Visible light communication (VLC) is a relatively new wireless communication technology that
allows for high data rate transfer. Because of its capability to enable high-speed transmission and eliminate
inter-symbol interference, orthogonal frequency division multiplexing (OFDM) is widely employed in VLC.
Peak to average power ratio (PAPR) is an issue that impacts the effectiveness of OFDM systems, particularly
in VLC systems, because the signal is distorted by the nonlinearity of light-emitting diodes (LEDs). The
proposed method Long Short Term Memory-Autoencoder (LSTM-AE) uses an autoencoder as well as
an LSTM to learn a compact representation of an input, allowing the model to handle variable length
input sequences as well as predict or produce variable length output sequences. This study compares the
suggested model with various PAPR reduction strategies to demonstrate that it offers a superior improvement
in PAPR reduction of the transmitted signal while maintaining BER. Also, this model provides a flexible
compromisation between PAPR and BER.