International Journal of Information Technology and Computer Science (IJITCS)
IJITCS Vol. 4, No. 8, 8 Jul. 2012
Cover page and Table of Contents: PDF (size: 1077KB)
Performance of Linear Block Coding for Multipath Fading Channel
Full Text (PDF, 1077KB), PP.51-56
Views: 0 Downloads: 0
Author(s)
Hemlata Sinha
1,*
M.R. Meshram
2
G.R. Sinha
1
Index Terms
BER, BPSK, Linear block code, SNR, Viterbi algorithm, Maximum-likelihood sequence estimator (MLSE), ISI
Abstract
This paper deals with the performance of linear block codes which provide a new paradigm for transmission over multipath fading channels. Multi path channel fading is the main enemy for any wireless communications system. Therefore, for any novel approach applied at any wireless communication system, its efficiency is measured according to its ability of mitigating the distortion caused by fading. It causes time dispersion to the transmitted symbols resulting in inter symbol interference (ISI). ISI inter symbol interference problem is a major impairment of the wireless communication channel. To mitigate the ISI problem and to have reliable communications in wireless channel, channel equalizer and channel coding technique is often employed. In this paper the BER (Bit Error Rate) performance is shown from analytically and by means of simulation for multipath dispersive channels. We have designed a channel equalizer using MLSE (Viterbi algorithm) in this paper for such a multipath channel (introducing inter symbol interferences) with BPSK modulation based on the assumption that the channel can be perfectly estimated at the receiver. Obviously the performance of channel coding in terms of BER is better than uncoded channel.
Cite This Paper
Hemlata Sinha, M.R. Meshram, G.R. Sinha, "Performance of Linear Block Coding for Multipath Fading Channel", International Journal of Information Technology and Computer Science(IJITCS), vol.4, no.8, pp.51-56, 2012. DOI:10.5815/ijitcs.2012.08.06
Reference
[1]John R. Barry, E. A. Lee, D. G. Messerschmitt, Digital Communication, 3rd ed, Kluwer Academic.
[2]John Proakis, Digital Communications, 4th ed. McGraw-Hill Higher Education, 2000.
[3]Andre Neubauer, Jurgen Freudnberger, Coding Theory,1st ed,John Wiley & Sons,Ltd 2007.
[4]Viterbi, Andrew J. and Audrey M. Viterbi. Nonlinear Estimation of PSK Modulated Carrier Phase with Application to Burst Digital Transmission. IEEE Trans. Information Theory, July 1983,29(4):543-551.
[5]John R. Barry, E. A. Lee, D. G. Messerschmitt, Digital Communication, 3rd ed, Kluwer Academic. Journal of Software,2001,12(9):1336-1342(in Chinese)
[6]Yannis Kopsinis and Sergios Theodoridis. An efficient low complexity technique for MLSE equalizers for linear and non linear channels. IEEE Trans. On Signal Processing, December 2003,51(12).
[7]Bernard Sklar. Rayleigh Fading Channel in Mobile Digital Communication System Part I: Characterization. IEEECommunication Magazine, July 1997, 90-100.
[8]Simon Haykin. Digital Communication. Wiley – India.
[9]Rong-Hui Peng, Rong-Rong. Chen Markov Chain Monte Carlo Detectors for Channels with Intersymbol Interference. IEEE transactions on signal processing , april 2010 , 58( 4).
[10]Yannis Kopsinis and Sergios Theodoridis. An efficient low complexity technique for MLSE equalizers for linear and non linear channels. IEEE Trans. On Signal Processing December 2003,51(12).
[11]G. D. Forney, Jr..Maximum likelihood sequence estimation of digital sequences in the presence of intersymbol interference. IEEE Trans. Inform. Theory, May1972 , 18: 363–378.
[12]Yannis Kopsinis and Sergios Theodoridis. An efficient low complexity technique for MLSE equalizers for linear and non linear channels .IEEE Trans. On Signal Processing, December 2003,51(12).
[13]W. Sauer-Greff, et al. Adaptive Viterbi Equalizers for Nonlinear Channels, in Proc. IEEE SignalProcessing Poznan, Poland, 2000.
[14]Andrew J. Viterbi. Error Bounds for Convolutional Codes and an Asymptotically Optimum Decoding Algorithm. IEEE Transactions on Information Theory, April, 1967,13:260-269.