Research On Vertical Handoff Algorithm In Heterogeneous Wireless Networks

With the diversification of communication service requirements and the rapid development of broadband wireless access technologies,distinctive wireless access networks have emerged.A variety of different types of wireless access technologies coexist and complement each other,forming a heterogeneous wireless network with overlapping coverage,providing users with diverse service requirements.Vertical switching technology ensures seamless roaming and session continuity for users moving in heterogeneous network environments.The multi-attribute vertical switching algorithm has been deeply studied in vertical switching due to its high effectiveness,high flexibility and low algorithm complexity.The calculation of network parameter weights and the preferred ranking of candidate networks are key technologies for multi-attribute vertical switching algorithms.In this paper,the multi-attribute vertical switching algorithm is deeply studied.The specific contents are as follows:Firstly,based on the research of multi-attribute vertical switching algorithm,the corresponding improved algorithm is given.The improved algorithm improves the network parameter weights to the coarse interval type,and improves the candidate network ranking method to the proximity-based approximation ideal solution ordering method.The improved algorithm can reduce the weight subjectivity and improve the accuracy of sorting.Simulation experiments verify the correctness of the improved algorithm.Secondly,in the study of network parameter weights,an improved algorithm for improving the accuracy is given for the accuracy of weights.The algorithm changes the weight value into a triangular fuzzy number,which reduces the subjectivity and improves the accuracy.For the ordering of the candidate networks,the ranking is determined by the degree of possibility.The performance of the improved algorithm was verified by simulation experiments.Finally,based on the research of candidate network ordering and weighting problem,a new algorithm is proposed.The algorithm uses foreground theory to rank candidate networks.The foreground theory integrates the environment in which decision makers are located and the degree of risk preference is in line with human decision-making behavior.For weights,it can reflect the subjective judgment of decision makers and reflect the actual network.The combined weight of the difference in parameters.The algorithm finally combines the foreground theory with the comprehensive weight to select the optimal network.Simulation experiments verify the performance of the algorithm.