Machine Learning and Intelligent Communications. Second International Conference, MLICOM 2017, Weihai, China, August 5-6, 2017, Proceedings, Part I

Research Article

Recent Advances in Radio Environment Map: A Survey

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  • @INPROCEEDINGS{10.1007/978-3-319-73564-1_25,
        author={Jingming Li and Guoru Ding and Xiaofei Zhang and Qihui Wu},
        title={Recent Advances in Radio Environment Map: A Survey},
        proceedings={Machine Learning and Intelligent Communications. Second International Conference, MLICOM 2017, Weihai, China, August 5-6, 2017, Proceedings, Part I},
        proceedings_a={MLICOM},
        year={2018},
        month={2},
        keywords={Cognitive radio Radio environment map Spectrum trend Spectrum dynamic access Spectrum sharing},
        doi={10.1007/978-3-319-73564-1_25}
    }
    
  • Jingming Li
    Guoru Ding
    Xiaofei Zhang
    Qihui Wu
    Year: 2018
    Recent Advances in Radio Environment Map: A Survey
    MLICOM
    Springer
    DOI: 10.1007/978-3-319-73564-1_25
Jingming Li1,*, Guoru Ding,*, Xiaofei Zhang1,*, Qihui Wu1,*
  • 1: Nanjing University of Aeronautics and Astronautics
*Contact email: lijingmingjlu@163.com, dr.guoru.ding@ieee.org, zhangxiaofei@nuaa.com, wuqihui2014@sina.com

Abstract

Electromagnetic spectrum, the main medium of wireless communication has been over-crowded. Accompanied by the arrival of big data era, the problem of the spectrum scarcity has received people’s attention. The emergence of cognitive radio improves the utilization of the spectrum and provides an effective solution to break the limitations of the traditional static allocation. Radio Environmental Maps (REM) is an enabling technology of cognitive radio which can be intuitive, multi-dimensional display of spectrum information. It provides a visual basis while accessing dynamic spectrum and sharing spectrum. In this paper, the various aspects of REM are studied from the perspective of cognitive radio. Based on the concept of REM, the recent research progress of REM is summarized, and a series of challenges in the construction of spectrum pattern are also highlighted.