Transform-Aided Performance Enhancement in Massive MIMO-OTFS Systems over Various Fading Channels

Abstract

Massive Multiple Input Multiple Output or massive-MIMO systems are a cornerstone technology in modern wireless communications, especially in 5G and beyond networks. Including Orthogonal Time Frequency Space modulation (OTFS) in Massive MIMO makes the systems more robust, with further promise for robust performance in both high-mobility and multipath-rich environments. OTFS taps into the delay-Doppler domain representation of the wireless channel, ensuring greater immunity to time-frequency variations and enhanced channel estimation compared to traditional modulation methods. While going through the detailed literature available for OTFS based Massive MIMO system it was seen that a very less work has been carried out in exploring the potential and performance enhancements of the system if the system were implemented using some diverse signal transforms such as DWT, FrFT etc, moreover it has not yet been explored as to see the effect of fading onto these systems by deployment of these diverse transforms, Therefore it leaves a gap in the available literature. This paper focusses on the improvement of the Massive MIMO-based OTFS systems by implementing the systems using more advanced signal transforms such as Discrete Wavelet Transform (DWT) and Fractional Fourier Transform (FrFT) under various fading channels. The simulation results have shown significant improvement in performance when implemented using these advanced transforms.