844–3848.
    17. 17)
      • Stibor, L., Yunpeng, Z., Reumerman, H.J.: `Evaluation of communication distance of broadcast messages in a vehicular ad-hoc network using IEEE 802.11p', IEEE Wireless Communications and Networking Conf., WCNC 2007, 2007, p. 254–257.
    18. 18)
    19. 19)
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