IEIE Transactions on Smart Processing and Computing

The Institute of Electronics and Information Engineers (대한전자공학회)
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Improved Physical Layer Implementation of VANETs

  • Khan, Latif Ullah (Department of Electrical Engineering, University of Engineering & Technology) ;
  • Khattak, M. Irfan (Department of Electrical Engineering, University of Engineering & Technology) ;
  • Khan, Naeem (Department of Electrical Engineering, University of Engineering & Technology) ;
  • Khan, Atif Sardar (Department of Electrical Engineering, University of Engineering & Technology) ;
  • Shafi, M. (Department of Electrical Engineering, University of Engineering & Technology)
  • Received : 2013.11.22
  • Accepted : 2014.03.20
  • Published : 2014.06.30
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Abstract

Vehicular Ad-hoc Networks (VANETs) are comprised of wireless mobile nodes characterized by a randomly changing topology, high mobility, availability of geographic position, and fewer power constraints. Orthogonal Frequency Division Multiplexing (OFDM) is a promising candidate for the physical layer of VANET because of the inherent characteristics of the spectral efficiency and robustness to channel impairments. The susceptibility of OFDM to Inter-Carrier Interference (ICI) is a challenging issue. The high mobility of nodes in VANET causes higher Doppler shifts, which results in ICI in the OFDM system. In this paper, a frequency domain com-btype channel estimation was used to cancel out ICI. The channel frequency response at the pilot tones was estimated using a Least Square (LS) estimator. An efficient interpolation technique is required to estimate the channel at the data tones with low interpolation error. This paper proposes a robust interpolation technique to estimate the channel frequency response at the data subcarriers. The channel induced noise tended to degrade the Bit Error Rate (BER) performance of the system. Parallel concatenated Convolutional codes were used for error correction. At the decoding end, different decoding algorithms were considered for the component decoders of the iterative Turbo decoder. A performance and complexity comparison among the various decoding algorithms was also carried out.

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