# Resource Optimization for 3D Video SoftCast with Joint Texture/Depth Power Allocation
## 5 Simulation Results
### The Resource Control Scheme Performance Comparison  
The performance of the proposed scheme was tested regarding the synthesized virtual views quality and compared with two benchmark schemes: SoftCast and the distortion-resource algorithm [31]. Figure 8: Power and bandwidth usage trade-off curves for different video sequences: (**a**) Kendo; (**b**) PoznanStreet. Figure 9 illustrates the synthesis quality at virtual viewpoint 2 of the 3D video for the three schemes, along with the synthesized frames. Under a channel bandwidth constraint of 8192, the SoftCast scheme exploits all the available bandwidth resources and allocates power to each chunk. In contrast, the other schemes tend to retain HP chunks and discard LP chunks, which significantly saves bandwidth usage. For instance, when the power usage was 10 dB, the PSNR and SSIM of the proposed resource control scheme were close to the values obtained by SoftCast with only 7.28% bandwidth usage, which is nearly half of the bandwidth saved by the distortion-resource algorithm. As the power usage decreased to SNR = 0 dB, the proposed scheme achieved even better performance. With only 1.1535% bandwidth usage, the proposed scheme PSNR saved 1.21 dB over SoftCast, and in terms of SSIM, the proposed scheme improved the SSIM from 0.8244 to 0.9317. The robustness of the proposed scheme was evaluated by a comparison of the results of the received video quality with those of the conventional SoftCast and the distortion  
Figure 9: Synthesis quality at virtual view point 2 for different algorithms: (**a**) SNR = 20 dB; (**b**) SNR = 10 dB; (**c**) SNR = 0 dB. resource algorithm. The performance achieved by each method in Table 4 corresponds to the bandwidth usage illustrated in Table 3. SoftCast harnesses all the bandwidth and assigns the available power to all chunks. The distortion-resource algorithm utilizes the available power by assigning the power resource to an optimal number of chunks, to minimize the receiving viewpoints' distortion. In contrast, the proposed scheme optimally allocates the available power to a limited number of chunks such that the overall quality of the transmitted 3D video is maximized. For instance, for the low power usage of 0 dB, the proposed method could obtain a PSNR gain of 1.5 dB over SoftCast and even a 1.789 dB gain over the distortion-resource algorithm (gtFly sequence), using less than 1.4% of the bandwidth, and a maximum SSIM increment of 0.1588 was achieved over SoftCast (Shark sequence) using 2% of the bandwidth. \begin{table}  
\end{table} 
Table 4: Preformance comparison for different 3D video sequences. Figure 10 shows the constrained resource influence on pseudo-analog transmission. Assuming different bandwidth resources along with different power budgets reveals the pseudo-analog transmission behavior. The impact of discarding LP chunks and retaining HP chunks at lower SNR is different from that at higher SNR. For each given power budget, several bandwidth constraints are suggested. Under each bandwidth resource, SoftCast consumes the available bandwidth resource for the transmission process. Although the available bandwidth resource also bounds the proposed resource control scheme, it achieves \(PSNR_{max}\). To save more bandwidth, the proposed scheme was set to achieve \(\tau\cdot PSNR_{max}\). The dashed line represents the resulting video quality for SoftCast transmission utilizing the whole bandwidth. In Figure 10a the same result is shown as in Figure 9 but for only one virtual viewpoint.