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GenAI & LLMs for
B5G Networks

DALL·E 2024-09-03 23.23.27 - A detailed futuristic illustration in a rectangular format, d

What is this book going to cover?

Generative AI (GenAI) and Large Language Models (LLMs) hold transformative potential for Beyond 5G (B5G) networks, fostering intelligent and autonomous network operations. These technologies can analyze vast amounts of data from various sources, enabling predictive maintenance, automated network optimization, and personalized services. They contribute to the creation of self-organizing networks that adapt to changing conditions in real-time, improving efficiency, reducing latency, and enhancing user experiences. Moreover, GenAI and LLMs facilitate the development of innovative applications and services, driving the evolution of B5G networks towards more adaptive, resilient, and user-centric architectures. As these networks become increasingly complex, the role of GenAI and LLMs becomes crucial in managing the network lifecycle and delivering the full potential of B5G capabilities.

From the User Equipment (UE) perspective, integrating GenAI and LLMs in Beyond 5G (B5G) and 6G networks can significantly enhance user experiences and device capabilities. Integrating GenAI and LLMs in UE for B5G and 6G networks represents a significant leap towards a more personalized, efficient, and intuitive user experience. These technologies can make devices not just tools but intelligent partners that understand and adapt to user needs, preferences, and environments, offering unprecedented levels of personalization and functionality.

From the B5G Radio Access Network (RAN) perspective, GenAI and LLMs can significantly enhance the design, operation, and user experience. Integrating GenAI and LLMs into B5G RAN is not just about enhancing current capabilities but also about reimagining network operations and services for the future. These technologies pave the way for networks that are more adaptive, efficient, and responsive, capable of meeting the complex and dynamic demands of the next generation of users and applications.

From the B5G core network perspective, GenAI and LLMs can revolutionize the way core networks are managed, operated, and evolved. Incorporating GenAI and LLMs into the B5G core network represents a significant shift towards more intelligent, flexible, and user-centric operations. These technologies enable the core network to not only respond to current requirements but also anticipate and adapt to future needs and challenges, driving innovation and excellence in service delivery and network performance.

From the service management and orchestration perspective in B5G and 6G networks, GenAI and LLMs can fundamentally transform how network services are managed, delivered, and optimized. Integrating GenAI and LLMs into service management and orchestration in B5G and 6G networks represents a paradigm shift towards more autonomous, efficient, and personalized network operations. By leveraging these technologies, networks can not only respond to current demands but also anticipate and adapt to future needs, driving innovation and excellence in service delivery.

General Manager

Dr. Sukhdeep Singh

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Samsung R&D India Bangalore

CVP / CTO

Mohan Rao GNS

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Samsung R&D India Bangalore

Associate Professor

Prof. Yulei Wu

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University of Bristol, UK

OUR EDITORIAL TEAM

Associate Dean / Professor

Prof. Neeraj Kumar

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Thapar University, India

General Manager

Dr. Madhan Raj K.

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Samsung R&D India Bangalore

Associate Professor

Prof. Navrati Saxena

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San Jose State University, CA, USA

Professor

Prof. Ali Kashif Bashir

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Manchester Metropolitan University, UK

Professor

Prof. Kshirasagar Naik

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University of Waterloo, Canada

Director

Ashok Kumar Reddy  Chavva

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Samsung R&D India Bangalore

GenAI & LLMs for UEs

Chapter: Enhanced User Experiences

1. Personalised connectivity

2. Predictive & Adaptive Interfaces

Chapter: Improved Security & Privacy

1. Proactive Threat Detection

2. Privacy Preserving personlization

Chapter: Intelligent & Autonomous Operations

1. Smart Resource Management

2. Adaptive Learning for Enhanced Functionality

Chapter: Enhanced Accessibility

1. Accessible Communication

2. Cotext Aware Assistance

GenAI & LLMs for B5G RAN

Chapter: Advanced Beamforming and MIMO

1. Dynamic Beamforming

2. Massive MIMO Optmization

Chapter: Virtualized & Open-RAN

1. Resource Orchestration in vRAN

2. Innovation through Open RAN

Chapter: Self-Organizing Networks

1. Automated Network Configuration

2. Self-Healing Mechanisms.

Chapter: Spectrum & Energy Efficiency

1. Spectrum Optimization

2. Energy-Saving Strategies

GenAI & LLMs for B5G Core

Chapter: Network Slicing & Virtuzlization

1. Dynamic Network Slicing

2. Virtualization & Orchestration

Chapter: Advanced Data Management & Analytics

1. Predictive Analytics

2. Real-Time Decision Making

Chapter: Enhanced Service Management

1. Automated Service Deployment

2. Quality of Service Optimization

Chapter: Personalization & User Experience

1. Contextual Service Provisioning

2. Intelligent Customer Support

GenAI & LLMs for Service Mngmnt & Orchestration

Chapter: Automated Service Management

1. Dynamic Service Creation & Deployment

2. Self-Healing Services..

Chapter: Predictive Analytics for Service Optimization

1. Traffic Prediction and Load Balancing

2. QoS Optimization

Chapter: Intelligent Orchestration

1. Resource Orchestration

2. Network Slice Orchestration

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| Abstract Submission: Oct 05, 2024 | Full Chapter Submission: Feb 01, 2025 | Camera Ready: March 01, 2025 |

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