An Optimized Vertical Handover Decision Model for the Heterogeneous DSRC/LTE Vehicular Networks

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Engineering and Technology Publishing

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Among a variety of Vehicle-to-Everything (V2X)-supporting access technologies, Dedicated Short Range Communication (DSRC) and cellular communications, e.g., Long Term Evolution (LTE) network is promising reliable and efficient vehicular communications. DSRC has been designed to allow for direct low-latency communications among different vehicles i.e., Vehicle-to-Vehicle (V2V) and between vehicles and Roadside Units (RSU). On the other hand, DSRC suffers from link quality degradation with the presence of buildings and vehicles, especially in urban areas, where channel collisions become serious when vehicle density is high. LTE networks can provide wide area coverage and are favorable to bandwidth-greedy applications, which require high data rates and reliability. Considering the relatively high end-to-end delay for message transmission due to the long Transmission Time Interval (TTI) current LTE networks have drawbacks regarding latency to support high-frequency safety-related information exchange among vehicles in local areas. Combining LTE and DSRC approaches as a heterogeneous solution is essential to fast introduce V2X services for future automated driving. By this intelligent Vertical Handover (VHO) algorithms are needed to ensure seamless connectivity of vehicles to the best network at a particular point in time. For this paper, we propose a 3-input fuzzy-logic-based VHO scheme for Heterogeneous DSRC/LTE Vehicular Communication Networks. The 3 input parameters for the fuzzy logic design were the Received Signal Strength (RSS), Signal to Interference & Noise Ratio (SINR), and Vehicular velocity. A vehicular density scenario was considered for the simulation of the proposed algorithm. Due to the inclusion of vehicular velocity as a parameter, the proposed algorithm enabled the vehicles to establish a longer connection based on their velocity with less decision delay to the best network available. � 2023 by the authors.

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