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Communications and Networking. 14th EAI International Conference, ChinaCom 2019, Shanghai, China, November 29 – December 1, 2019, Proceedings, Part I

Research Article

Load Balancing Mechanism Based on Sparse Matrix Prediction in C-RAN Networks

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  • @INPROCEEDINGS{10.1007/978-3-030-41114-5_54,
        author={Yang Liu and Zhanjun Liu and Ling Kuang and Xinrui Tan},
        title={Load Balancing Mechanism Based on Sparse Matrix Prediction in C-RAN Networks},
        proceedings={Communications and Networking. 14th EAI International Conference, ChinaCom 2019, Shanghai, China, November 29 -- December 1, 2019, Proceedings, Part I},
        proceedings_a={CHINACOM},
        year={2020},
        month={2},
        keywords={Sparse matrix Matrix block Load balancing},
        doi={10.1007/978-3-030-41114-5_54}
    }
    
  • Yang Liu
    Zhanjun Liu
    Ling Kuang
    Xinrui Tan
    Year: 2020
    Load Balancing Mechanism Based on Sparse Matrix Prediction in C-RAN Networks
    CHINACOM
    Springer
    DOI: 10.1007/978-3-030-41114-5_54
Yang Liu1,*, Zhanjun Liu1, Ling Kuang1, Xinrui Tan1
  • 1: School of Communication and Information Engineering
*Contact email: liuzj@cqupt.edu.cn

Abstract

In order to solve the problem that the existing algorithms in large-scale networks have high complexity in adjusting power iteratively, a load balancing mechanism based on sparse matrix prediction is proposed to achieve load balancing in C-RAN architecture. In order to minimize the correlation degree of load transfer and the balance of load transfer, the optimal sparse matrix block is obtained combined with Ncut cutting algorithm to realize dimension reduction and zero removal of the load transfer matrix. After the block, the load transfer matrix of each block is recalculated, and the load transfer matrix is used to predict the load. Finally, combined with the predicted load, the power adjustment step size is determined, and the pilot signal power of each block is adjusted in parallel to achieve load balancing. The simulation results show that the load balancing mechanism can reduce the complexity of load balancing.

Keywords
Sparse matrix Matrix block Load balancing
Published
2020-02-27
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-41114-5_54
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