Fractional weighted ZF equalizer: A novel approach for channel equalization in MIMO-OFDM system under impulse noise environment

Main Article Content

S. P. Girija
Rameshwar Rao

Abstract

Impulse noise is the major factor degrading the performance of the wireless system, imposing the need for the impulse noise mitigation strategy. Mainly, in the multiple-input multiple-output (MIMO) and orthogonal frequency-division multiplexing (OFDM) system contaminated with the impulse noise creates a major impact in the performance as the conventional zero-forcing (ZF) equalizer as there is no satisfactory results. Thus, the paper concentrates on the impulse noise mitigation strategy based on the fractional weighed zero-forcing (FWZF) equalizer, which is the integration of the fractional concept in the Zero-Forcing equalizer. The noise impacts in the MIMO-OFDM system are minimized and the performance is enhanced due to the usage of the fractional theory in the ZF equalizer as the equalization values of the previous instances are interpreted for the formulation of the effective equalization value in the current instance of the ZF equalizer. The performance of the methods is done based on the valuation metrics, Bit Error Rate (BER), Mean Square Error (MSE), and Symbol Error Rate (SER) with respect to the Signal-to-Noise Ratio (SNR) and dissimilar antenna array size. It is found that the proposed Fractional Weighed Zero-Forcing equalizer outperformed the existing methods with a minimal BER and SER of 0.063, and 0.1038 while analyzing the methods in the Rayleigh environment.

Downloads

Download data is not yet available.

Article Details

How to Cite
Girija, S. P., & Rao, R. (2021). Fractional weighted ZF equalizer: A novel approach for channel equalization in MIMO-OFDM system under impulse noise environment. Communications in Science and Technology, 6(1), 1-10. https://doi.org/10.21924/cst.6.1.2021.224
Section
Articles

References

R. Pavan, M.T. Silva, M.D. Miranda, A numerically robust blind equalization scheme applied to MIMO communication systems, J. Franklin Inst. 355 (2018) 596-624.

S.P. Girija and K.D. Rao, Smoothing term based noise correlation matrix construction for MIMO-OFDM wireless networks for impulse noise mitigation, TENCON-2015, IEEE Region 10 Conference, Macao, 2015.

Q. Liu, L. Yang, K. Li, Decorrelating bootstrap equalizer for time- variation suppression of MIMO channel, Signal Process. 86 (2006) 1509-1517.

G. Faria, J.A. Henriksson, E. Stare, P. Talmola, DVB-H: Digital broadcast services to handheld devices, Proceed. IEEE, 94 (2006) 194-209.

R. Arablouei, and K. Do?ançay, Low-complexity adaptive decision- feedback equalization of MIMO channels, Signal Process. 92 (2012) 1515-1524.

N. Roži?, P. Banelli, D. Beguši?, J. Radi?, Multiple-threshold estimators for impulsive noise suppression in multicarrier communications, IEEE Trans. Signal Process. 66 (2018) 1619-1633.

Y. Chen, Y. Zhang, H. Shu, J. Yang, L. Luo, J. Coatrieux, Q. Feng, Structure-Adaptive Fuzzy Estimation for Random-Valued Impulse Noise Suppression, IEEE Transact. Circ. Syst. Video Technol. 28 (2018) 414 - 427.

H. Liu, Y. Li, Y. Zhou, H. Chang, T. Truong, Impulsive noise suppression in the case of frequency estimation by exploring signal sparsity, Digital Signal Process. 57 (2016) 34-45.

H. Hosseini, F. Hessar, F. Marvasti, Real-time impulse noise suppression from images using an efficient weighted-average filtering, IEEE Signal Process. Lett. 22 (2015) 1050-1054.

A. Bansal and A.K. Kohli, Suppression of impulsive noise in OFDM system using imperfect channel state information, Optik 127 (2016) 2111-2115.

D. Darsena, G. Gelli, F. Melito, F. Verde, A. Vitiello, Impulse noise mitigation for MIMO-OFDM wireless networks with linear equalization, IEEE Int. Workshop Meas. Net. (M&N), Naples, 2013, pp. 94-99.

