# A Survey on Physical Layer Techniques and Challenges in Underwater Communication Systems
## 4 UWA Modern Technologies  
In the future, UWCs can be used for the examination of the sea, preservation of biology, and coastal protection with fast speed and rabid-reliable communication. To obtain a high data rate and accuracy, the UWC systems need to integrate advanced technology. The substantial design associated with the novel technique of modulation for estimation of channel for time-varying underwater channels, design of transceiver having medium access control (MAC) and spatial diversity, and multiuser multiple input (MU-MIMO) or full-duplex protocol design underwater systems is categorized under the progressive technologies. Artificial intelligence (AI) schemes are used as well to make enhance wireless communications and networks underwater. The performance of the UWC can be enhanced by using profound and complicated communication systems. It aids in managing a huge number of requirements with great strength and system capacity. It also allows for deeper sea exploration. UWCs researchers have been interested in artificial intelligence due to its better performance. Recently, UWA modern technologies has been introduced in a brief although there are many papers published dealing with UWAC [180; 181; 182]. UWWC's contemporary technologies are depicted in Figure 19.  
ML algorithms, particularly deep learning, have shown great promise in improving the performance of UWAC systems. Deep learning techniques can be used for tasks, such as signal processing, feature extraction, and modulation classification. For example, convolutional neural networks (CNNs) have been used to improve the accuracy of acoustic signal classification in underwater environments. Additionally, ML can be used for channel estimation, equalization, decoding, and improving the reliability of UAC systems. Recent research has also explored the use of ML for underwater acoustic localization and tracking of mobile underwater platforms. For instance, recurrent neural networks (RNNs) and long short-term memory (LSTM) networks have been used to improve the accuracy of UWA source localization. IoUT is a network of underwater devices that can communicate with each other to collect and exchange information. IoUT can enable real-time monitoring of the ocean environment, improve the efficiency of underwater operations, and enable remote control of underwater devices. IoUT can be used in conjunction with UAC to improve the reliability and efficiency of UWC. Some of the challenges of IoUT include the limited range of UWWC, the low data rate of acoustic communication, and the high energy consumption of underwater devices. To overcome these challenges, researchers are exploring new wireless communication technologies, such as UWOC and UWAC, at higher frequencies. NOMA is a multiple-access technique that allows multiple users to share the same frequency and time resources. NOMA can improve the spectral efficiency of UWAC systems, which is critical for high data rates applications, such as video streaming and underwater imaging. In underwater environments, the limited bandwidth and high signal attenuation make it challenging to achieve high data rates. NOMA can improve the efficiency of UWC systems by allowing multiple users to share the available bandwidth. Recent research has explored the use of NOMA for multiple-access UWC systems, demonstrating significant improvements in spectral efficiency and user capacity. Energy harvesting techniques can be used to power underwater devices without the need for external power sources. Energy harvesting can enable the long-term and autonomous operation of underwater devices, reducing the need for costly and complex maintenance operations. Several energy harvesting techniques can be used in underwater environments, including solar cells, thermoelectric generators, and piezoelectric generators. Solar cells can harvest energy from sunlight, but their effectiveness is limited in underwater environments due to the limited availability of sunlight.