# Natural Brain-Inspired Intelligence for Non-Gaussian and Nonlinear Environments with Finite Memory
## 5 CDS Implementation Case Study: OFDM Long-Haul Fiber Optic Communications
### Simulation Results and Discussions
#### 5.2.2 Results for the System with the CDS Focus Level One  
The global PAC procedure can be summarized using the results shown in Figures 8-14 as follows:  
1. First PAC (focus level zero): CDS reduces the date rate to find the first data rate for which the BER is under the FEC-threshold (see Figure 9 and Section 4.2.1). Therefore, 208 Gb/s is applied to the fiber optic link as the first action (\(c_{1}\)). Because the BER is under the FEC threshold, the perceptor can extract the statistical model for 208 Gb/s. The perceptor can improve the BER using the extracted model (see Figure 9, \(c_{1}\):208 Gb/s). Note that the minimum BER for a conventional system at 208 Gb/s is \(8.0\times 10^{-3}\)(see Figure 9) whereas this is reduced to \(5.5\times 10^{-4}\) when the CDS is used (see Figure 10, \(c_{1}\):208 Gb/s). The perceptor sends the extracted model to the executive using the internal feedback link. 2. Second PAC (focus level zero): The executive predicts the virtual internal rewards and BER for virtual action of \(c_{2}\) (see Figures 8 and 11 as well as Algorithm 1). Then, the executive applies 236 Gb/s as the \(c_{2}\), because the virtual BER for 240 Gb/s at \(t=8\) is more than the FEC-threshold of \(10^{-2}\) (see Figure 11b, \(c_{2}\): prediction). Also, 236 Gb/s has the minimum virtual internal rewards (See Figure 11a, \(c_{2}\): prediction) and at this data rate, the BER is under FEC threshold (See Figure 11b, \(c_{2}\): prediction). After applying \(c_{2}\) by the CDS (i.e., transmitter sends the data at 236 Gb/s), the perceptor uses the 208 Gb/s model (see Figure 8 and Algorithm 1, previous model selection) to predict the BER for 236 Gb/s. However, the BER is more than FEC-threshold (see Figure 10, \(c_{2}\): 236 Gb/s prediction, topmost curve). Note that we used the previous model selection in this case study. By using previous model selection, the system does not need to transmit the training frames for model extraction. Figure 9: Bit error rate (BER) for a conventional system with a linear equalizer. 3. Third PAC (focus level zero): The BER is more than the FEC-threshold for \(c_{2}\). Therefore, the executive reduces the data rate by \(d\) = 4 Gb/s (see Figure 11). As a result, executive applies 232 Gb/s as \(c_{3}\) in third PAC number. Then, the perceptor uses 208 Gb/s model for BER estimation of 232 Gb/s (See Figure 10, \(c_{3}\): 232 Gb/s prediction) and it can bring the BER for 232 Gb/s under the FEC-threshold. Therefore, the perceptor can extract the model for 232 Gb/s. The extracted model results in further BER improvement for 232 Gb/s (see Figure 10, \(c_{3}\): 232 Gb/s). 4. Fourth PAC (focus level zero): The executive applies the 236 Gb/s (See Figure 11, \(c_{4}\): prediction) as \(c_{4}\) to the environment (i.e., fiber optic link) because the predicted BER for 240 Gb/s is more than the FEC-threshold (see Figure 11b, \(c_{4}\): prediction) and virtual internal reward increases for 240 Gb/s (see Figure 11a, \(c_{4}\): prediction). Figure 10 (\(c_{4}\): 236 Gb/s prediction) shows that the perceptor provides the BER for 236 Gb/s under FEC-threshold using the model for 232 Gb/s (provided that the model for 208 Gb/s was used and BER was higher than FEC threshold in second PAC). Like the third PAC, the BER can improve further using the exact extracted model (see Figure 10, \(c_{4}\): 236 Gb/s). Figure 10: BER in perceptor after environmental actions (\(PF\) = 2, \(d\) = 4 Gb/s, focus level zero). Figure 11: BER using CDS in executive prediction for virtual actions (\(PF\) = 2, \(d\) = 4 Gb/s, focus level zero); (**a**) learning curve for virtual internal reward and (**b**) virtual BER versus executive internal cycle). 5. Fifth PAC (focus level zero and focus level one): The executive finds that the predicted BER for 240 Gb/s is just less than the FEC threshold (see Figure 11b, \(c_{5}\): prediction), but the virtual internal reward increases in comparison to 236 Gb/s (see Figure 11a, \(c_{5}\): prediction).