Research On The Network Selection Algorithm In Heterogeneous Wireless Networks

Although the cellular mobile communication technology and broadband wirelessaccess technology as well as new access technologies such as cognitive radio aredeveloping continuously, these different wireless access technologies provide users withdifferent service delay, available bandwidth and expenses. There are none of radioaccess technology can meet the user’s different service demands. So the integration ofheterogeneous networks is an inevitable development trend of next-generation networks.How to choose a suitable network to satisfy the users’ service in the heterogeneousenvironment is a key issue to be solved. In this thesis, we take a research on the networkselection algorithm of heterogeneous wireless networks from the perspective of the user.Firstly, based on the depth study of the result of domestic and international networkselection algorithm, we recognize that different network selection algorithm providedifferent utility to users. So we consider the four possible scenarios in the future of theheterogeneous wireless network, such as the low price model scene, the low-powermode scene, file transfer scene and voice service scene. According to the simulationshow that the user can select the MEW （Multiplicative Exponent Weighting）algorithmto get the lowest price in the low price mode scene. And in low-power mode, SAW（Simple Additive Weighting）、TOPSIS（Technique for Order Preference by Similarityto Ideal Solution）、GRA（Grey Relational Analysis） algorithm can all ensure users tochoose the network of lowest power consumption. In file transfer mode, the user shouldselect the TOPSIS algorithm for the reason it can guarantee both of the large transferrate, and the cost. In voice service mode, the user can select the GRA algorithm toguarantee the minimal delay.Secondly, for the scene that a large amount of users must choose a network to switchin the heterogeneous wireless network, users will choose the same network to switch inbecause of each user take the same network selection algorithm. Thus the network willhave a large load, and leads to bad quality of users’ service. So we put forward a conceptof user comfort ratio, and design a network selection algorithm based on the fuzzy logicand neural network algorithm. From the simulation result,we can recognize that the algorithm can not only enable users to select the appropriate network, but also have ahigher user comfort ratio compared to non-adaptive fuzzy logic algorithm. Furthermore,with the increase of the number of users, the gap of the user comfort ratio between thedesigned algorithm and the non-adaptive fuzzy logic algorithm is more significant.