Computational study demonstrates improved peak-to-average power ratio reduction in OFDM multicarrier systems, suggesting enhanced signal fidelity via dilated convolutions and recovery modules.
Orthogonal Frequency Division Multiplexing (OFDM) technology, renowned for its multicarrier transmission paradigm, encounters a formidable challenge characterized by an elevated Peak-to-Average Power Ratio (PAPR). This phenomenon can precipitate an escalation in signal distortion. In this study, we present an innovative approach wherein a neural network is harnessed to enhance the attenuation of PAPR, synthesizing the techniques of peak clipping and dilated convolution. Simultaneously, a recovery module is integrated to optimize the signal quality post-suppression, especially at the receiver's terminal. Our empirical findings manifest a noteworthy upswing in the efficacy of PAPR suppression, underscoring the remarkable performance augmentation realized through the proposed methodology.
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Ge et al. (2024) studied this question.
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