• DocumentCode
    3291038
  • Title

    Block decoding using the Dorsch Algorithm

  • Author

    Rahman, H.A. ; Rahman, F.Y.A. ; Kadir, Ros Shilawani S Abd ; Khalid, M.F.A. ; Naim, Nani Fadzlina

  • Author_Institution
    Fac. of Electr. Eng., MARA Univ. of Technol., Shah Alam
  • fYear
    2008
  • fDate
    2-4 Dec. 2008
  • Firstpage
    427
  • Lastpage
    430
  • Abstract
    The aim of this research is to investigate the Dorsch algorithm performance in the decoding process of binary Hamming codes. The conventional decoding method is hard decision based whereby the message of the demodulator is quantized only to two levels. An important feature of the Dorsch algorithm is that it uses soft decision decoding. Soft decision occurs if the output of the demodulator is quantized to more than two levels. The algorithm uses soft decision information to rank the reliability of the received symbols. The high reliability symbols are treated as the soft decision of the information values whereas the low reliability symbols are treated as parity checks for the information values. The error performance of both the decoding methods were evaluated and concluded. It was observed that Dorsch Algorithm produces better performance compared to the conventional hard decision decoding.
  • Keywords
    Hamming codes; binary codes; block codes; decoding; demodulation; parity check codes; Dorsch algorithm; binary Hamming codes; block decoding; demodulator; parity check code; soft decision decoding; AWGN; Additive white noise; Bit error rate; Block codes; Decoding; Demodulation; Equations; Error correction; Gaussian noise; Parity check codes; Additive White Gaussian Noise; Bit Error Rate; Block Codes; Soft Decision Decoding;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    RF and Microwave Conference, 2008. RFM 2008. IEEE International
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-1-4244-2866-3
  • Electronic_ISBN
    978-1-4244-2867-0
  • Type

    conf

  • DOI
    10.1109/RFM.2008.4897471
  • Filename
    4897471