• Rachanagouda kamatigi
• Siddaling B
• Sharangouda patil
• Veeresh K
• Sharanabasappa  Sali

This research explores the use of deep neural networks (DNNs) to enhance the efficiency of OFDM systems in underwater acoustic communication, which is challenging due to factors like multipath propagation, frequency fluctuations, and limited frequency range. We propose a novel DNN architecture integrated with OFDM technology to improve channel estimation and equalization. Extensive simulations and real-world tests demonstrate that our approach significantly outperforms previous methods, achieving higher data rates and more reliable communication in underwater environments. This study highlights the potential of deep learning to revolutionize underwater acoustic networks.

DNN, OFDM, acoustic networks etc...

" Underwater Accoustic OFDM Network Systems with Deep Neural Nets", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 8, page no.e708-e717, August-2024, Available :http://www.jetir.org/papers/JETIR2408582.pdf

" Underwater Accoustic OFDM Network Systems with Deep Neural Nets", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 8, page no. ppe708-e717, August-2024, Available at : http://www.jetir.org/papers/JETIR2408582.pdf