Abstract
Various methods are available for channel estimation in the orthogonal frequency division multiplexing and orthogonal frequency and code division multiplexing (OFCDM) based wireless communication schemes. Along with this, the most utilized techniques are namely the minimum mean square error (MMSE) and least square (LS). The process of LS channel estimation method is simple but it occupies a very high mean square error. On the other hand, the performance of MMSE is better than LS in terms of SNR, though it shows high computational complexity. Compared to MMSE and LS based techniques, the combination of MMSE and LS techniques using evolutionary programming reduces the error significantly to receive exact signal. In this study, we propose a hybrid method namely GGWO that includes grey wolf optimization (GWO) and genetic algorithms (GA) for estimate the channel in MIMO–OFCDM schemes. At first, the best channel is estimated using GWO and afterwards, the MMSE and LS are hybridized through GA for calculating the best channel to decrease error. Overall, the GWO and GA contribute in fine tuning the obtained channel scheme so that the channel model is derived further to correlate with the ideal scheme. Our results demonstrate that the proposed scheme is superior to conventional MMSE and LS in terms of BER and SNR.
Similar content being viewed by others
References
Stüber, G. L. (2001). Principles of mobile communication (Vol. 2). Boston: Kluwer.
Barry, J. R., & Lopes, R. R. (2005). The extended-window channel estimator for iterative channel-and-symbol estimation. EURASIP Journal on Wireless Communications and Networking, 2, 92–99.
Upadhya, K., Seelamantula, C. S., & Hari, K. V. S. (2016). A risk minimization framework for channel estimation in OFDM systems. Signal Processing, 128, 78–87.
Yi, W., & Leib, H. (2017). OFDM symbol detection integrated with channel multipath gains estimation for doubly-selective fading channels. Physical Communication, 22, 19–31.
Wang, Z., Babu, P., & Palomar, D. P. (2017). Effective low-complexity optimization methods for joint phase noise and channel estimation in OFDM. IEEE Transactions on Signal Processing, 65(12), 3247–3260.
Satya Prasad, K., & Naganjaneyulu, P. V. (2009). An adaptive blind channel estimation of OFDM system by worst case H∞ approach. International Journal of Hybrid Information Technology, 2(4), 1–6.
Chua, B.K., Fausty, O., Pradhan, P. K., & Patra, S. K. (2011). Channel estimation algorithms for OFDM systems. In International conference on electronics systems. Rourkela: National Institute of Technology.
Sang, T., Lam, W. H., & Zeng, Y. (2006). Semiblind channel estimation and equlization for MIMO space–time coded OFDM. IEEE Transactions on Circuits and Systems, 53(2), 463–474.
Wan, F., Swamy, M. N. S., & Zhu, W. P. (2008). A semiblind channel estimation approach for MIMO–OFDM systems. IEEE Transactions on Signal Processing, 56(7), 2821–2834.
Goldberg, D. E. (1989). Genetic algorithm in search optimization and machine learning. Reading, MA: Addison-Wesley.
Garg, H., Rani, M., Sharma, S. P., & Vishwakarma, Y. (2014). Intuitionistic fuzzy optimization technique for solving multi-objective reliability optimization problems in interval environment. Expert Systems with Applications, 41, 3157–3167.
Sheikhalishahi, M., Ebrahimipour, V., Shiri, H., Zaman, H., & Jeihoonian, M. (2013). A hybrid GA–PSO approach for reliability optimization in redundancy allocation problem. International Journal of Advanced Manufacturing Technology, 68, 1–22.
Garg, H. (2015). A hybrid GA–GSA algorithm for optimizing the performance of an industrial system by utilizing uncertain data. In Handbook of Research on Artificial Intelligence Techniques and Algorithms (pp. 620–654). IGI Global.
Quadeer, A. A., & Al-Naffouri, T. Q. (2010). ML blind channel estimation in OFDM using cyclostationarity and spectral factorization. In IEEE eleventh international workshop on signal processing advances in wireless communications (SPAWC) (pp. 1–5).
Ozdemir, M., & Arslan, H. (2007). Channel estimation for wireless OFDM systems. IEEE Communications Surveys Tutorials, 9(2), 18–48.
Morelli, M., & Mengali, U. (2001). A comparison of pilot-aided channel estimation methods for OFDM systems. IEEE Transactions on Signal Processing, 49(12), 3065–3073.
Van De Beek, J. J., Edfors, O., Sandell, M., Wilson, S. K., & Borjesson, P. O. (1995). On channel estimation in OFDM systems. In IEEE 45th conference in vehicular technology (Vol. 2, pp. 815–819).
Edfors, O., Sandell, M., van de Beek, J. J., Wilson, S., & Borjesson, P. (1998). OFDM channel estimation by singular value decomposition. IEEE Transactions on Communications, 46(7), 931–939.
Huang, L., Bergmans, J., & Willems, F. M. J. (2007). Low-complexity LMMSE based MIMO–OFDM channel estimation via angle-domain processing. IEEE Transactions on Signal Processing, 55(12), 5668–5680.
Noh, M., Lee, Y., & Park, H. (2006). Low complexity LMMSE channel estimation for OFDM. IEE Proceedings Communications, 153(5), 645–650.
Li, Y., Cimini, L. J., & Sollenberger, N. R. (1998). Robust channel estimation for OFDM systems with rapid dispersive fading channels. IEEE Transactions on Communications, 46(7), 902–915.
Jakes, W. C. (1975). Microwave mobile communications. New York: Wiley.
Minn, H., & Bhargava, V. (2000). An investigation into time-domain approach for OFDM channel estimation. IEEE Transactions on Broadcasting, 46(4), 240–248.
Tomasoni, A., Gatti, D., Bellini, S., Ferrari, M., & Siti, M. (2013). Efficient OFDM channel estimation via an information criterion. IEEE Transactions on Wireless Communications, 12(3), 1352–1362.
Kang, Y., Kim, K., & Park, H. (2007). Efficient DFT-based channel estimation for OFDM systems on multipath channels. IET Communications, 1(2), 197–202.
Krondorf, M., Liang, T. J., Irmer, R., & Fettweis, G. (2006). Improved channel estimation for complexity-reduced MIMO–OFDM receiver by estimation of channel impulse response length. In Proceeding of the 12th European wireless conference—enabling technologies for wireless multimedia communications (pp. 1–6).
Yu, M., & Sadeghi, P. (2012). A study of pilot-assisted OFDM channel estimation methods with improvements for DVB-T2. IEEE Transactions on Vehicular Technology, 61(5), 2400–2405.
Mirjalili, S., Mirjalili, S. M., & Lewis, A. (2014). Grey wolf optimizer. Advances in Engineering Software, 69, 46–61.
Zhou, Y., & Wang, J. (2006). Downlink transmission of broadband OFCDM systems-part IV: Soft decision. IEEE Journal on Selected Areas in Communications, 24(6), 1208–1220.
Bagadi, K. P., & Das, S. (2010). MIMO–OFDM channel estimation using pilot carries. International Journal of Computer Applications, 2(3), 81–88.
Schober, K., & Wichman, R. (2009). MIMO–OFDM channel estimation with eigen beamforming and user-specific reference signals. In IEEE 69th conference on vehicular technology conference.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Sujitha, J., Baskaran, K. Genetic Grey Wolf Optimizer Based Channel Estimation in Wireless Communication System. Wireless Pers Commun 99, 965–984 (2018). https://doi.org/10.1007/s11277-017-5161-8
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11277-017-5161-8