• DocumentCode
    2451691
  • Title

    Study on Channel Estimation Technology in OFDM System

  • Author

    Liu Nanping ; Yuan, Yuan ; Xia Kewen ; Zhang Zhiwei

  • Author_Institution
    Sch. of Inf. Eng., Hebei Univ. of Technol., Tianjin, China
  • fYear
    2009
  • fDate
    25-26 April 2009
  • Firstpage
    773
  • Lastpage
    776
  • Abstract
    The technique of orthogonal frequency division multiplexing (OFDM) channel estimation is an important topic being studied in the fourth generation mobile communications. It is significant in increasing the capacity of the system and the efficiency of the frequency spectrum. The traditional channel estimation algorithms have the disadvantages of performance worsening and they are all hard to obtain good performance in the transmission efficiency and operational precision, so a new method based on insertion pilot method and regression least square support vector machine (RLS-SVM) algorithm is proposed. Firstly, the frequency responses of the positions of pilot frequencies and the frequency responses between the carriers are obtained, then the frequency responses of the positions of the subsequent subcarriers are predicted by applying RLS-SVM algorithm. The simulation result shows that increasing with SNR, performance of this method is better than all the traditional methods when applied to OFDM system. At the same transmission rate, the number of pilot frequencies in RLS-SVM algorithm is less than that in traditional algorithms, so the transmission efficiency of the system is improved. In a word, the performance of RLS-SVM is far and away better than that of traditional methods.
  • Keywords
    4G mobile communication; OFDM modulation; channel capacity; channel estimation; least squares approximations; regression analysis; support vector machines; telecommunication computing; wireless channels; OFDM system; channel capacity; channel estimation technology; fourth generation mobile communication; frequency spectrum; insertion pilot method; regression least square support vector machine; Artificial intelligence; Channel estimation; Frequency estimation; Interpolation; Least squares approximation; Mobile communication; OFDM modulation; Quadrature amplitude modulation; Quadrature phase shift keying; Support vector machines; Channel Estimation; OFDM; Pilot Frequency; RLS-SVM;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence, 2009. JCAI '09. International Joint Conference on
  • Conference_Location
    Hainan Island
  • Print_ISBN
    978-0-7695-3615-6
  • Type

    conf

  • DOI
    10.1109/JCAI.2009.173
  • Filename
    5159117