Cognitive vertical handover engine for vehicular communication
Always best connected (ABC) communication is an essential requirement for intelligent transportation system. In this paper, we propose a cognitive vertical handover (CVHO) engine to ensure seamless connectivity on the move. Analytic hierarchy process and artificial neural network are used for the development of the algorithm and MATLAB is used as simulation platform. The CVHO engine, which is knowledge based context aware system, takes into account multiple relevant criteria and previous experiences. This system is capable of performing both voluntary and reflex actions. A detailed literature review is presented to compare this work with the conventional methods of vertical handover. A case study, considering the network selection in a typical highway traffic scenario, which consists of both peer-to-peer (P2P) and mobile networks, is presented for the validation of the design. Three radio access technologies, WLAN (P2P), UMTS and WiMAX (mobile networks), are considered for simulation. The results show that the presented model not only realistically optimizes the best available network on the move but also avoids unnecessary handovers. This algorithm is specific to vehicular communication system and hence variation in network selection with vehicle speed is shown.
cognitive vertical handover (cvho) engine intelligent transportation system (its) radio access technology (rat) analytic hierarchy process (ahp) artificial neural network (ann) software defined radio (sdr)