Journal on Communications ›› 2022, Vol. 43 ›› Issue (9): 148-156.doi: 10.11959/j.issn.1000-436x.2022177

• Papers • Previous Articles     Next Articles

Research on elastic handover algorithm of 6G network based on fine-grained slicing

Xiaorong ZHU, Kang CHEN   

  1. Jiangsu Key Laboratory of Wireless Communications, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
  • Revised:2022-08-29 Online:2022-09-25 Published:2022-09-01
  • Supported by:
    The National Natural Science Foundation of China(61871237);The National Natural Science Foundation of China(92067101);Program to Cultivate Middle-aged and Young Science Leaders of Universities of Jiangsu Province;The Key Research and Development Program of Jiangsu Province(BE2021013-3);Jiangsu Province Postgraduate Research and Practice Innovation Program(KYCX21_0733)

Abstract:

With the emergence of high-bandwidth services such as holographic communication and augmented reality in the future, high-bandwidth services will be divided into finer-grained service slices according to the rates to meet diverse requirements of users.For the problem of how to complete network switching in a fine-grained slicing of large bandwidth services, an elastic handover algorithm of 6G network based on bipartite graph stable matching was proposed.By optimizing “user-network slice-base station” association, the total rate of users was maximized, and the access problem was modeled as a hierarchical bipartite graph stable matching problem.Then by using the two matching ideas of “slice base station” integration and “slice first and then base station”, the adaptive handoff of the network was realized by using Gale-Shapley algorithm.Simulation results show that the access success rates of the proposed integrated and two-stage matching algorithms are 15% and 10% higher respectively than that of the traditional method, and the total rate of users is also significantly improved.

Key words: network handover, fine-grained slicing, elastic matching, resource allocation

CLC Number: 

No Suggested Reading articles found!