# GAO-FCNN-Enabled Beamforming of the RIS-Assisted Intelligent Communication System
## 4 Numerical Results
Figure 4 depicts shows the BER performance curves of four intelligent communication systems when \(d=60\) m. When the value of the BER using the GAO-FCNN scheme is 0.001, the performance gain of the SNR is about 3.7 dB compared with the RIS-assisted intelligent communication system. Based on the above analysis, it can be concluded that the BER performance is affected by the length of the distance in the RIS-assisted wireless communication system. Figure 5 displays the BER performance versus the user movement distance d when SNR is equal to 0 dB under four wireless communication system scenarios. The green line represents the traditional intelligent MIMO system without an RIS, the blue line is the BER curve of an RIS-assisted intelligent MIMO system, the red line depicts the BER performance of an RIS-assisted MIMO intelligent system enhanced with the FCNN, and the pink line illustrates the BER values of an RIS-assisted intelligent communication system with the GAO-FCNN algorithm. In the system without the RIS, it appears that the BER values almost remain unchanged with the increasing distance. And it is worth noting that the BER also remains basically unchanged with an increasing distance in the system utilizing the FCNN. The reason may be due to the limitations or performance bottlenecks of the FCNN in signal transmission, resulting in the inability of error correction. The BER performance could potentially be limited by this situation, and the reliability and stability of data transmission are both influenced. Then the BER performance of the RIS-assisted intelligent communication system with GAO-FCNN is gradually improved with the increasing distance. It can be reached at the lowest value under the condition that the distance is equal to 60 m, and then it is gradually increased. It is also shown that the BER curves of the RIS-assisted intelligent communication system using the proposed GAO-FCNN algorithm is better than these three compared communication systems with different methods. However, in the RIS-assisted MIMO system and the GAO-FCNN-enhanced RIS-assisted MIMO intelligent system, a decreasing trend of the BER value is shown firstly at the distance of 60 m. After then, the BER value is increased with the growth of distance. Within a certain distance, the RIS technology can reflect, focus, or adjust the transmission path of the signal, thus significantly increasing the strength of the reliever signal, reducing the impact of interference and noise, and then leading to a prominent reduction in the BER. Figure 4: BER performance versus different values of SNRs. (**a**) BER performance when \(d=40\) m. (**b**) BER performance when \(d=60\). However, as the distance increases, the signal suffers from the severe fading of free-space propagation. Consequently, the signal strength is gradually decreased, and the performance of the BER is also deteriorated. The BER performance versus the distance when the SNR = 5 dB and 10 dB are illustrated in Figure 6. As expected, the BER curves of the RIS-assisted intelligent communication system using the proposed GAO-FCNN algorithm is better than those three compared communication systems with different methods. As a consequence, the satisfactory BER performance of our proposed technique can be achieved under different values of the SNR even when \(d\) is changed very often. As illustrated in Figure 7, the RIS-assisted intelligent communication system is trained using the GAO-FCNN algorithm when the SNR is 6 dB. In the blue part, the system is maintained at the fixed noise power levels for both the standard deviation and the mean,  
Figure 5: BER performance versus the distance \(d\) when SNR = 0 dB. Figure 6: BER performance versus the distance. (**a**) BER performance when SNR = 5 dB. (**b**) BER performance when SNR = 10 dB. the green part features the adjustable noise power settings of different parameters, and the red part represents dynamic adjustments of the standard deviation and the mean.