PAPR Reduction Technique for Mobile Communication Systems Using Neural Networks

Autor(es)

da Silva, Bianca S. de C. ; de Souza, Pedro H. C. ; Mendes, Luciano L.

• Tipo de documento: Artigo Científico
• Fonte: IEEE Latin America Transactions; v. 23, n. 7, p. 9-pg., 2025-07-01.

Resumo

This work proposes a new solution to reduce the PAPR in OFDM systems using NN. The NN leverages a training dataset generated by the MCSA, which fine-tunes the NN for attaining a similar PAPR reduction of the MCSA. Compared to traditional techniques such as the PTS, the proposed solution offers superior performance by achieving a PAPR reduction of up to 4 dB. Nevertheless, a significant advantage is that the trained NN presents a lower computational complexity compared to the MCSA, without compromising its PAPR reduction capabilities. (AU)

• Processo FAPESP: 22/09319-9 - Centro de Ciência para o Desenvolvimento em Agricultura Digital - CCD-AD/SemeAr
• Beneficiário: Silvia Maria Fonseca Silveira Massruhá
• Modalidade de apoio: Auxílio à Pesquisa - Centros de Ciência para o Desenvolvimento