Abstract
In order to calculate the branches metric in the maximum a posteriori algorithm of turbo decoder, it is mandatory to know the values of parameters of the noise contaminating the transmitted signal. In the case of a generalized Gaussian distribution impulsive noise, it is very difficult to estimate the shape parameter, because the noise is inseparable from transmitted signal at turbo decoder reception. Until now, few researches about shape parameter estimation for an impulsive noise on turbo codes have been presented, and existing estimation methods use only the high order statistics (HOS). In this paper, we propose a novel semi-blind method, that does not use the HOS, to estimate the shape parameter from only the received signal in the turbo decoder. This method is based on fractional lower order statistics and the probability that the received signal is the same sign as the transmitted signal modulated with BPSK. The results, in terms of root mean square error, show the advantage of our method over other methods using HOS in the case of impulsive noise.
Similar content being viewed by others
References
Ahadiat MR, Azmi P, Haghbin A (2014) Impulsive noise estimation and suppression in OFDM systems over in-home power line channels. Int J Commun Syst
Al-Naffouri TY, Quadeer A, Caire G, 3 (2014) Impulse noise estimation and removal for OFDM systems. IEEE Trans Commun 62:976–989
Anthony L (2006) Blancheur et non-gaussianité pour la déconvolution aveugle de données bruitées : application aux signaux sismiques’. Institut national polytechnique de grenoble, Thèse de Doctorat de L’INPG, le 13 septembre p 113
Berrou C, Glavieux A, Thitimajshima (1993) Near Shannon limit error correction coding: turbo codes. In: Proceedings of IEEE International Conference on Communications, Geneva, Switzerland, pp 1064–1070
Dan W (2013) Improvement for LDPC coded OFDM communication system over power line. Master of Science Thesis performed at the Radio Communication Systems Group, KTH. Stockholm, Sweden
Der-Feng T, Tsung-Ru T, Han YS (2013) Robust turbo decoding in impulse noise channels. In: IEEE, proceedings of IEEE international symposium conference on power line communications and its applications (ISPLC), Johannesburg, 24–27 March, pp 230–235
Graciela GF, Armando DMJ, Ramón MRD (2003) A practical procedure to estimate the shape parameter in the generalized Gaussian distribution. Technique report I-01-18_eng. pdf, available through http://www.cimat.mx/reportes/enlinea/I-01-18_eng.Pdf, Vol. 1
Graciela GF, Armando DMJ, Ramón MRD (2009) Efficiency of the approximated shape parameter estimator in the generalized gaussian distribution. IEEE Trans Veh Technol 58(8):4214–4223
Li X, Xie Y (2013) State estimation based on generalized Gaussian distributions. Metrol Meas Syst XX(1):65–76
Majoul T, Raouafi F, Jaïdane M (2008) Semi-blind turbo decoding in impulsive noise channels. IEEE, ISCCSP 2008, Malta, 12–14 March, pp 810–813
Mallat G (1989) A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans Pattern Anal Mach Intell 7(11):674–693
Regazzoni CS, Sacchi C, Teschioni A, Giulini S (1998) Higher order statistics based sharpness evaluation of a generalized Gaussian PDF model in impulsive noisy environments. In: Proceedings of 9th IEEE workshop on statistical signal and array processing, 411–414
Roenko AA, Lukin VV, Djurovic I, Simeunovic M (2014) Estimation of parameters for generalized Gaussian distribution. In: Proceedings of IEEE International Symposium Conference on Communications, Control and Signal Processing (ISCCSP), 21–23 May Athens, pp 376–379
Sharifi K, Leon-Garcia A (1995) Estimation of shape parameter for generalized Gaussian distributions in subband decompositions of video. IEEE Trans Circuits Syst Video Technol 5(1):52–56
Sumi M, Prasanth M (2014) Periodic impulsive noise reduction in OFDM based power line communication. Int J Res Eng Technol (IJRET) 03(05):517–522
Summers TA, Wilson SG (1998) SNR mismatch and online estimation in turbo decoding. IEEE Trans Commun 46(4):421–423
Taiyue W, Xiusheng L, Yanqing D, Hongwei L (2008) Locally optimum detection of a Noise model based on generalized gaussian distribution. In: Proceedings of IEEE international conference on MultiMedia and information technology, pp 253–256
Varanasi MK, Aazhang B (1989) Parametric generalized Gaussian density estimation. J Acoust Soc Am 86:1404–1415
Walter A (2007) Mathematics for physics and physicists. Princeton University Press, Princeton
Xiaoling H, Nam P (1998) Turbo decoders which adapt to noise distribution mismatch. IEEE Commun Lett 2(12):321–323
Yu S, Zhang A, Li H (2012) A review of estimating the shape parameter of generalized Gaussian distribution. J Comput Inf Syst 8(21):9055–9064
Yunfei C, Norman CB (2009) Novel low-complexity estimators for the shape parameter of the generalized gaussian distribution. IEEE Trans Veh Technol 58(4):2067–2071
Zhijiang X, Kang W, Limin M (2013) Channel parameters estimation algorithm based on the characteristic function under impulse noise environment. Radioengineering 22(4):1034–1040
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Chemsa, A., Saigaa, D., Ghodbane, H. et al. Novel semi-blind estimation for turbo decoding in impulsive noise channel. Int J Syst Assur Eng Manag 8 (Suppl 1), 188–197 (2017). https://doi.org/10.1007/s13198-015-0341-y
Received:
Revised:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13198-015-0341-y