A CGLS Method for Efficient Equalization of OFDM Systems under Doubly Dispersive Fading Channels with an Application into 6G Communications in Smart Overcrowded

Because of its superior multipath channel performance and spectrum efficiency, orthogonal frequency-division multiplexing (OFDM) is one of the most suitable candidates for the 6G physical layer in contemporary applications like smart cities and crowded environments in a social Internet of Things (S-IoT) ecosystem. The terahertz (THz) band, 1Tb/s data rate, low latency, spectrum efficacy, and mobility of 1000 km/h are just a few of the requirements that 6G must meet. Using single-tap equalization, OFDM may reduce the multipath channel impact optimally. However, when the channel has doubly dispersive fading, inter-carrier interference starts to create errors. The worst doubly dispersive fading channel will be produced when THz and high-speed mobility are combined with OFDM as the physical layer for 6G. OFDM requires a complicated equalizer when using channels with doubly dispersive fading. On the basis of band factorization, time domain least squares QR (LSQR) iterative computing, and banded minimum mean squared error (BMMSE), a number of low-complexity equalizers for OFDM have been proposed. Conjugate gradient least squares (CGLS), a revolutionary iterative computation algorithm, is proposed in this study; the proposed equalization technique obtains the trade-off between computations and performance. Simulation results show that the proposed equalizer outperforms the existing BMMSE and LSQR algorithms over doubly dispersive fading channels.