Modified Entropy based Least Square Channel Estimation for OFDM and UFMC 5G Systems (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2022)
The 5G network is anticipated to enable a sizable volume of wireless connections and mobile data traffic. A demand for several wireless communication is to attain greater spectrum, energy-efficiency, as well as quality of service (QoS) in terms of delay, dependability, and security. A developing technology for 5G wireless communication systems is massive multiple-input multiple-output (MMIMO). In MMIMO technology the main criteria for the transfer of information are multi carrier modulation (MCM) techniques for better spectral efficacy. It acts as a main part in the design of physical layer. In recent years orthogonal frequency division multiplexing (OFDM) MCM technique has played a vital role for the transmission of the information. But the main disadvantage of the OFDM system is the cyclic prefix that is added at the end of information. Because of this CP the symbol length also increases. To overcome the problem universal filtered multicarrier (UFMC) MCM technique is used. The other main criteria for the transmission of information are channel estimation (CE). 5G MMIMO systems require efficient CE technique to improve the performance of the system. For 5G MMIMO-UFMC systems, this research provides a modified entropy-based least square (MELS) CE approach. This research work is evaluated using MATLAB software. The performance analysis of UFMC and OFDM systems are done for MELS CE technique. The parameters such as bit error rate (BER) and mean square error (MSE) are analyzed for UFMC and OFDM systems. The results also prove that the proposed MELS CE technique performs better for UFMC 5G MMIMO system compared to OFDM 5G MMIMO system.