# Fast and Reliable Burst Data Transmission for Backscatter Communications
## 6 Performance Evaluation
### Evaluation  
To model the changing energy-harvesting and channel conditions, we evaluate the performance with different values of \(E_{b}/N_{0}\) and different combinations of \(U_{\max}\) and \(\tau\). \(E_{b}/N_{0}\) is the signal-to-noise ratio (SNR) per bit. All the corresponding parameters are listed in Table 1.  
We consider that the CRFID has 7400-bit data in buffer that need to be sent to the reader. Our proposed scheme is simulated to obtain the goodput performance and the corresponding frame length and number of redundant frames, which are compared with the theoretical optimal solution obtained from Reference [36]. The theoretical optimal value is used as a benchmark under specific energy-harvesting and channel conditions. We also evaluate the performance of our proposed scheme by the actual implementation and compared it to the fixed 96-bit frame length strategy adopted by EPC C1G2 and the DFCA scheme. In order to be fair, all solutions use the optimized communication procedure as shown in Figure 4. \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameters** & **Values** \\ \hline payload length \(l_{p}\) (bit) & 16–96 \\ PC and CRC length \(l_{h}\) (bit) & 32 \\ RC constant \(\tau\) & \(2,3\) \\ maximum voltage \(U_{\max}\) (V) & 6, 5 \\ weight coefficient \(\alpha\) & 0.35 \\ minimum redundant frames \(M_{\min}\) & \(1\) \\ maximum redundant frames \(M_{\max}\) & 20 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Corresponding parameters setting. Figure 8: Energy consumption comparison between Cauchy- and Vandermonde-matrix–based Reed–Solomon (RS) code. Figure 9a shows the variation of the goodput of the four schemes as \(E_{b}/N_{0}\) increases under the harvesting conditions of \(U_{\max}=6\) V and \(\tau=2\). We clearly see that, in Figure 9a, as \(E_{b}/N_{0}\) increases, system goodput gradually increases due to the decreasing the bit error rate (BER). However, as \(E_{b}/N_{0}\) gets larger, the improvement of goodput is reduced and eventually converges to a fixed value. This is because the frame successful transmission rate eventually tends to 1 with the decreasing BER. The theoretical goodput in Figure 9a is larger than our scheme, the DFCA scheme, and the fixed frame length scheme, but the theoretical goodput depends on accurate estimation about channel-quality and harvesting condition, which is difficult to achieve in practice. The goodput achieved by our solution is very close to optimal. Figure 9b,c shows the optimal frame length and the number of redundant frames used by the theoretical method and our proposed scheme, respectively, under \(E_{b}/N_{0}\) corresponding to Figure 9a. It can be seen that, when \(E_{b}/N_{0}\) is small, which means poor channel quality, the frame length used is small and the number of redundant frames is large. As \(E_{b}/N_{0}\) increases, the frame length is larger and redundant frames are fewer. Our scheme is close to the theoretical value, but because our scheme uses the online measurement goodput feedback to the node to change the corresponding frame length and the number of redundant frames, the curve has certain fluctuations. Figure 10 shows the goodput, frame length, and number of redundant frames for several scenarios under energy-harvesting conditions of \(U_{\max}=5\) V and \(\tau=3\). Compared with Figure 9, the maximum chargeable voltage of the CRFID node is reduced to 5 V and the RC circuit time constant \(\tau\) is set to 3, which reduces the energy-harvesting conditions. Overall, trend of goodput variation in Figure 10a is the same as in Figure 9a, but the overall goodput is smaller than Figure 9a due to poor energy-harvesting conditions. As can be seen from Figure 10a,b, increasing the frame length does not increase the goodput indefinitely.