Implementing green optical waveform system using hybrid cognitive methods for QAM transmission scheme

Abstract

Abstract This study proposes a hybrid approach combining Energy Detection (ED) and Matched Filter (MF) spectrum sensing techniques to enhance power spectrum density (PSD) in optical Nonorthogonal Multiple Access (NOMA) systems. Optical NOMA has emerged as a key technology for boosting spectral efficiency in optical communication networks. However, optimizing PSD remains a critical challenge due to various factors including signal detection and noise interference. The hybrid ED–MF spectrum sensing method aims to address these challenges by leveraging the strengths of both techniques. Energy Detection (ED) offers simplicity and robustness in detecting primary users, making it suitable for initial spectrum sensing in cognitive radio networks. Matched Filter (MF) spectrum sensing, on the other hand, provides superior signal detection and noise rejection capabilities, particularly in low signal-to-noise ratio (SNR) environments. By integrating these two techniques, we aim to achieve improved sensitivity and accuracy in spectrum sensing, thus enhancing spectral efficiency and system performance in optical NOMA networks. The effectiveness of the proposed hybrid approach is evaluated through theoretical analysis and simulation experiments. Results demonstrate significant enhancements in spectral efficiency and system reliability compared to conventional spectrum sensing methods, highlighting the potential of the hybrid ED–MF approach for enhancing PSD in optical NOMA systems. This research contributes to advancing the design and optimization of optical communication systems for future high-capacity and high-speed data transmission applications. The PSD values −920 are obtained and it confirmed that the proposed algorithm outperforms the standard algorithms.