Abstract—Efficient spectrum decision and spectrum mobility schemes for cognitive radio based inter vehicle communication (IVC) system have been anticipated in this research. Cognitive Radio has four main functions, spectrum sensing, spectrum management, spectrum mobility and spectrum sharing. At high speed of vehicles performing spectrum decision and spectrum mobility is not an easy task for cognitive radio. Spectrum mobility is very frequent in IVC due to extremely mobile nature of vehicles and unpredictable radio frequency channel. A proficient white space optimization technique is a basic requirement to perform in time spectrum decision and spectrum mobility. Genetic Algorithm (GA) is considered as one of the best optimization techniques for white space optimization. But at high vehicular speed simple genetic algorithm (GA) has been botched to perform optimization. To anticipate this problem, we have already proposed Memory Enabled Genetic algorithm (MEGA) in our previous work. In this research work we have further improved the convergence time of MEGA by manipulating the generation gap, crossover and mutation operator of MEGA. Simulation results proved that improved memory enabled genetic algorithm (IMEGA) is 0.522 ms faster than MEGA. Simulation results revealed that using our proposed spectrum decision and spectrum mobility schemes are more efficient cognitive radio based vehicular networks.

Index Terms—V2V communication, genetic algorithm, cognitive radios, spectrum mobility, MEGA, IMEGA.


Cite: Atta-ur-Rahma, "Efficient Decision Based Spectrum Mobility Scheme for Cognitive Radio Based V2V Communication System," Journal of Communications, vol. 13, no. 9, pp. 498-504, 2018. Doi: 10.12720/jcm.13.9.498-504.