Abstract
Universal frequency division multiplexing (UFMC) has obtained a lot of interest in 5G wireless communication. In UFMC systems, the function of channel transfer of radio channel appears unequal in both time and frequency domains. Therefore, estimating a channel dynamically is important for the detection of UFMC signals. There are many estimation methods for UFMC systems. This paper investigates pilot-aided channel estimation techniques for UFMC systems. It is known that least square (LS) and minimum mean square error (MMSE) algorithms are effective channel estimation (CE) methods to produce accurate estimation output. We proposed a novel modified entropy-based least square (MELS) channel estimation method which is based on mean value of the transmitted vector to improve the estimation accuracy of the UFMC system. This paper also explains the analytical analysis of the LS, MMSE and MELS channel estimation techniques. The performance analysis of this channel estimation methods is done by using simulation results. The simulation results are implemented using MATLAB software. The results show that at high values of SNR, the MELS algorithm outperforms the LS and MMSE for both bit error rate (BER) and mean square error (MSE).
Published Version
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