Abstract: In cognitive radio,the cognitive user has to sense all the candidate channels to search idle channels.In practice,its sensing ability is limited,which makes the user sense the channel in one-by-one mode.However,the more channels are to sense till an idle is found,the more time is needed to spend in the sensing process,so that the less time is remainder for transmission.Therefore,sensing order is critical for the spectrum efficiency.In this paper,the optimization of sensing order problem was modeled completely with the idle probability and channel capacity considered,which is different from the previous studies.Since the modeled problem is NP-hard,the traditional optimization lacks computation efficiency.Therefore,the genetic algorithm was adopted.Different from the classical genetic algorithm,the proposed algorithm develops a unique elite reservation strategy.Moreover,three crossing operators were proposed intensively for the problem,i.e.the single-spot crossing,the multiple-spot crossing and the coding crossing.In simulation,the computation complexity and the accuracy are compared between the genetic algorithm and brute force algorithm.After obtaining the advantage of the genetic algorithm,we compared the three proposed crossing operators in terms of expected throughput and maximum throughput,and verified the superiority of the coding crossing operator.

Key words: Genetic algorithm,Channel sensing,Coding crossing,Cognitive radio