Research Article
Load Balancing Mechanism Based on Sparse Matrix Prediction in C-RAN Networks
@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
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.
