EMERGING DIGITAL SIGNAL PROCESSING TECHNIQUES FOR ENHANCED COMMUNICATION SYSTEMS

Abstract

The rapid advancements in communication technology necessitate the integration of sophisticated Digital Signal Processing (DSP) techniques to improve signal quality, bandwidth efficiency, and real-time processing capabilities. This study explores modern DSP methodologies tailored for Electronic and Communication Engineering (ECE) applications, including Adaptive Beamforming for enhanced spatial filtering, MIMO-OFDM for improved spectral efficiency, and Kalman Filtering for real-time signal estimation and error correction. Additionally, the application of Fast Wavelet Transform (FWT) in multi-resolution analysis and Digital Predistortion (DPD) for non-linearity compensation in power amplifiers is examined. These advanced techniques are evaluated in terms of bit error rate (BER), signal-to-noise ratio (SNR) improvement, and energy efficiency. A comparative analysis demonstrates the superiority of these approaches over conventional methods in mitigating signal degradation, optimizing bandwidth utilization, and enhancing system reliability. By leveraging these cutting-edge DSP techniques, the study aims to contribute to the evolution of next-generation wireless communication networks with improved robustness and performance.