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[Author] Hideo MATSUKI(2hit)

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  • Mobile Computing Using Personal Handy-Phone System (PHS)

    Toshiaki TANAKA  Hideo MATSUKI  

     
    INVITED PAPER

      Vol:
    E80-B No:8
      Page(s):
    1118-1124

    Given the tremendous growth in the cellular phone system and the Personal Hadny-phone System (PHS), it is to be expected that demands for mobile computing using those wireless infrastructures, that is mobile computer access, will dramatically increase. This paper describes high-quality and high-speed data transmission technology for PHS mobile computing and current PHS data transmission standardization activities. Furthermore, wireless agent communication and a service example are presented together with the concept of background communication for the coming wireless multimedia services.

  • MMSE Mobile Station Positioning Method Using Signal Strength in Cellular Systems

    Hideyuki MATSUTANI  Ryoji YAMAMOTO  Hideo MATSUKI  Tomoyoshi OONO  Seizo ONOE  

     
    PAPER

      Vol:
    E86-A No:7
      Page(s):
    1593-1602

    A mobile station (MS) positioning method using signal strength is an algorithm to estimate the geographical position of a target MS based on measured strength of signals transmitted to/from the MS from/to multiple base stations (BSs) at known geographical positions. This paper proposes a novel MS positioning method using signal strength in cellular systems. The primary sources of position location error for positioning methods using signal strength are multipath fading and shadowing. Although signal strength averaging can help to reduce the effect of multipath fading, the effect of shadowing still remains. In order to eliminate the error caused by shadowing, the proposed method applies a statistical approach and a minimum mean squared error (MMSE) criterion to determine a position estimate. The performance of the proposed method is compared to that of a maximum likelihood (ML) positioning method and a cell-site positioning method. The performance is obtained by computer simulations and field experiments. A computer simulation result shows that the proposed method can determine position estimates in higher probability than the ML method. Also, it is shown that the proposed method provides higher accuracy than the ML method and the cell-site method.