Research On Key Technologies Of Access Selection In Heterogeneous Wireless Networks

With the development of various wireless network technologies,various wireless networks such as cellular networks,wireless local area networks,wireless personal networks,and wireless metropolitan area networks have emerged.Each wireless network has great differences in signal coverage,transmission rate,support service characteristics,mobility,etc.The coexistence of these wireless networks forms heterogeneous wireless networks.At the same time,the wireless access capability of mobile user terminal equipment is also expanding,and it can support access to a variety of different types of wireless networks.How to enable a mobile terminal in a heterogeneous wireless network environment to select the most suitable network has become a research hotspot of heterogeneous wireless networks.In this paper,the concept of access selection in heterogeneous wireless network environment is analyzed firstly,then the access selection algorithm is classified,and the reference literature is studied in detail.Finally,some problems in access selection research are summarized.In response to these problems,this paper proposes the following access selection methods:(1)To better describe user characteristics in a heterogeneous wireless network environment,this paper designs a network selection algorithm based on service characteristics and user preferences.First,user services are divided into different types,and utility functions are used to calculate the utility value of each network attribute for different services.Next,the entropy method and the Fuzzy-Analytic Hierarchy Process(FAHP)are used to calculate the objective weight and subjective weight of network attributes respectively,with FAHP specifically being used to calculate the user preference values of services for candidate networks.Finally,Simple Additive Weighting(SAW),Multiplicative Exponent Weighting(MEW),and Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)are used according to network attribute utility values and weights to calculate the score of each candidate network.These scores are converted into a comprehensive score for the candidate network based on such user preferences,thus obtaining the ranking of candidate networks.Simulation results show that the proposed algorithm can allow users to choose the most suitable network to access according to different service characteristics while reducing the number of network handovers.(2)In order to optimize the transmission performance of heterogeneous wireless networks in the access process,this paper proposes a parallel access selection method based on optimal bandwidth resource allocation.Firstly,a parallel access and bandwidth resource allocation model is designed.The wireless link transmission rate is analyzed according to the characteristics of the wireless link,and the problem is modeled as maximizing the system transmission rate.Then,based on the dynamic programming theory,the problem solving process is divided into several interconnected stages according to the number of users,and the problem of maximizing the system transmission rate in all user situations is converted into a sub-problem of the maximum transmission rate under different user numbers,and the optimal value for allocating bandwidth to the user is derived.Finally,the user is connected to the appropriate network based on the rate requirements of the user's service.Simulation experiments show that the proposed algorithm can effectively improve the system transmission performance in multilink parallel transmission scenarios.(3)In order to achieve the candidate network score and bandwidth allocation value in the access selection process,this paper proposes a joint access selection and bandwidth allocation method in heterogeneous wireless networks.This method designs an algorithm framework for joint access selection and bandwidth allocation based on fuzzy neural network structure.The framework includes an input module,a fuzzy logic decision module,an output module,and a learning module.The input module considers the three aspects,including wireless link status,network performance,and user requirements.It also uses received signal strength,network load,and user rate requirements as input decision parameters.The fuzzy logic decision module obtains the scores and bandwidth allocation values of candidate networks through three steps of fuzzification,fuzzy inference,and defuzzification.In addition,the learning module corrects the parameters of the membership function in the fuzzy neural network structure through supervised learning.This algorithm can allow users to select the most suitable network and get the bandwidth allocation value.Furthermore,it can adjust the resource utilization of different networks and better meet the user requirements.