N. Benvenuto and S. Tomasin, On the comparison between OFDM and single carrier modulation with a DFE using a frequency-domain feed- forward filter, IEEE Trans. Commun. 50 (2002) 947–955.

Z. Xie, X. Chen, X. Liu, A virtual pilot-assisted channel estimation algorithm for MIMO-SCFDE systems over fast time-varying multipath channels, IEEE Trans. Veh. Technol. 67 (2018) 4901-4909.

Y. Zhang, Y.V. Zakharov, J. Li, Soft-decision-driven sparse channel estimation and turbo equalization for MIMO underwater acoustic communications, IEEE Access 6 (2018) 4955-4973.

N. Al-Dhahir, A.F. Naguib, A.R. Calderbank, Finite-length MIMO decision feedback equalization for space-time blockcoded signals over multipath-fading channels,” IEEE Trans. Vehi. Technol. 50 (2001) 1176–1182.

M. Sellathurai and S. Haykin, A simplified diagonal BLAST architecture with iterative parallel interference cancellation receivers, IEEE Int. Conf. Commun. 10 (2001) 3067–3071.

H. Luo, R.-W. Liu, X. Lin, X. Li, The autocorrelation matching method for distributed MIMO communications over unknown FIR channels, IEEE Int. Conf. Acoustics Speech Signal Process. 4 (2001) 2161–2164.

A. Maleki-Tehrani, B. Hassibi, J.M. Cioffi, Adaptive equalization of multiple-input multiple-output (MIMO) channels, IEEE Int. Conf. Commun. 3 (2000) 1670–1674.

A. Aminjavaheri, A. Farhang, B. Farhang-Boroujeny, Filter bank multicarrier in massive MIMO: Analysis and channel equalization, IEEE Trans. Signal Process. 66 (2018) 3987 - 4000.

J. Coon, M. Sandell, M. Beach, J. McGeehan, Channel and noise variance estimation and tracking algorithms for unique-word based single carrier systems, IEEE Trans. Wireless Commun. 5 (2006) 1488–1496.

N. Benvenuto, R. Dinis, D.D. Falconer, S. Tomasin, Single carrier modulation with nonlinear frequency domain equalization: An idea whose time has come again, Proc. IEEE 98 (2010) 69–96.

Z. Xie, X. Chen, X. Liu, Joint channel estimation and equalization for MIMO-SCFDE systems over doubly selective channels, J. Commun. Net. 19 (2017) 627-636.

X. He, Y. Weng, J. Wang, Z. Pan, Fast convergent frequency- domain MIMO equalizer for few-mode fiber communication systems, Optics Commun. 409 (2018) 131-136.

P. Zhe, Y. Zhu, K.B. Letaief, Robust single-carrier frequency- domain equalization for broadband MIMO systems with imperfect channel estimation, IEEE Trans. Wireless Commun. 17 (2018) 4432-4446.

L. Samara, A.O. Al-Abbasi, R. Hamila, N. Al-Dhahir, Reduced-complexity sparsity-aware joint phase noise mitigation and channel equalization in OFDM receivers, Phys. Commun. 30 (2018) 50-57.

W. Liu, Channel equalization and beamforming for quaternion-valued wireless communication systems, J. Franklin Inst. 354 (2017) 8721-8733.

K. Ramadan, M.I. Dessouky, S. Elagooz, M. Elkordy, F.A. El- Samie, Equalization and carrier frequency offset compensation for underwater acoustic OFDM systems, Annals Data Sci. 5 (2018) 259-272.

P.R. Bhaladhare, A clustering approach for the ?-diversity model in privacy preserving data mining using fractional calculus-bacterial foraging optimization algorithm, Adv. Comput. Eng. 2014 (2014) 396529.

V. Pawar, R. Pawar, K. Nai, Blind time-domain equalizer for doubly-selective channel with reduced time averaging and computational complexity, AEU-Int. J. Electronics Commun. 94 (2018) 187-198.