Spectrum Allocation of Cognitive Radio Network Based on Improved Cuckoo Search Algorithm
ZiYun Xin, Damin Zhang, ZhongYun Chen · 2019
In order to effectively solve the discrete optimization problem of cognitive radio network spectrum allocation, a new binary adaptive cuckoo search (BACS) algorithm is proposed, which introduces reverse learning in the initialization stage of traditional cuckoo search (CS), it increases the diversity of the population. Second, the adaptive discovery probability balances the ability of global and local optimization. Finally, a cognitive wireless network spectrum allocation method based on binary adaptive cuckoo algorithm is proposed, and compared with the classical spectrum allocation algorithm for network benefit function and fairness. The simulation shows that BACS has better optimization ability and can be used to maximize the network benefits and fairness between users when applied to spectrum allocation.