Channel frequency response estimation method based on pilot’s filtration and extrapolation
DOI:
https://doi.org/10.20535/RADAP.2019.78.36-42Keywords:
OFDM, digital communication system, wireless channel, channel frequency response, estimation, autoregressive model, Kalman filterAbstract
Introduction. Mobility is one of the main requirements for modern communication system. For OFDM systems it means spreading the wideband signals thru the multipath channel with variable in time parameters. Receiver should estimate channel parameters for demodulation the received signal.
Problem statement. The pilots from current and previous received OFDM symbols are used for channel estimation. Development of channel frequency response estimation method that use only pilots from current received symbol is the task.
Method development. This paper proposes a channel frequency response estimation method based on pilot’s filtration and extrapolation. Method consists of two stages. At first stage performs pilot’s filtration in forward and backward directions by Kalman filter and combining the results in each point. It allows increase the accuracy of channel estimation. At second stage performs extrapolation the channel frequency response between pilots in forward and backward directions and combining the results.
Experimental results. Performed analysis of developed method by statistical modeling on example of communication system with channel frequency response described as second order autoregressive model. The standard deviation of estimation error for developed algorithm and Kalman algorithm was calculated. Mean square error of channel estimation for developed method and method of least square was compared.
Conclusions. Developed algorithm allows decrease the standard deviation of channel frequency response estimation error in comparing with Kalman algorithm. Mean square error of channel frequency response estimation for developed method is lower than for method of least square.
Key words: OFDM, digital communication system, wireless channel, channel frequency response, estimation, autoregressive model, Kalman filter.
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