"JOURNAL OF RADIO ELECTRONICS" (Zhurnal Radioelektroniki ISSN 1684-1719, N 12, 2017

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D. R. Valiullin, P. N. Zakharov

 M.V. Lomonosov Moscow State University, Faculty of Physics, Leninskie Gory Bldg. 1-2, Moscow 119991, Russia


The paper is received on December 5, 2017


Abstract. The frequency-selective fading inherent in multipath channels leads to the inter-symbol interference, which affects the data transmission reliability. Implementation of the equalizer in data transmission system exploits the inter-symbol interference thus increasing the energy efficiency at the receiver. The existing decision feedback equalizer (DFE) and maximum-likelihood sequence estimator (MLSE) have following disadvantages: DFE has poor energy efficiency and MLSE is computationally complex. The neural network equalizer algorithm proposed in this paper has proved to have better performance in terms of the energy efficiency than DFE, while having the similar computational complexity. The neural network equalizer was implemented in the data transmission system along with carrier recovery, clock recovery, automated gain control, matched filtering, interleaving, de-interleaving, turbo-coding, turbo-decoding blocks. The energy efficiency of the neural network equalizer was experimentally estimated in different conditions: 1) single-path flat radio frequency channel with AWGN. The effects of carrier frequency offset between the transmitter and the receiver (up to 5kHz) and the Doppler shift (up to 150 Hz) were investigated; 2) stationary multipath channel environment. The performance of the equalizer with different number of iterations was measured; 3) non-stationary fast-varying multipath channel. The impact of the step size in learning procedure of the equalizer on the performance was investigated. In addition, the combination of the proposed neural network equalizer and turbo-code was investigated in all the mentioned channels in order to test the equalizer’s performance in data transmission system.

Key words: equalizer, multipath channel, neural networks, inter-symbol interference.


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For citation:
D. R.Valiullin, P. N.Zakharov. Experimental performance estimation of neural network equalizer with learning in multipath radio frequency channel. Zhurnal Radioelektroniki - Journal of Radio Electronics. 2017. No. 12. Available at http://jre.cplire.ru/jre/dec17/10/text.pdf.