LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Low-Band Information and Historical Data Aided Non-Uniform Millimeter Wave Beam Selection Algorithm in 5G-R High-Speed Railway Communication Scene

Photo from wikipedia

Millimeter wave (mmWave) communication is one of the critical technologies of the fifth generation mobile communication. It can meet the increasing demand for high-speed railway (HSR) communications services. However, configuring… Click to show full abstract

Millimeter wave (mmWave) communication is one of the critical technologies of the fifth generation mobile communication. It can meet the increasing demand for high-speed railway (HSR) communications services. However, configuring mmWave links, which can be more complicated than that at lower frequency band, is a large source of overhead due to a large number of antennas and high path loss. In this paper, we assume a hybrid frequency system model with both low-frequency band and high-frequency band in the HSR communication scene to meet high data-rate and reliability requirements. Then, we make use of low-band channel information and historical data as the prior information to aid non-uniform mmWave beam selections, which is called Low-Band-and-Historical-Data-Aided-Non-Uniform-Beams-Selection (LBHDANUBS) algorithm. Moreover, we take into account the frequency dependence and time dependence of the same channel to more accurately simulate the characteristics of HSR channels. LBHDANUBS algorithm can not only help to improve the accuracy of beam selections, but also reduce the beam overhead in the training phase and improve the stability of the system. Our simulation results further verify that the proposed scheme based on the low-band information and historical data is superior to the traditional method like exhaustive search and Orthogonal Matching Pursuit (OMP) algorithm.

Keywords: band; information; communication; beam; low band; historical data

Journal Title: IEEE Transactions on Vehicular Technology
Year Published: 2022

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.