Proactive Doppler Shift Compensation in Vehicular Cyber-Physical Systems - 2018 PROJECT TITLE :Proactive Doppler Shift Compensation in Vehicular Cyber-Physical Systems - 2018ABSTRACT:In vehicular cyber-physical systems (CPS), safety info, together with vehicular speed and location info, is shared among vehicles via wireless waves at specific frequency. This helps management vehicle to alleviate traffic jam and road accidents. However, Doppler shift existing between vehicles with high relative speed causes an evident frequency shift for the received wireless wave, that consequently decreases the reliability of the recovered safety info and jeopardizes the protection of vehicular CPS. Passive confrontation of Doppler shift at the receiver side isn't applicable thanks to multiple Doppler shifts at each receiver. During this Project, we have a tendency to offer a proactive Doppler shift compensation algorithm based mostly on the probabilistic graphical model. Every vehicle pre-compensates its carrier frequency individually, so that there is no frequency shift from the specified carrier frequency between each try of transceiver. The pre-compensated offset for each vehicle is computed in a very distributed fashion in order to be adaptive to the distributed and dynamic topology of vehicular CPS. Besides, the updating procedure is intended during a broadcasting fashion to reduce Communication burden. It's rigorously proved that the proposed algorithm is convergence guaranteed even for systems with packet drops and random Communication delays. Simulations based on real map and transportation information verify the accuracy and convergence property of the proposed algorithm. It's shown that this methodology achieves nearly the optimal frequency compensation accuracy with a slip approaching the Cramér-Rao lower certain. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Privacy-Preserving Crowdsourced Spectrum Sensing - 2018 RobLoP: Towards Robust Privacy Preserving Against Location Dependent Attacks in Continuous LBS Queries - 2018