Training course on 5G and IoT Network Integration

Module 1: Foundations of 5G and IoT Technologies
Overview:
Introduces participants to the evolution, architecture, and core technologies driving 5G and IoT ecosystems.
Key Topics:
Evolution from 1G to 5G and the role of 5G in digital transformation
IoT fundamentals: devices, sensors, connectivity models, and communication protocols
Overview of 5G architecture: NR, gNB, UPF, and control plane functions
Comparison between 4G LTE and 5G NR for IoT applications
5G spectrum, frequency bands, and deployment strategies (NSA & SA)
Practical Focus:
Hands-on analysis of 5G and IoT architecture diagrams and case scenarios.

Module 2: 5G Network Architecture and Core Technologies
Overview:
Explores the technical foundation of 5G networks, focusing on performance enablers for IoT integration.
Key Topics:
5G core (5GC) components and functions
Network Function Virtualization (NFV) and Software-Defined Networking (SDN)
Massive MIMO, beamforming, and millimeter-wave communication
5G RAN (Radio Access Network) design principles
Quality of Service (QoS) and latency management
Practical Focus:
Simulate a 5G network topology integrating SDN/NFV concepts.

Module 3: IoT Ecosystem, Devices, and Communication Protocols
Overview:
Provides a detailed view of IoT architecture layers and protocols supporting connectivity and interoperability.
Key Topics:
IoT architecture: perception, network, and application layers
Communication standards: MQTT, CoAP, AMQP, Zigbee, NB-IoT, and LoRaWAN
IoT device lifecycle and firmware management
IoT platforms and cloud integration (AWS IoT, Azure IoT Hub, Google Cloud IoT)
Sensor data acquisition and transmission in low-power environments
Practical Focus:
Configuring IoT sensor devices and establishing communication via MQTT or CoAP protocol.

Module 4: Integration of IoT Systems with 5G Networks
Overview:
Focuses on the intersection of 5G and IoT technologies, highlighting deployment and interoperability strategies.
Key Topics:
5G-enabled IoT use cases: smart cities, healthcare, manufacturing, transportation
Network slicing for IoT verticals
5G private networks for industrial IoT (IIoT)
Interoperability and scalability challenges
End-to-end architecture for 5G-IoT deployment
Practical Focus:
Develop an integration framework for IoT devices communicating over a simulated 5G network.

Module 5: Edge and Cloud Computing in 5G-IoT Integration
Overview:
Examines how edge computing complements 5G-IoT systems by reducing latency and enhancing data analytics.
Key Topics:
Edge computing architecture and edge-to-cloud continuum
Mobile Edge Computing (MEC) and its role in IoT data processing
AI and machine learning at the edge
Data orchestration between edge and cloud environments
Case studies: autonomous vehicles, smart factories, remote healthcare
Practical Focus:
Design a sample edge computing model for real-time IoT analytics using a simulated dataset.

Module 6: Network Slicing and Virtualization for IoT Services
Overview:
Explores network slicing and virtualization techniques essential for optimizing IoT performance in 5G.
Key Topics:
Concept of network slicing: definition, benefits, and use cases
Virtual network functions (VNFs) and orchestration (NFVO, MANO)
Resource allocation and traffic prioritization for IoT
Multi-access edge computing (MEC) integration with network slices
Dynamic service-level agreements (SLAs) and QoS guarantees
Practical Focus:
Participants simulate creating distinct network slices for critical IoT applications (e.g., healthcare vs logistics).

Module 7: AI and Automation in 5G-IoT Networks
Overview:
Covers the role of artificial intelligence and automation in managing, optimizing, and securing 5G-IoT systems.
Key Topics:
AI-driven network management and self-healing networks
Predictive maintenance using IoT data analytics
Machine learning for traffic optimization and resource allocation
Cognitive radio and spectrum management using AI
Automated fault detection and service assurance
Practical Focus:
Develop a machine learning model to optimize IoT network resource allocation under simulated conditions.

Module 8: Cybersecurity and Data Privacy in 5G-IoT Environments
Overview:
Addresses the unique security and privacy challenges associated with integrating IoT into 5G networks.
Key Topics:
Threat landscape for 5G-IoT systems
Security architecture and trust models for IoT networks
Encryption, authentication, and identity management
Privacy-preserving data analytics and GDPR compliance
Zero Trust principles for IoT device access
Practical Focus:
Perform a threat modeling exercise for a 5G-IoT use case and propose mitigation strategies.

Module 9: Standards, Policies, and Industry Frameworks
Overview:
Explores global standards and regulatory frameworks guiding 5G and IoT integration and deployment.
Key Topics:
3GPP, ITU, ETSI, IEEE, and GSMA standards
Spectrum policy and frequency allocation for 5G
IoT data governance and compliance frameworks
Policy considerations for smart infrastructure
Role of governments and private sector in 5G-IoT rollout
Practical Focus:
Participants evaluate national or regional regulatory frameworks for 5G and IoT deployment.

Module 10: Future Trends and Capstone Project
Overview:
Examines the future landscape of 5G-IoT technologies and provides participants an opportunity to apply their knowledge in a real-world project.
Key Topics:
6G and beyond: hyperconnectivity, AI-native networks, and quantum communication
Integration with blockchain, digital twins, and metaverse technologies
Sustainable and green IoT deployment models
Economic and societal impact of 5G-IoT convergence
Capstone Project:
Participants design a 5G-IoT integration blueprint for a chosen industry (e.g., smart transportation, manufacturing, healthcare, or agriculture), incorporating architecture,
communication models, data flow, and security protocols.