# GAO-FCNN-Enabled Beamforming of the RIS-Assisted Intelligent Communication System
## 4 Numerical Results  
This section studies a hybrid approach of the proposed GAO-FCNN in the downlink intelligent MIMO wireless communication system. There are 80 antennas at the BS, with the uniform linear array utilization. And there are 256 RIS units and 20 user antennas. The training period is set to be 200 epochs. The BS is located at the coordinates (0 m, \(-40\) m), while the range of user terminal positions is between (0 m, 0 m) and (100 m, 0 m). The RIS is positioned at the coordinates (60 m, 10 m). In this study, the performance metric of the RIS-assisted intelligent downlink MIMO communication system is the BER. As illustrated in Figure 3, the curves of BER performance versus values of SNRs are investigated in an intelligent MIMO communication system without an RIS, an RIS-assistedintelligent communication system, an RIS-assisted intelligent communication system with an FCNN, and an RIS-assisted intelligent communication system using the proposed GAO-FCNN algorithm when \(d=20\) m. The green line means the MIMO communication system without an RIS, and it is served as the baseline. The blue line demonstrates the improved BER performance of the MIMO intelligent system established with an RIS. The red line demonstrates an RIS-assisted intelligent MIMO system that utilizes the FCNN. And the pink line depicts the BER performance of the RIS-assisted intelligent communication system using the GAO-FCNN scheme. Specifically, the RIS-assisted intelligent communication system is performed using the GAO-FCNN algorithm. The performance curves show that all BER values of these three intelligent communication systems are decreased when the values of the SNR are increased. However, the BER results of the FCNN basically remain to be unchanged under different values of SNR. Although the RIS-assisted MIMO communication system is supported by the FCNN, it can be observed that the BER performance is still maintained in a poor condition. Notably, the high BER means that the data transmission quality of the system may not be efficient enough, thus the user experience and system reliability are affected. The GAO-FCNN-enabled beamforming performance of the RIS-assisted intelligent communication system is improved significantly in the entire value range of the SNR. When the value of BER is 0.001, the performance gain of the SNR is 3.1 dB compared with the RIS-assisted intelligent communication system. It can be achieved when there are 256 RIS elements established in the system. The whole results show that the signal processing of the RIS-assisted intelligent communication are effectively optimized using the proposed GAO-FCNN algorithm. Traditional methods are surpassed by it through the discovery of optimal network parameters. Additionally, BER spikes that arise from the reliance on neural networks are mitigated by it. When \(d=40\) m, the performance curves in Figure 4 show that all BER values of four intelligent communication systems are decreased with the growth of the values of SNR. The overall BER performance curves are better than those when the distance is equal to 20 m in Figure 3. In addition, the BER result of the FCNN is still higher than that without RIS, specifically when the SNR is larger than 10 dB. It means that the system of the FCNN is not improved at a larger distance, while the BER performance of the remaining three systems can be optimized. Furthermore, it is concluded that the BER performance of the RIS-assisted intelligent communication using the GAO-FCNN algorithm is much better  
Figure 3: BER performance versus different values of SNRs when \(d=20\) m.  
than the remaining three systems when \(d=40\) m. For an example, when the value of BER of the GAO-FCNN scheme is 0.001, the performance gain of the SNR is around 2.8 dB compared with the RIS-assisted intelligent communication system.