Title :
An Adaptive Genetic Based Cognitive Radio Parameter Adjustment Algorithm
Author :
Aiwei Sun ; Tao Liang ; Yajun Zhang ; Wei Lu
Author_Institution :
Inst. of Commun. Eng., PLA Univ. of Sci. & Tech., Nanjing, China
Abstract :
To overcome the drawbacks such as pre-maturity and the inclination to converge to partial optimum of the standard genetic algorithm, the adaptive genetic algorithm has been proposed in this paper. The adaptive genetic algorithm can change its cross-over probability and mutation probability adaptively according to the iterative times and the value of the cost function to avoid the shortcomings of the standard genetic algorithm. The paper also analyses the dynamic reconfiguration problem in the cognitive radio system which is a key aspect in realizing the optimization of wireless resources management. At last, the proposed algorithm is simulated under three different modes of the OFDM multi-carrier system. The simulation results indicate that the adaptive genetic algorithm can overcome the drawbacks of the standard genetic algorithm effectively, the parameters adjustment outcomes coincide with the expected results.
Keywords :
OFDM modulation; cognitive radio; genetic algorithms; OFDM multicarrier system; adaptive genetic algorithm; cognitive radio parameter adjustment algorithm; cognitive radio system; cost function; crossover probability; dynamic reconfiguration problem; iterative times; mutation probability; wireless resources management; Cognitive radio; Engines; Genetic algorithms; Indexes; Optimization; Standards; Throughput; Adaptive Genetic Algorithm; Cognitive Radio; Fitness Function; Multi-objective Optimization;
Conference_Titel :
Computational Intelligence and Design (ISCID), 2014 Seventh International Symposium on
Print_ISBN :
978-1-4799-7004-9
DOI :
10.1109/ISCID.2014.203