MADM and Rank Similarity-Based Network Selection Algorithm in Heterogeneous Networks

Abstract

In order to provide better service for the users, this paper put forwards a new algorithm for network selection. Firstly, the algorithm acquires weights’ vectors by analytic hierarchy process (AHP), G-1, entropy weighting method (EW) and variable coefficient (VC). Then combine the weights’ vector according to the similarity of different methods. Finally select the target network with the best performance. The simulation results show that the proposed algorithm can provide subscribers with better quality of service.