Throughput improvement and PAPR reduction for OFDM-based VLC systems using an integrated STC-IMADJS technique

Abstract

AbstractVisible light communication (VLC) is a technology that is currently being employed to achieve high data rates. Orthogonal frequency division multiplexing (OFDM) is a powerful scheme for intensity modulation and direct detection (IM-DD) that is becoming increasingly important. OFDM systems based on VLC are accomplished through the implementation of IM-DD constraints, including direct current biased optical OFDM (DCO-OFDM), asymmetrically clipped optical OFDM (ACO-OFDM), and asymmetrically clipped DC-biased (ADO-OFDM), among others. The OFDM technique based on VLC is inefficient in terms of spectral efficiency and has a high peak to average power ratio (PAPR). In this article, the symbol time compression-image adjust (STC-IMADJS) technique will be proposed for throughput maximization and PAPR reduction in the DCO-OFDM, ACO-OFDM, and ADO-OFDM systems. Furthermore, the STC technique enables the simultaneous transmission of two sub-carriers through Walsh spreading codes without inference between them. As a result, the OFDM symbol has been reduced by 50%. The IMADJS strategy reduces the high PAPR of transmitted signals by compressing large signals and expanding small signals, as long as the average power level remains constant after compression. Therefore, the proposed STC-IMADJS technique doubles the throughput as well as significantly reduces the PAPR for OFDM systems based on VLC. The simulation results are performed using Matlab-2021a for 1024 sub-carriers. As a result, the simulation results show that the proposed technique reduces the PAPR by 3.7 dB ($$86\%$$ 86 % ), 8.16 dB ($$93\%$$ 93 % ), and 1.81 dB ($$20\%$$ 20 % ) for DCO-OFDM, ACO-OFDM, and ADO-OFDM systems respectively. Furthermore, the technique has a significantly lower computational complexity than conventional OFDM systems based on VLC. Finally, the measures of performance through this article are bit error rate and complementary cumulative distribution function.