A Statistical Modeling Approach to Location Estimation
IEEE Transactions on Mobile Computing
The predictive user mobility profile framework for wireless multimedia networks
IEEE/ACM Transactions on Networking (TON)
A Cross-Layer (Layer 2 + 3) Handoff Management Protocol for Next-Generation Wireless Systems
IEEE Transactions on Mobile Computing
Mobility models for vehicular ad hoc networks: a survey and taxonomy
IEEE Communications Surveys & Tutorials
Handover in Mobile WiMAX Networks: The State of Art and Research Issues
IEEE Communications Surveys & Tutorials
Traffic pattern detection in a partially deployed vehicular Ad Hoc network of vehicles
IEEE Wireless Communications
Mobility modeling, location tracking, and trajectory prediction in wireless ATM networks
IEEE Journal on Selected Areas in Communications
Predictive mobility support for QoS provisioning in mobile wireless environments
IEEE Journal on Selected Areas in Communications
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For the improvement of the quality of service (QoS) of wireless Internet users traveling in vehicles, it is effective to reduce the service disruption time by avoiding unnecessary handover occurrence, considering the vehicles' movement paths. This paper proposes a handover scheme suitable for users traveling in vehicles, which enables continuous learning of the handover process using a discrete-time Markov chain (DTMC). The proposed handover scheme avoids unnecessary handover trials when a short dwell time in a target cell is expected or when the target cell is an intermediate cell through which the vehicle quickly passes. For verifying the performance of the proposed scheme, we observe the average number of handover trials and the average throughput along various paths, which are real bus lines. The results show that the proposed scheme reduces the number of handover occurrences and maintains adequate throughput.