A macro-cell statistical location estimation method for TD-SCDMA networks

  • Authors:

  • Hong Tang;Ting Li;Tianshuang Qiu;Yongwan Park

  • Affiliations:

  • School of Electronic and Information Engineering, Dalian University of Technology, 116024, PR China;School of Electronic and Information Engineering, Dalian University of Technology, 116024, PR China and College of Electromechanical and Information Engineering, Dalian Nationalities University, 1 ...;School of Electronic and Information Engineering, Dalian University of Technology, 116024, PR China;Mobile Communication Laboratory, Yeungnam University, Kyongsan-city, Kyongbuk, 712-749, Korea

  • Venue:
  • Signal Processing
  • Year:
  • 2009

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Abstract

TD-SCDMA is an innovative wireless radio standard for a physical layer 3G air interface, approved as one 3GPP standards by ITU in May 2000. Based on the unique advantages of the physical layer, this paper investigates network-based methods to obtain the angle of arrival (AOA) and time of arrival (TOA) via subspace tracking and channel impulsive estimation. By incorporating the spatial-temporal channel of radio propagation, this paper proposes a unified objective function to extract mobile location information from the statistical distribution of AOA and TOA data in a TD-SCDMA cellular network. The proposed method may estimate mobile position even using one base station. The location performances are analyzed in detail in macro-cell scenarios. This method can be easily extended to other networks except TD-SCDMA, provided that the statistical information of the local radio propagation channel is available as pre-knowledge. Simulation comparing several hybrid location methods in two macro-cell scenarios show that the proposed method has a high accuracy; but it has a relatively high complexity.