Spectrum Sensing: An integrated approach for 6G VANETs

Abstract

To fulfill the needs of exponentially growing automobiles’ users and to provide services with efficient paths among different bands on demand for these proliferated users, an integrated approach for software-defined vehicular network (SDVN) is proposed in this thesis. Due to this huge increase, DSRC has already been considered insufficient to fulfill the modern needs. Hence, to enhance the network performance and to fulfill the growing needs of users in SDVN environment, we implement cognitive technology by integrating DSRC, sub-6GHZ, and THz bands to find stable paths among different nodes. SDN controller is considered as the main controller (MC) for keeping the global state of all the nodes in the network. Channel sensing is done individually for each technology, and these sensing results representing the number of available bands for secondary communications is updated periodically to the MC. Consequently, the MC is managing these bands by switching between DSRC, sub-6GHz, and THz, and providing stable paths between source and destination. The switching decision is taken by considering the distance and availability of channels among these three technologies. This cognitive integration of bands in SDVN improves the network performance in terms of packet delivery ratio, network delay, and overhead ratio.