<![CDATA[Advanced signal processing techniques have become integral to modern communication systems, enabling efficient data transmission, improved signal quality, and enhanced network performance. This study explores key techniques, including adaptive filtering, wavelet transforms, and multiple-input multiple-output (MIMO) processing, which address challenges such as noise interference, spectral efficiency, and multipath fading. The analysis highlights the theoretical principles and practical applications of these methods in wireless communications, satellite systems, and fibre-optic networks. Comparative evaluations demonstrate the superiority of advanced algorithms in mitigating errors, maximising throughput, and ensuring reliable communication. Experimental results and simulations validate the performance of these techniques under various channel conditions, showcasing their adaptability to dynamic network environments. The research concludes with insights into the future of signal processing, particularly its integration with machine learning and artificial intelligence, to drive the evolution of communication engineering.]]>
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