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A Green Load Balancing Algorithm for Dynamic Spatial-Temporal Traffic Distribution in HetNets

  • Jichen Jiang
  • Xi Li
  • Hong Ji
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 237)

Abstract

With the increasing users demands, the data traffic in the network reveal different characteristics in both spatial and temporal dimensions, bringing severe load imbalance problem. This may impact resource utilization, users experience and system energy efficiency, and then need further investigation. In this paper, we propose a distributed load-balancing algorithm considering this spatial-temporal variation in a two-tier heterogeneous network. Instead of illuminating the spatial-temporal influence, we make use of this characteristic while designing the algorithm, and accordingly switch ON/OFF small cell base stations (SBSs) for improving the energy efficiency. A load factor described with load variance is derived, based on which the problem is formulated as a non-linear integer programming that seeks to minimize a load function. Then a suboptimal solution is obtained by an effective heuristic algorithm. Simulation results show that our proposed algorithm balances the traffic load better and significantly reduces the total energy consumption, compared with conventional load-balancing scheme.

Keywords

Spatial-temporal variation Load balance Small cell ON/OFF 

Notes

Acknowledgement

This paper is jointly sponsored by the National Natural Science Foundation of China (Grant No. 61671088) and the National Science and Technology Major Project of the Ministry of Science and Technology of China (Grant No. 2016 ZX03001017).

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Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018

Authors and Affiliations

  1. 1.Key Laboratory of Universal Wireless Communications, Ministry of EducationBeijing University of Posts and TelecommunicationsBeijingPeople’s Republic of China

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