## 3 Simulation Results  
Figure 2 depicts the BER performances of the UFMC-based underwater transceiver with an LDPC code, PCE and CEEs of 5% and 10%. The circle, square, and triangle symbols denote the BER performances with PCE and CEEs of 5% and 10%, respectively, in Figures 2-4. The solid and dashed lines denote the BER performances using 4-QAM, and 16-QAM, respectively, in Figures 2-4. The Matlab-based underwater channel model [26] was adopted. The parameters of the adopted MATLAB-based underwater channel model are listed in Table 2. The transmitter was set 3 m beneath the sea surface, the receiver 2 m beneath the sea surface, the water 14.5 m deep, the direct path at a range of 100 m, the  
carrier frequency at 40 kHz, and the channel bandwidth at 20 kHz. In the underwater channel model, the water sound speed was 1539 m/s. In addition, the channel delay profile was generated by using a MATLAB-based underwater channel model [26]. The BER of the proposed system was below \(10^{-3}\), thereby achieving the quality of services requirements for underwater voice transmissions. The simulation results showed that as the SNR increased, the BERs for the proposed UFMC-based underwater transceiver decreased. As the CEEs increased, the BERs for the proposed UFMC-based underwater transceiver increased. The SNRs using 4-QAM with PCE and CEEs of 5%. And 10% were 14.0671, 14.5223, and 14.9894 dB, respectively, for the proposed system with a BER of \(4\times 10^{-4}\). As the CEEs increased, the SNRs increased, at the same transmission BER of \(4\times 10^{-4}\). The SNRs using 16-QAM with PCE and CEEs of 5% and 10% were 21.0568, 21.5490, and 23.4679 dB, respectively, for the proposed system with a BER of \(8.5324\times 10^{-4}\). The SNRs using 16-QAM were larger than those when using 4-QAM, at the same transmission BER and CEE. The (2000, 1000) LDPC code showed superior error-correcting capability in the proposed UFMC-based underwater transceiver in the BER range \(10^{-2}\) to \(4\times 10^{-4}\). The 4-QAM likewise had a superior capability to overcome channel fading, whereas 16-QAM, a high-order modulation method, could achieve high data transmission rates. Figure 3 shows the transmission power weighting of the UFMC-based underwater transceiver with an LDPC code and a BER of \(4\times 10^{-4}\), for PCE and CEEs of 5% and 10%, respectively. The AWGNs with spectral densities (\(No\)) were 0.0274, 0.0247, 0.0222, 0.00548, 0.0049, and 0.0031, for 4-QAM with a PCE, 4-QAM with a CEE of 5%, 4-QAM with a CEE of 10%, 16-QAM with a PCE, 16-QAM with a CEE of 5%, and 16-QAM with a CEE of 10%, respectively, at a transmission power weighting of 21/30. The PCE outperformed CEEs of 5% and 10%, under 4-QAM, with \(No\) gains of 0.0027 and 0.0052, respectively, at a transmission power weighting of 21/30. Although the CEE increased, No decreased. The 4-QAM outperformed 16-QAM, under CEEs of 10%, with \(No\) gains of 0.0243, at a transmission power weighting of 21/30. The \(No\) of 4-QAM was larger than that of 16-QAM under the assumption of the same transmission power weighting and CEE. Figure 4 shows the power saving ratios of the UFMC-based underwater transceiver with an LDPC code and a BER of \(4\times 10^{-4}\) for PCE and CEEs of 5% and 10%. \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Depth of transmitter beneath the sea surface, meters & 3 \\ Depth of receiver beneath the sea surface, meters & 2 \\ Water depth, meters & 14.5 \\ Water sound speed & 1539 m/s \\ Range of direct path, meters & 100 \\ Carrier frequency & 40 kHz \\ Channel bandwidth & 20 kHz \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Parameters of the adopted underwater channel model [26]. Figure 3: Transmission power weighting of the UFMC-based underwater transceiver with an LDPC code and a BER of \(4\times 10^{-4}\) for PCE and CEEs of \(5\%\) and \(10\%\).