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Self-organized Resource Allocation Based on Traffic Prediction for Load Imbalance in HetNets with NOMA

  • Jichen Jiang
  • Xi Li
  • Hong Ji
  • Heli Zhang
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 234)

Abstract

With the development of mobile communication technology, the data traffic of wireless cellular network has grown rapidly in the past decade. Because of the various bandwidth-eager applications and users movement, load imbalance has become an increasing severe problem, impacting the user experience and communication efficiency. Especially, it may lead to the degrading of resource utilization and network performance. In this paper, we investigate this problem and propose a self-organized resource allocation algorithm that allocates the resource to somewhere that the resource is needed to deal with the load imbalance problem. The typical heterogeneous network with non-orthogonal multiple access (NOMA) is discussed. A traffic prediction model is applied to the NOMA system. Then the self-organized resource allocation is formulated as a mixed integer non-linear programming (MINP) problem aiming at maximizing the overall throughput. The optimization problem is hard to tackle so we propose an algorithm to obtain a suboptimal solution via quantum-behaved particle swarm optimization (QPSO) algorithm. To evaluate how the resource is allocated according to the data traffic requirements, an indicator called evolved balance factor (EBF) is proposed to jointly consider the resource utility and the distribution of data traffic. Simulation results show that the proposed algorithm achieves a better performance in the overall throughput compared with exiting schemes.

Keywords

Self-organized Resource allocation Traffic prediction NOMA Load imbalance 

Notes

Acknowledgments

This paper is jointly sponsored by the National Natural Science Foundation of China (Grant No. 61671088) and the National Natural Science Foundation of China for the Youth (Grant No. 61501047).

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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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