## 2 Literature Review Methodology
### Development of the Review Protocol
#### 2.2.3 Systematic Approach Used in Extracting and Analyzing Studies
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Ref.** & **Training Loss** & **Complexity** & **Channel Prediction** & **Gain (BER)** \\ \hline
[18] & 0.025 (MAE) & Higher & — & \(0.5\times 10^{-6}\) \\  & & (Big-O, Runtime) & — & \(40\%\) \\ \hline
[22] & 0.00012 (MSE) & Medium \(O(LK^{2})\) & Near optimal & \(40\%\) \\ \hline
[58] & 0.1 (L2) & — & — & \(1\times 10^{-2}\) at an SNR of 20 dB \\ \hline
[23] & Combines MSE and BER & 47.8 ms & — & Improvement of over 0.17 \\ \hline
[24] & MSE & — & — & \(1\times 10^{-3}\) (ComNet) \\ \hline
[28] & Not Given (MSE) & Same (Time complexity) & \(-24\) dB (NMSE) & \(4\times 10^{-4}\) (AMP) \\ \hline
[59] & 0.018 (MSE) &
\begin{tabular}{c} 2.12 MB (Memory), \\ 561,526 (Para.), \\ \(1.04\times 10^{6}\) (FLOPs) \\ \end{tabular} & — & \(1\times 10^{-3}\) (ComNet) \\ \hline
[60] & — & — & \(2\times 10^{-6}\) (MSE) & \(0.5\times 10^{-3}\) (ChannelNet) \\ \hline
[27] & 0.01 (MSE) &
\begin{tabular}{c} 0.2 MB (Memory), \\ (P), Lower by \(0.5\times 10^{5}\) (FLOPs) \\ \end{tabular} & \(0.25\times 10^{-6}\) (MSE) & \(1\times 10^{-3}\) (biLSTM) \\ \hline
[29] & WGAN-GP & — & TVIR, CDF, JS Divergence, Entropy & Close to measurements \\ \hline
[32] & \(4.09\times 10^{-3}\) (MSE) &
\begin{tabular}{c} 8,460,928 (Par.), 23.7 s \\ (T. Time), 83.3 ms \\ (P. Time) \\ \end{tabular} & \(9\times 10^{-4}\) (MSE) & Not Done \\ \hline
[30] & 0.05 (MSE) & Lower (CNN) & TVIR \(\approx 0\) & \(7\times 10^{-4}\) (FC-NN) \\ \hline
[31] & MSE & Not Done & Not Done & \(1\times 10^{-2}\) (ComNet) \\ \hline
[33] & MSE &
\begin{tabular}{c} Lower by 21.3 ms \\ (Runtime) \\ \end{tabular} & \(1\times 10^{-4}\) (NMSE) & \(1.7\times 10^{-2}\) (LMMSE) \\ \hline
[34] & 0.02 (MSE) & \
\begin{tabular}{c} 20.70 MB, 4,996,384 P, \\ \(2.48\times 10^{8}\) F \\ \end{tabular} &
\begin{tabular}{c} 3 dB gain at \(10^{-3}\) \\ \end{tabular} & \(1\times 10^{-7}\) (CNN-ResNet) \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Comparison for ML/DL-based channel techniques in MC-UWA communication. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Ref.** & **Bandwidth** & **Tx-Rx Distance** & **System** & **Subcarr.** & **Modulation** & **CP** \\ \hline
[35] & — & — & OFDM & — & FSK & — \\ \hline
[37] & 6 kHz & 5 km & OFDM & 256 & PSK, QAM & 64 \\ \hline
[38] & — & — & OFDM & — & — & — \\ \hline
[39] & 8 kHz & 5 km & OFDM & 1024 & PSK, QAM & 400 \\ \hline
[40] & 6 kHz & 0.3 km to 1.5 km & OTFS & 32 & PSK & — \\ \hline
[41] & — & 5 to 355 cm & OFDM & — & — & — \\ \hline
[42] & 5 kHz & 0.82 km & OFDM & 200 & — & — \\ \hline \hline \end{tabular}
\end{table} 
Table 14: Comparison of adaptive modulation techniques in SC-UWA communication. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Ref.** & **ML/DL Technique** & **Optimizer** & **Training Examples** \\ \hline
[35] & A-kNN & Not Applicable & Measured Data \\ \hline
[37] & RL & PPO & Simulated (Bellhop) \& Measured Data \\ \hline
[38] & CNN & Adam & Simulated Data \\ \hline
[39] & RL & Adam & Simulated Data (Bellhop) \\ \hline
[40] & CNN & Adam & Measured Data \\ \hline
[41] & RL & Not Applicable & No Dataset Used \\ \hline
[42] & RL & Not Applicable & Measured Data \\ \hline \hline \end{tabular}
\end{table} 
Table 11: Overview of ML/DL-based adaptive modulation in MC-UWA communication. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Ref.** & **Bandwidth** & **Tx-Rx Distance** & **Modulation** \\ \hline
[43] & 5 kHz, 10 kHz & 1 km, 2 km, 3 km & PSK, QAM \\ \hline
[36] & 4 kHz & 1 km & PSK, QAM \\ \hline
[38] & — & — & CDMA, TDMA \\ \hline
[41] & — & 5 to 355 cm & FH-BFSK, ASK, PSK \\ \hline
[42] & 5 kHz & 0.82 km & FSK, DS-SS \\ \hline \hline \end{tabular}
\end{table} 
Table 12: Characteristics of adaptive modulation techniques in SC-UWA communication.