# ROAD Statistics-Based Noise Detection for DME Mitigation in LDACS
## 5 Results and Discussions
This can be due to the increase in missed detection that occurs for high threshold value. Figure 12: DME interference (**Top**), threshold amplitude-based sensing (**Middle**) and threshold ROAD value-based sensing (**Bottom**) for an SNR of 0 dB. Figure 13: DME interference (**Top**), threshold amplitude-based sensing (**Middle**) and threshold ROAD value-based sensing (**Bottom**) for an SNR of 15 dB. For better clarity of the results, the variation in probability of false detection and missed detection has been plotted for a constant SNR value. The rate of decrease in false detection with the increase in threshold value is clearly visible in Figure 8.0 The variation in accuracy and missed detection are separately plotted to verify the optimum threshold value of detection and the reason behind it. From Figure 21, it is evident that optimum threshold value of detection is occurring for a value of 8. The reduction in detection after threshold value 8 is due to the increase in missed detection as in Figure 8.1  
Once the significance of ROAD value-based sensing and its optimum threshold ROAD value are identified (based on experimental results), the method is incorporated with an existing pulse blanking method to propose a new DME mitigation scheme. Figure 8.2 Probability of detection vs. SNR. Figure 8.3 Probability of false detection vs. SNR. The block diagram of the proposed LDACS receiver is shown in Figure 8.4 Initially, the cyclic prefix bits are removed from the received data. The resulting data are then converted into frequency domain using fast Fourier transform. Further, the frame decomposer separates the pilot symbols and complex data from the corresponding subcarriers. The segregated complex data values further undergo QPSK demodulation and symbol demapping to obtain the bitstreams. The bitstreams are de-interleaved and decoded using de-interleaver and vitterbi decoder, respectively. From the output of the vitterbi decoder, redundant bits are removed and decoded using the RS decoder to obtain the original data. Figure 23 shows the variation in BER with different transmit SNR values. It has been observed that the proposed ROAD PB exhibits a much improved performance for a threshold value of 8. Figure 24 shows the variation in performance of ROAD PB for different threshold values ranging from 7 to 11. The performance of ROAD PB initially improved with a rise in threshold values and then started diminishing. The reason for this nature  
Figure 8.5 Probability of missed detection vs. SNR. Figure 8.6 Probability of false detection in ROAD statistics-based detection for different threshold value vs. SNR. is very obvious; ROAD detectors with low threshold values perceive the small variations from the neighboring carrier as DME interference. The actual data can cause a variation in ROAD values which can lead to false detection of DME interference. Moreover, once DME interference is detected in a subcarrier with a low threshold value, blanking the subcarrier causes the loss of more data. As OFDM systems have a self-removal noise mechanism due to the principle of orthogonality, the focus of detection is for large variation. Hence, there is an optimum high threshold value for which leaving the data is better than maintaining or estimating. From the results shown in Figure 24, the optimum threshold value is noted as 8. The accuracy of interference detection starts diminishing for a threshold value greater than an optimum threshold value. In this situation, the ROAD interference detector will only sense a very large variation from the neighboring carrier as DME interference leading to missed detection. With the introduction of pulse blanking, a possibility of change in optimum threshold exists, if one considers the trade-off between interference power and signal distortion. Excess interference power may exist in mitigated data if the threshold value is high. On the other hand, reducing the threshold value can cause more distortion and loss of data due to blanking.