# Jamming Detection and Suppression Technique for OTFS Systems in an AWGN Channel
## 4 Simulation Results
### Jamming Detection Performance  
In this work, jamming detection performance is evaluated using the detection probability \(P_{d}\) and false alarm probability \(P_{fa}\). Here, \(P_{d}\) is defined as the ratio of the number of successfully detected jamming frequency points to the total number of actual jamming frequency points. \(P_{fa}\) represents the ratio of falsely identified interfered frequency points to the total number of frequency points that are not interfered. In simulations, the SNR is set to 8 dB, and the segment number \(Z\) is set to 16 for the improved FCME algorithm. Finally, the detection performance of the proposed algorithm is compared with that of the CME algorithm and the FCME algorithm. Figure 7 shows the jamming detection probability when there is single-tone jamming. It can be observed from the figure that the detection probability consistently increases with the target false alarm probability. This is because a higher target false alarm probability lowers the detection threshold, enabling the detection of smaller jamming signals and thereby improving the detection probability. However, this also causes non-jamming signals to be more likely to exceed the lower threshold and be mistakenly identified as interference, resulting in an increase in the actual false alarm probability. The detection probability of the proposed algorithm is largely comparable to that of FCME while outperforming CME. \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **LUTs** & **FFs** & **BRAMs** \\ \hline Traditional FCME method & 2880 & 2428 & 14.5 \\ \hline Proposed method & 2135 & 1941 & 0.5 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: FPGA implementation results of different FCME methods. Figure 8 illustrates the false alarm probability under single-tone jamming. The simulation results indicate that the actual false alarm probability is closely aligned with the theoretical results, although the error between them increases as the target false alarm probability rises. The reason is that a high target false alarm probability typically results from a lower decision threshold. However, when a lower threshold factor is applied, the jamming-free signal becomes more susceptible to noise. The smaller the threshold factor, the greater the impact of noise, leading to an increase in the actual false alarm probability. Overall, the performance differences between the three algorithms under single-tone interference are negligible. Figure 9 shows the jamming detection probability under partial-band jamming, with a target false alarm probability \(P_{fa}=0.05\), and varying jamming factors \(\xi\). In simulations,  
Figure 8: The false alarm probability of single-tone jamming in an OTFS system. Figure 7: The detection probability of single-tone jamming in an OTFS system. scenarios of partial-band jamming with \(\xi=0.1,0.4,0.7\) are considered. The detection probabilities of three different algorithms, including the proposed method and the conventional CME and FCME algorithms, are compared. For a small jamming factor (e.g., \(\xi=0.1,0.4,0.7\)), the detection performance of the three algorithms is nearly identical. However, as the jamming factor increases, the performance advantages of the FCME and the proposed algorithm become more apparent. As the jamming factor \(\xi\) increases, the detection probability performance decreases. The primary reason is that under the same JSR conditions, a larger jamming factor corresponds to a wider jamming bandwidth, resulting in a lower jamming power spectral density. Consequently, the jamming signal becomes more difficult to detect relative to the signal power. In summary, the proposed FCME algorithm demonstrates a performance comparable to that of the conventional FCME algorithm. However, it offers lower computational complexity because the sorting process is significantly reduced during the initialization stage. Figure 10 illustrates the actual jamming false alarm probability under partial-band jamming when the target false alarm probability is set to \(P_{fa}=0.05\).