Implementation of an Empirical Acoustic Channel Model Using OFDM–DWT Technique

Several environmental factors, such as depth, salinity, frequency, and ambient noise, influence underwater acoustic communication (UAC). These factors reduce the integrity of signals, thereby decreasing system performance and increasing transmission errors. Out of these, noise is a major constraint that reduces communication reliability. To counter this, the current research suggests implementing a denoising technique using the discrete wavelet transform (DWT) combined with orthogonal frequency-division multiplexing (OFDM). Specifically, the DWT soft thresholding method is employed to reduce noise, while OFDM is used to reduce inter-symbol interference (ISI) and enhance spectral efficiency. OFDM combined with DWT is a significant contributor to reducing the bit error rate (BER), as demonstrated by a semi-analytic model used for calculating the BER. The modeled underwater channel impulse response (CIR) consists of 16 discrete taps. The taps have exhibited exponentially decreasing amplitudes between approximately 0.44 and 0.10, thereby modeling accurate energy dispersion and delay spread in shallow aquatic media. Simulation results confirm that the suggested methodology detects a BER of 10-7 at an SNR of 20 dB, with power efficiency measured by a peak-to-average power ratio (PAPR) of 8.5 dB, obtained using MATLAB simulations.