Communications and Networking. 12th International Conference, ChinaCom 2017, Xi’an, China, October 10-12, 2017, Proceedings, Part II

Research Article

Fast Group Paging Algorithm for Large-Scale MTC Systems

  • @INPROCEEDINGS{10.1007/978-3-319-78139-6_36,
        author={Si Huang and Xiaohui Li and Bin Zhou and Yanbin Zhao and Ruiyang Yuan},
        title={Fast Group Paging Algorithm for Large-Scale MTC Systems},
        proceedings={Communications and Networking. 12th International Conference, ChinaCom 2017, Xi’an, China, October 10-12, 2017, Proceedings, Part II},
        proceedings_a={CHINACOM},
        year={2018},
        month={4},
        keywords={Machine-type communication Group paging Low-complexity iteration method Severe congestion},
        doi={10.1007/978-3-319-78139-6_36}
    }
    
  • Si Huang
    Xiaohui Li
    Bin Zhou
    Yanbin Zhao
    Ruiyang Yuan
    Year: 2018
    Fast Group Paging Algorithm for Large-Scale MTC Systems
    CHINACOM
    Springer
    DOI: 10.1007/978-3-319-78139-6_36
Si Huang1, Xiaohui Li1,*, Bin Zhou2, Yanbin Zhao3, Ruiyang Yuan1
  • 1: Xidian University
  • 2: AVIC Computing Technique Research Institute
  • 3: Geographic Information Center
*Contact email: xhli@mail.xidian.edu.cn

Abstract

Group paging (GP) is an effective way to solve the serious congestion problem. Congestion problem usually is caused by lots of machine-type communication (MTC) devices communicating at the same time. A certain number of MTC devices in each time slot is been activated, and the number of MTC devices can achieve the maximum of resource utilization. First of all, the total number of MTC devices in each time slot should be calculated according to the different new arrivals in each time slot. By making the resources utilization maximum, the optimal number of total MTC devices can be obtained, from which the optimal number of arriving MTC devices in each time slot will be get. To estimate the total number of MTC devices for traffic scattering GP, a Fast Group Paging Algorithm (FGPA) is proposed, which aims to improve the performance of GP under the condition of massive MTC devices. FGPA is an iterative algorithm that converges fast and has low arithmetic complexity. The corresponding simulation results demonstrate that the proposed FGPA requires less number of iterations under the condition of the same estimation results of total number of MTC devices compared with the existing iterative algorithm.