Researches On Channel Assignment Algorithm Of Cognitive Radio Sensor Networks

Wireless sensor networks(WSNs)use the unlicensed industrial,scientific,and medical(ISM)band for transmissions.However,with the increasing usage and demand of these networks,the currently available ISM band does not suffice for their transmissions.This spectrum insufficiency problem has been overcome by incorporating the opportunistic spectrum access capability of cognitive radio(CR)into the existing WSNs,thus giving birth to cognitive radio sensor networks(CRSNs).The sensor nodes in CRSNs depend on power sources that have limited power supply capabilities.Therefore,advanced and intelligent radio resource allocation schemes are very essential to perform dynamic and efficient spectrum allocation among sensor nodes and to optimize the energy consumption of each individual node in the network.Radio resource allocation schemes aim to ensure QoS guarantee,maximize the network lifetime,reduce the internode and internetwork interferences etc.This article focuses on the channel assignment problem of CRSNs,aiming to maximize the residual energy,prolong the network lifetime.In general,the main contents of this paper include the following aspects:Firstly,this paper develops a model of data transmission and channel state,which can clearly describe the channel status of CRSNs,effectively portrays the behaviors of secondary nodes,accurately expresses energy consumption of data transmission.This model is the basis of the channel assignment algorithm of CRSNs based on residual energy.Secondly,channel assignment is a resource optimization problem,and different assignment methods have different benefits.CRSNs is a network with limited energy,only highly efficient,energy-saving assignment algorithm can meet the requirements.Basing on the above model,this paper proposes a suitable encoding and decoding method,and then develops a channel assignment algorithm based on particle swarm optimization,which converges faster and can effectively maximize network residual energy,prolong the network lifetime.Finally,the assignment algorithm based on discrete particle swarm optimization allocation method can find a good assignment solution fast,but it will take a long time when the network scale is large.To further improve efficiency and reduce energy consumption,this paper proposes a assignment method based on fruit fly optimization algorithm.A fruit fly individual is independent in searching for food,which can well adapt to changes in the external environment,and even a single individual search fails,it does not affect the search of the entire fruit fly group,so it can quickly find the optimal value.The algorithm converges faster than genetic algorithm and particle swarm optimization,even the problem is large,it also find an optimum channel assignment scheme in a limited time.