## 4 Experimental Results
### Assessing the Corruption Impact of QIV in a Wireless Communication Environment  
#### 4.2.1 Experimental Setup for Air Channel Model  
To evaluate the performance of the autoencoder-based neural codec system in the wireless communication environment between DIFAR sonobuoys and MPA, an air channel model simulating actual wireless communication conditions was developed. The purpose of this experiment was to analyze the impact of the Bit Error Rate (BER) of the Quantized Index Vector on the signal reconstruction performance of the neural codec. For this, the simulation was conducted in a simplified environment, with the air channel model configured based on the wireless communication parameters of the SSQ-573 DIFAR sonobuoy, as summarized in Table 6[28].  
As shown in Figure 8, the simulation was conducted in 2D space, and two experiments were carried out to validate the air channel model.  
\begin{table}
\begin{tabular}{c c} \hline \hline \multicolumn{2}{c}{**Sonobuoy Characteristics**} \\ \hline Telemetry (Digital Mode) & Coherent GMSK at 224 kbps \\ RF Channel & 97 channels (136 MHz\({}_{-}\)173.5 MHz, 376 kHz spacing) \\ VHF Radiated Power & 1 Watt nominal \\ \hline \hline \end{tabular}
\end{table}
Table 6: SSQ-573 DIFAR sonobuoy communication specifications.  
Figure 8: Conceptual diagram of 2-ray propagation communication between DIFAR sonobuoy and MPA (including LOS and NLOS paths).  
Figure 7: Reconstruction Error (Spectrogram MSE) Comparison Based on Transmitted Information Amount: (**a**) Reconstruction error results for CW signals; (**b**) Reconstruction error results for LFM signals.  
In the first experiment, the air channel model's Pathloss was evaluated by configuring the positions of the sonobuoy and the MPA as follows. The sonobuoy's X-axis position was fixed at 0 m, while its Y-axis position followed a Gaussian distribution within the range of 1 m to 0.5 m. The MPA's X-axis position varied from 0 m to 10,000 m, while its Y-axis position followed a Gaussian distribution between 1950 m and 2050 m, introducing approximately 50 m of movement. Using these configurations, the Pathloss of the transmitted signal was measured, and a graph was generated with the X-axis representing the MPA's X-axis position (distance) and the Y-axis representing the Pathloss values, validating the reliability of the air channel model.  
In the second experiment, the system's BER performance was evaluated under various SNR conditions. For this purpose, the sonobuoy's X-axis and Y-axis positions were fixed at 0 m and 1 m, respectively, while the MPA's X-axis and Y-axis positions were fixed at 10,000 m and 2000 m, respectively. In this fixed configuration, 150 different data samples were transmitted under varying SNR conditions, and the overall system performance was analyzed based on the resulting BER.  
These two experiments were conducted to evaluate the reliability of the air channel model, which simulates a wireless communication environment, and to investigate the impact of BER degradation in wireless communication on the performance of autoencoder based acoustic signal compression and reconstruction model.  
The wireless communication simulation process was as follows: the QIV was first converted into a 10-bit bitstream. The MATLAB Communications Toolbox was used to perform GMSK modulation and demodulation [29]. The GMSK modulation was configured with a bit rate of 224 kbps, a Bandwidth-Time Product of 0.5, and 16 samples per symbol to ensure signal integrity. At the receiver end, the GMSK demodulator was used with a Traceback Depth of 50 to accurately recover the signal.  
The modulated signal was transmitted with a transmission power of 1 W. To simulate realistic wireless channel conditions, the signal was passed through an Additive White Gaussian Noise (AWGN) channel, introducing noise to the received signal. The demodulated bitstream was then compared with the original transmitted bitstream to evaluate the BER.