1st International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications

Research Article

Identification of LOS and NLOS for wireless Transmission

  • @INPROCEEDINGS{10.1109/CROWNCOM.2006.363457,
        author={Serhan  Yarkan and Huseyin  Arslan},
        title={Identification of LOS and NLOS for wireless Transmission},
        proceedings={1st International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications},
        publisher={IEEE},
        proceedings_a={CROWNCOM},
        year={2007},
        month={5},
        keywords={Adaptive systems Autocorrelation Cognitive radio Computational modeling Computer vision Discrete Fourier transforms Receivers Signal to noise ratio Testing Wireless communication},
        doi={10.1109/CROWNCOM.2006.363457}
    }
    
  • Serhan Yarkan
    Huseyin Arslan
    Year: 2007
    Identification of LOS and NLOS for wireless Transmission
    CROWNCOM
    IEEE
    DOI: 10.1109/CROWNCOM.2006.363457
Serhan Yarkan1,*, Huseyin Arslan1,*
  • 1: Department of Electrical Engineering, University of South Florida, 4202 E. Fowler Avenue, ENB-1 18, Tampa, FL, 33620.
*Contact email: syarkan@eng.usf.edu, arslan@eng.usf.edu

Abstract

Distinguishing the transmission status of the communication as line-of-sight (LOS) and non-LOS (NLOS) is of great importance for the wireless communication systems. It is known that for LOS and NLOS, some statistical characteristics of the transmission differ from each other. If the distinction between LOS and NLOS can be made as quick and accurate as possible, ranging based applications and adaptive radio systems like cognitive radios can make use of this information to increase their performances significantly. In this study, a numerical and computationally low complex method for coherent receivers is proposed to discriminate the LOS/NLOS status of the transmission depending on the autocorrelation properties of individual paths. The proposed method is tested for both noise-free and noisy conditions with sum-of-sinusoids (SoS) and inverse discrete Fourier transform (IDFT) based simulation models. It is observed that the proposed method gives good results even for relatively low signal-to-noise ratio (SNR) values