Machine Learning and Intelligent Communications. Third International Conference, MLICOM 2018, Hangzhou, China, July 6-8, 2018, Proceedings

Research Article

Particle Swarm Optimization Based Location Recommendation for D2D Communication Underlying LTE Cellular Networks

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  • @INPROCEEDINGS{10.1007/978-3-030-00557-3_64,
        author={Chiapin Wang and Ming-Hsun Wu and Te-Sheng Tsai},
        title={Particle Swarm Optimization Based Location Recommendation for D2D Communication Underlying LTE Cellular Networks},
        proceedings={Machine Learning and Intelligent Communications. Third International Conference, MLICOM 2018, Hangzhou, China, July 6-8, 2018, Proceedings},
        proceedings_a={MLICOM},
        year={2018},
        month={10},
        keywords={Device-to-Device (D2D) communication 3GPP Long Term Evolution (LTE) Interference mitigation},
        doi={10.1007/978-3-030-00557-3_64}
    }
    
  • Chiapin Wang
    Ming-Hsun Wu
    Te-Sheng Tsai
    Year: 2018
    Particle Swarm Optimization Based Location Recommendation for D2D Communication Underlying LTE Cellular Networks
    MLICOM
    Springer
    DOI: 10.1007/978-3-030-00557-3_64
Chiapin Wang,*, Ming-Hsun Wu1, Te-Sheng Tsai1
  • 1: National Taiwan Normal University
*Contact email: chiapin@ntnu.edu.tw

Abstract

In this paper, we present a particle swarm optimization based location recommendation scheme (PSO-LR) for Device-to-Device (D2D) Communication underlying Long Term Evolution (LTE) cellular networks. The proposed scheme enables D2D users to move to new locations which provide better link qualities and a higher system capacity. Also, it can balance resource allocation between cellular users and D2D users. The simulation results illustrate that the proposed PSO-LR scheme can effectively improve the total system capacity by location recommendation for D2D users, and reduce both the distance and time of location recommendation by comparison with other location recommendation scheme [11].