Adaptive Modulation of DCO-OFDM for Internet of Underwater Things Using VLC

This paper proposes an adaptive modulation scheme for direct current-biased optical orthogonal frequency division multiplexing (DCO-OFDM) in underwater Internet of Things (IoUT) applications using visible light communications (VLC). The objective of the adaptive scheme is to reduce the bit error rate (BER). The system continuously monitors the signal-to-noise ratio (SNR) and separates each symbol into eight SNR groups. The modulation order is then dynamically adjusted based on the measured SNR to optimize performance. Pilot-based channel estimation is employed to obtain accurate SNR measurements. The study considers various modulation formats, including binary phase-shift keying (BPSK), 4-quadrature amplitude modulation (4-QAM), 16-QAM, 64-QAM, and 256-QAM, along with different fast Fourier transform (FFT) sizes. Numerical simulations conducted using MATLAB demonstrate that the adaptive scheme effectively adjusts the modulation order based on the SNR. Additionally, the FFT size has minimal impact on the BER.