## 3 FTN Signal Processing Based on the UEP Algorithm
### Simulation Results  
The performance of the proposed FTN-based UEP method and that of the conventional FTN method were compared through simulation. The simulation was performed using the Visual C++ language on a PC. The LDPC encoder employed K = 32,400 as the size of the source bit, N = 64,800 as the size of coded bits, and R = 1/2 as the rate of encoding. The square root raised cosine (SRRC) filter, with a roll-off factor of 0.35 as defined by the DVB-S2 standard, was used. The performance was compared by setting the FTN interference rate to 20%, 30%, and 40.0%. The UEP setting was configured based on the number of interference ratios, \(N_{p}=\boldsymbol{4}\). Fixed on the LDPC coding parameters, shown in Table 1, in order to achieve the performance improvement effect of the UEP algorithm, the different interference ratios for the UEP setting were configured, and the average interference ratios were set to 20%, 30%, or 40%. The UEP-based FTN transmission method was applied. To compare the conventional FTN algorithm, with the same interference ratio applied to all groups, we performed a BER performance analysis according to the different interference ratios allotted for the priority group, as shown in Table 2. \begin{table}
\begin{tabular}{c c} \hline \hline
**Total number of data** & \(10^{6}\) \\ \hline
**Channel coding** & LDPC (HSS algorithm) \\ \hline
**Input bit (K)** & 32,400 \\ \hline
**Code word (N)** & 64,800 \\ \hline
**Coding rate** & 1/2 \\ \hline
**Modulation** & BPSK \\ \hline
**Number of sampling bits (SRRC filter)** & 32 \\ \hline
**Roll off factor** & 0.35 \\ \hline
**Interference rate (\(\boldsymbol{\tau^{\prime}}\))** & 20\%, 30\%, 40\% \\ \hline
**LDPC inner iteration (\(l\))** & 60 \\ \hline \(N_{p}\) & 4 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Simulation parameters. \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{4}{c}{**Interference Rate for Each Priority Group (\%)**} \\ \cline{2-5}  & \(\boldsymbol{\tau^{{}^{\prime}}_{1}}\) & \(\boldsymbol{\tau^{{}^{\prime}}_{2}}\) & \(\boldsymbol{\tau^{{}^{\prime}}_{3}}\) & \(\boldsymbol{\tau^{{}^{\prime}}_{4}}\) \\ \hline
**Type1** & 22 & 21 & 19 & 18 \\ \hline
**Type2** & 18 & 19 & 21 & 22 \\ \hline
**Type3** & 30 & 25 & 15 & 10 \\ \hline
**Type4** & 10 & 15 & 25 & 30 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: UEP parameter settings for the average of the interference ratio, \(\tau^{\prime}=20\%\). In Figures 9 and 10, the red BER curves represent the performance, with the interference ratio set at 30% and 40% in the FTN, without UEP. Compared to FTN without UEP at the BER of \(10^{-4}\), it was demonstrated, in the simulation, that the performance improved by 0.1 dB at BER = \(10^{-4}\) in type 2, where the range of the FTN interference ratio between groups was set to low in the UEP-FTN algorithm. In addition, it was shown that the performance improved by 0.2 dB and 0.3 dB in the case of an average interference ratio of 30% and 40%, respectively, in type 4, where the range of the FTN interference ratios between groups was set to high. The simulation demonstrated that the most excellent performance was obtained in type 4, where the range of the interference ratios for each group was set to high through each priority algorithm, and the low interference ratio was applied to the high-priority group. These results can be interpreted as follows. First, the reason why the range of the interference ratios was set to high was because the difference in the branch metric allocated to each trellis became larger, allowing the BCJR decoder to operate efficiently. Second, applying the low interference ratios was applied to the high-priority signal in order to enhance the reliability of the transmitted signal, the LDPC decoder can update the highly reliable data by the calculation of the bit node and check node updating. Through this process, the performance can eventually be improved.