Efficient Hybrid Channel Estimation and Adaptive Equalization Framework in Wireless Communication System

On considering the “Intelligent Reflecting S urface-Assisted Multi-User Communication (IRS -MUC)” framework, channel estimation is regarded as the major task. Moreover, being different from the conventional communication system, the IRS -MUC system has included the cascaded channel along with sophisticated statistical distribution techniques. The IRS -MUC system with a huge amount of antennas over the Base Station (BS) has been validated without signal processing and active receiving capability. Moreover, the Minimum Mean Square Error (MMS E) acquires a integrated calculation, which is more significant for implementation. Along with the maximization of demand over the higher data rate, modern communication techniques are more complex. Consequently, equalization has also become a more significant process as it has the ability to mitigate the multipath fading that is often attained in a high- data-rate communication system. So, to tackle the limitations presented in the existing techniques, a novel “fused channel estimation and adaptive equalization approach for the broadband wireless communication system (WCS)” is developed in this work. Initially, the channel estimation approach named Invariable Step-S ize Zero-Attracting Normalized Least Mean S quare (IS S -ZA-NLMS) is mainly utilized to improve the Adaptive Sparse Channel Estimation (ASCE). Further, the estimated channel is used for performing the transmission of signal in the further phases, which it includes two techniques. Then, techniques of adaptive equalization are utilized over the signal on the receiver side to offer the error-free Electrocardiogram (ECG) with the weight optimization. At last, the objective of the recommended model is analyzed depending upon “convergence rate, correlation coefficient, and MSE”. Finally, the suggested fused channel estimation and adaptive equalization framework for the broadband WCS is analyzed over different measures and also secure the process of enhanced channel estimation and equalization rate over the conventional techniques through the experimental analysis.