## 8 5G IoT Architecture and Infrastructure
### 5G Infrastructure  
Fifth-generation (5G) technology holds the potential to revolutionize EEG biometric authentication in health and IoT services. This network offers a reliable and secure channel for transmitting EEG data, crucial for authentication and related services. Furthermore, 5G enables efficient computation of EEG biometric data through its distributed computing capabilities. Additionally, the advanced signal processing capabilities of 5G, including artificial intelligence, can significantly enhance the accuracy of biometric authentication. The consistent and reliable data transmission capabilities of the 5G network are also particularly beneficial for real-time health monitoring and diagnostic applications using wearable and implantable sensors. With its extensive frequency range reaching up to 100 GHz, 5G networks are equipped to achieve substantially faster speeds and more efficient data transmission compared to the existing LTE networks [126]. Fifth-generation (5G) technology is engineered to accommodate a greater number of users simultaneously, optimizing the use of limited spectrum resources. It aims to achieve peak speeds of up to 20 Gbps in millimeter wave networks and up to 1 Gbps in lower-band frequencies. A primary goal of 5G is to consistently provide sufficient spectra to support high-bandwidth applications, while also maintaining broad coverage. Moreover, 5G technology offers faster response times and reduced latency compared to current technologies [37]. Wireless 5G networks comprise the new-generation radio access network (NG-RAN) and the 5G core network (5 GC), as illustrated in Figure 10.  
The NG-RAN architecture for 5G encompasses both ng-eNBs (next-generation evolved Node B) and gNBs (gigabit network base stations) [127]. This architecture integrates the existing LTE radio access network (eNodeB) with new 5G next-generation radio access network nodes, including gNBs, to support both 4G and 5G services. This integration results in improvements in speed, latency, and coverage. The  
Figure 9: Architecture of 5G IoT. cial role in facilitating the transfer of control and user plane traffic between these nodes and is commonly used for inter-eNB connections, forming a key component of the 5G RAN architecture. With advancements in 5G technology, EEG and biometric data can now be collected, processed, and analyzed remotely, enabling non-intrusive and portable authentication in various EEG deployment scenarios [128]. The rise of EEG-enabled IoT deployments offers new opportunities for organizations and individuals to monitor and respond to brain activities in real time. Smart wearables and EEG sensors are increasingly used for biofeedback and performance metrics, enabling the measurement of attention and autonomic nervous system (ANS) responses, crucial in the diagnosis and management of conditions such as autism and epilepsy [129]. EEG-enabled IoT deployments have a vast array of potential applications. When combined with AI, these devices can provide predictive analytics applicable in multiple industries, including mental health and augmentative robotics. An EEG-enabled IoT platform can offer invaluable insights into user behavior and needs, leading to informed decision-making and improved strategies for growth and efficiency. Real-time collection and analysis of EEG data in biomedical applications can be significantly enhanced by such platforms. The incorporation of nanomaterials in electrodes and EEG sensors allows for the capture of a wider range of neurological signals, providing more detailed information than traditional electrodes. This use of nanomaterials also facilitates the miniaturization of EEG systems, making them smaller, more portable, and suitable for non-invasive EEG scans outside conventional settings, thus increasing accessibility for general healthcare. This miniaturization empowers individuals to conduct EEG tests at home, reducing reliance on costly hospital equipment [24; 70].