Integrating AI and IoT for Smart Antenna Systems in 5G Networks

The evolution of 5G systems depends on complex antennas able to give high performance with low latency and energy consumption. This paper investigates the convergence of Internet of Thing (IoT) and Artificial Intelligence (AI) in smart antenna networks in terms of network performance improvement and resource optimization. Through comparative analysis, we quantify the performance of SNR, beamforming accuracy, latency, network throughput, energy efficiency, etc., for the traditional systems and AI-IoT integrated systems. Results show that the AI-IoT integrated system SNR (38dB) is much higher than ($\mathbf{a t} \mathbf{2 5 d B}$) for conventional systems, which obviously is a better reception in terms of signal to noise and interference ratio. Beamforming effectiveness was improved from 78 % to 92 %, demonstrating the capability of AI to optimise antenna patterns in real-time for improving signal dissemination. Latency was 42 % less than 12 ms to 7 ms, illustrating the effectiveness of real-time data analysis of human AI system. Furthermore, the network throughput was 47 % higher as well: the BCNet base network rendered 850 Mbps on average, while the parallel BCNet production network achieved $\mathbf{1 2 5 0}$ Mbps, covering to its better handling and resource consumption. The AI-IoT integrated network is also shown with 33% reduction of energy consumption, showing green in 5 G network. These results highlight the disruptive power of AI and IoT technologies for smart antenna systems in 5 G networks and serve as a stepping stone for the progress of wireless communication. The combination of these technologies provides remarkable gains in performance and efficient power use, enabling more responsive, reliable, and energy-efficient network solutions.