## 4 Results and Discussion
### Performance Analysis of Image Communication System
#### 4.2.2 Evaluation of Communication Systems over AWGN Channel  
Figure 5a illustrates the BER in logarithmic scale versus \(\mathrm{E_{b}}/\mathrm{N_{0}}\) for the proposed OFDM-based image communication system over AWGN channel, using higher order M-QAM and different channel estimation techniques. The graph indicates that lower order M-QAM experiences a sharp drop in BER with higher \(\mathrm{E_{b}}/\mathrm{N_{0}}\), characterized by the waterfall trend, whereas the drop in the higher order M-QAM is insignificant across all \(\mathrm{E_{b}}/\mathrm{N_{0}}\) values due to the increased number of error bits. At \(\mathrm{E_{b}}/\mathrm{N_{0}}\) 20 dB, 16-QAM and \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameters** & **Values** \\ \hline Source Coding & Variable Length Coding \\ Modulation Technique & M-QAM \\ Modulation Order & M \(\in\) {16, 32, 64, 128, 256, 512, 1024} \\ Length of Symbol (k) & \(log_{2}(M)\) \\ Subcarriers (S) & \(n\times 2^{n}\) \\ Cyclic Prefix (CP) & \(s/4\) \\ Pilots (P) & \(CP/4\) \\ Pilot Insertion & Comb-type \\ Channel Model & AWGN \\ \multirow{2}{*}{Channel Estimation} & \multirow{2}{*}{Rayleigh Fading with AWGN} \\  & LS \\ \multirow{2}{*}{Channel Equalization} & MMSE \\ Channel Equalization & Zero-Forcing \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Simulation parameters of the image communication system. 1024-QAM have reached their lowest mean BER of 2.25 \(\times\) 10\({}^{-5}\) and 0.05 using MMSE channel estimation, respectively. For channel estimation analysis, MMSE outperforms LS channel estimation across all M-QAM, and for 16-QAM at E\({}_{\text{b}}\)/N\({}_{0}\) 20 dB, the use of MMSE resulted in the highest improvement (approximately 40 times lower BER) compared to LS channel estimation. Overall, the 16-QAM system using MMSE channel estimation has the lowest average BER and 1024-QAM system using LS estimation has the highest average BER. The image\(-\) quality measure in terms of PSNR of the recovered images for the proposed systems is shown in Figure 5b. The PSNR values follow a similar pattern to the BER and improve with higher E\({}_{\text{b}}\)/N\({}_{0}\); however, when using higher order M-QAM, the PSNR values decrease indicating the decline in image quality across all E\({}_{\text{b}}\)/N\({}_{0}\). Additionally in high E\({}_{\text{b}}\)/N\({}_{0}\) regions, the quality of the image improves significantly for lower order M-QAM with a steep upward incline compared to higher order M-QAM, which has a more flattened incline. At E\({}_{\text{b}}\)/N\({}_{0}\) 20 dB, 16-QAM and 1024-QAM have obtained their highest quality images with mean PSNR value of 66 dB and 26 dB using MMSE channel estimation, respectively. With respect to channel estimation, MMSE outperformed LS across all M-QAM, and 16-QAM at E\({}_{\text{b}}\)/N\({}_{0}\) 20 dB achieved highest improvement of 26 dB when utilizing MMSE channel estimation; however with the higher order M-QAM, the improvement due to different channel estimation is less significant. MS-SSIM evaluation metrics (in logarithmic scale) have almost identical trends with PSNR, as illustrated in Figure 5c. For higher E\({}_{\text{b}}\)/N\({}_{0}\) the MS-SSIM improves significantly for lower order M-QAM, however, the improvement is slow for the higher order M-QAM. Lower order M-QAM has a higher MS-SSIM score and demonstrates significant improvement with increased E\({}_{\text{b}}\)/N\({}_{0}\), while higher order M-QAM does not exhibit a significant improvement in the image quality across E\({}_{\text{b}}\)/N\({}_{0}\). At E\({}_{\text{b}}\)/N\({}_{0}\) 20 dB, 16-QAM and 1024-QAM have obtained their highest quality images with mean MS-SSIM values 43 dB and 10 dB using MMSE channel estimation, respectively. In terms of channel estimation, MMSE performs better than LS for all M-QAM (16-QAM at E\({}_{\text{b}}\)/N\({}_{0}\) 20 dB achieved and improvement of 20 dB using MMSE); however, for higher order M-QAM, the difference in performance between the two techniques is not substantial.