Research Article
Optimize Spectrum Allocation in Cognitive Radio Network
@INPROCEEDINGS{10.1007/978-3-319-73712-6_21, author={Nidhi Patel and Ketki Pathak and Rahul Patel}, title={Optimize Spectrum Allocation in Cognitive Radio Network}, proceedings={Future Internet Technologies and Trends. First International Conference, ICFITT 2017, Surat, India, August 31 - September 2, 2017, Proceedings}, proceedings_a={ICFITT}, year={2018}, month={2}, keywords={Cognitive radio Spectrum allocation Primary user Secondary user Dynamic spectrum access Genetic algorithm}, doi={10.1007/978-3-319-73712-6_21} }- Nidhi Patel
Ketki Pathak
Rahul Patel
Year: 2018
Optimize Spectrum Allocation in Cognitive Radio Network
ICFITT
Springer
DOI: 10.1007/978-3-319-73712-6_21
Abstract
With rapid evolution in wireless devices increases the demand for radio spectrum. To solve spectrum underutilization problem cognitive radio technology is introduced. Cognitive radio technology is next generation technology which allows non-licensed user to use electromagnetic spectrum without interfering licensed user. To use white space in radio spectrum one should sense the spectrum perfectly. Once sensing is done, the distribution of the spectrum among the secondary user is also challenging task. Optimizing is the process to find best solution among the available solutions. Radio environment is random in nature. Due to fast convergence property of the genetic algorithm can use to find optimal solution for spectrum allocation problem to maximizing spectral utilization. Problem is modeled as Multi Objective Problem (MOP), considering that function as fitness function and evaluating the best allocation among all. Firstly defining target objective function that is minimizing Bit Error Rate (BER), maximizing throughput and minimizing power, then using aggregate sum approach, it converts all single objective function into one MOP. Than mathematically applying the fitness function in software so we get graphical representation. We have check convergence of algorithm first. Than we simulate result for single channel and multichannel performance. By observation of graphical parameter we have simulate results for real scenario and get optimum parameter for given situation.
