# A Survey on Physical Layer Techniques and Challenges in Underwater Communication Systems
## 2 UWAC Physical Layer Techniques
### Multicarrier Modulation for the UWAC
#### 2.1.1 Orthogonal Frequency Division Multiplexing
_Interference Mitigation:_ Interference is a common issue in UWAC, and CP-OFDM can be adapted to mitigate interference. For example, frequency hopping can be used to avoid interference from other sources or adaptive interference cancellation algorithms can be used to remove interference from the received signal. _Synchronization:_ Synchronization is critical in CP-OFDM for UWAC due to the long propagation delays and Doppler shifts in the channel. Adaptive synchronization algorithms can be used to maintain synchronization between the transmitter and receiver, even in the presence of channel variations and environmental changes. In summary, CP-OFDM is adapted for UWAC by taking into account the specific requirements and constraints of the underwater environment and communication channel. These adaptations can improve the reliability and performance of the communication system and ensure effective communication in challenging underwater environments. Zero Padding Orthogonal Frequency Division Multiplexing  
In ZP-OFDM (Zero Padding Orthogonal Frequency Division Multiplexing), the guard interval is placed after the data block and is filled with zeros. Unlike the CP-OFDM receiver, the ZP-OFDM receiver does not discard the samples from the guard interval. Instead, it uses a method called overlap and adds, which involves adding the samples from the guard interval to the received samples that correspond to the beginning of the OFDM data block. The resulting sequence is then subjected to Fourier transform. Figure 7 illustrates the transformation in the processing of the receiver in ZP-OFDM and CP-OFDM. The advantages of CP-OFDM and ZP-OFDM are compared in [77]. It is observed that ZP-OFDM is better than CP-OFDM due to the following reasons:  
1. Regardless of the position of channel nulls, ZP-OFDM assures symbol recovery because it facilitates linear channel equalization. Figure 6: The transmitting process of ZP-OFDM and CP-OFDM [75]. 2. ZP-OFDM offers better flexibility to practice a range of diverse methods to channel equalization and estimation. 3. Compared to CP-OFDM, ZP-OFDM, with a semi-blind pilot-based estimation of channel trails, better channel variations. The single weakness of ZP-OFDM, according to [77], is its relation to the PAPR, and thus inducing clipping. Since ZP-OFDM presents somewhat added nonlinear variations in comparison to CP-OFDM, it requires marginally extra increased power back-off. The issue of power back-off was discussed in [78]. Here, the PAPR is observed to be reduced using a non-binary LDPC code in aggregation with ZP-OFDM. An added disadvantage for ZP-OFDM is the retaining of guard samples, compulsory for the overlap and adds process in an interference condition. The ZP-OFDM technique retains interference that occurs on the samples, while interference that arises in the guard band is removed along with the CP in CP-OFDM. In this study, ZP-OFDM was chosen as it is the prevailing choice for UWAC systems. Additionally, the interference cancellation method proposed in [79] was applied to ZP-OFDM. The use of ZP-OFDM enables a more direct comparison between the present work and previous literature. Figure 8 shows the receiver basic processing chain for the received OFDM signal through an underwater channel. First, a bandpass filter (BPF) removes any noise outside the frequency band of interest. Next, the received signal is synchronized using the known packet preamble. The main Doppler effect is eliminated through coarse estimation and re-sampling before the packet is partitioned into blocks. The time-domain waveform is then downshifted to low pass filtering (LPF) and baseband, followed by conversion to the frequency domain through addition, overlap, and FFT. After compensating for any remaining Doppler effect (e.g., estimation and compensation of carrier frequency offset (CFO)), the estimate of channel and equalization of the signal is accomplished. The processing steps have been completed through symbol detection and decoding.