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| In this paper, the authors first review the increasing demand of broadband wireless communications for high-speed rail (HSR) and the challenges yet to be addressed. By developing and exploiting a dedicated radio environment map (REM) for high-speed rail, a novel cognitive radio (CR) approach is proposed to deal with the various challenging issues, such as fast channel estimation and adaptation under doubly selective fading, large Doppler spread, signalling storm and fatal communication disruption resulting from frequent group handover, coexistence and spectrum management issues. CR-based system architecture and cognitive signal processing algorithms are introduced for HSR broadband wireless communications, which have numerous benefits and advantages over the traditional approach. In addition, the REM-based cognitive channel estimation algorithm is proposed to acquire the channel coefficient efficiently and accurately. Simulations show that the performance of HSR broadband wireless communications can be improved significantly due to CR's situation awareness and learning capability by utilizing the comprehensive environmental information from a spatial-temporal database－REM. The parameters in the REM for HSR can be updated or fine-tuned through cognitive learning algorithms so that the performance of HSR broadband wireless communications can be continuously optimized along the repetitive movement of high-speed train on a fixed course. The CR approach presents a new paradigm for systems design and optimization of HSR broadband wireless communications. |
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| Keywords:Broadband wireless communication; cognitive radio; high-speed rail; radio environment map |
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