Allocation of power in NOMA based 6G-enabled internet of things using multi-objective based genetic algorithm

Saraswat, Shelesh Krishna; Deolia, Vinay Kumar; Shukla, Aasheesh

doi:10.2478/jee-2023-0012

Cited by 2 publications

(2 citation statements)

References 27 publications

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“…In network management, RL can be applied to optimize resource allocation, routing, and scheduling based on changing conditions [ 49 ]. A multi-objective-based genetic algorithm is an optimization algorithm inspired by natural selection that can be used to solve resource allocation problems in networks, adapting to changing demands and constraints [ 50 ]. Particle swarm optimization (PSO) is a population-based optimization algorithm that models the social behavior of particles.…”

Section: Ai and ML For 6g Networkmentioning

confidence: 99%

6G Networks and the AI Revolution—Exploring Technologies, Applications, and Emerging Challenges

Chataut,

Nankya,

Akl

2024

Sensors

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In the rapidly evolving landscape of wireless communication, each successive generation of networks has achieved significant technological leaps, profoundly transforming the way we connect and interact. From the analog simplicity of 1G to the digital prowess of 5G, the journey of mobile networks has been marked by constant innovation and escalating demands for faster, more reliable, and more efficient communication systems. As 5G becomes a global reality, laying the foundation for an interconnected world, the quest for even more advanced networks leads us to the threshold of the sixth-generation (6G) era. This paper presents a hierarchical exploration of 6G networks, poised at the forefront of the next revolution in wireless technology. This study delves into the technological advancements that underpin the need for 6G, examining its key features, benefits, and key enabling technologies. We dissect the intricacies of cutting-edge innovations like terahertz communication, ultra-massive MIMO, artificial intelligence (AI), machine learning (ML), quantum communication, and reconfigurable intelligent surfaces. Through a meticulous analysis, we evaluate the strengths, weaknesses, and state-of-the-art research in these areas, offering a wider view of the current progress and potential applications of 6G networks. Central to our discussion is the transformative role of AI in shaping the future of 6G networks. By integrating AI and ML, 6G networks are expected to offer unprecedented capabilities, from enhanced mobile broadband to groundbreaking applications in areas like smart cities and autonomous systems. This integration heralds a new era of intelligent, self-optimizing networks that promise to redefine the parameters of connectivity and digital interaction. We also address critical challenges in the deployment of 6G, from technological hurdles to regulatory concerns, providing a holistic assessment of potential barriers. By highlighting the interplay between 6G and AI technologies, this study maps out the current landscape and lights the path forward in this rapidly evolving domain. This paper aims to be a cornerstone resource, providing essential insights, addressing unresolved research questions, and stimulating further investigation into the multifaceted realm of 6G networks. By highlighting the synergy between 6G and AI technologies, we aim to illuminate the path forward in this rapidly evolving field.

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Section: Ai and ML For 6g Networkmentioning

confidence: 99%

6G Networks and the AI Revolution—Exploring Technologies, Applications, and Emerging Challenges

Chataut,

Nankya,

Akl

2024

Sensors

View full text Add to dashboard Cite

show abstract

“…In network management, RL can be applied to optimize resource allocation, routing, and scheduling based on changing conditions [105]. Multi-objective-based genetic algorithm is an optimization algorithm inspired by natural selection which can be used to solve resource allocation problems in networks, adapting to changing demands and constraints [106]. Particle Swarm Optimization (PSO) is a population-based optimization algorithm that models the social behavior of particles.…”

Section: Artificial Intelligence and Machine Learning For 6g Networkmentioning

confidence: 99%

6G Networks and AI Revolution - Exploring Technologies, Applications, and Emerging Challenges

Chataut,

Nankya,

Akl

2023

Preprint

View full text Add to dashboard Cite

In the rapidly evolving landscape of wireless communication, each successive generation of networks has achieved significant technological leaps, profoundly transforming the way we connect and interact. From the analog simplicity of 1G to the digital prowess of 5G, the journey of mobile networks has been marked by constant innovation and escalating demands for faster, more reliable, and more efficient communication systems. As 5G becomes a global reality, laying the foundation for an interconnected world, the quest for even more advanced networks leads us to the threshold of the sixth-generation (6G) era. This paper presents a hierarchical exploration of 6G networks, poised at the forefront of the next revolution in mobile wireless technology. This study delves into the technological advancements that underpin the need for 6G, examining its key features, benefits, and the key enabling technologies. We dissect the intricacies of cutting-edge innovations like terahertz communication, ultra-massive MIMO, artificial intelligence (AI), machine learning, quantum communication, and re-configurable intelligent surfaces. Through a meticulous analysis, we evaluate the strengths, weaknesses, and state-of-the-art research in these areas, offering a wider view of the current progress and potential applications of 6G networks. Central to our discussion is the transformative role of AI in shaping the future of 6G networks. By integrating AI and machine learning, 6G networks are expected to offer unprecedented capabilities, from enhanced mobile broadband to groundbreaking applications in areas like smart cities and autonomous systems. This integration heralds a new era of intelligent, self-optimizing networks that promise to redefine the parameters of connectivity and digital interaction. This paper also addresses critical challenges in the deployment of 6G, from technological hurdles to regulatory concerns, providing a holistic assessment of potential barriers. By highlighting the interplay between 6G and AI technologies, this study not only maps out the current landscape but also lights the path forward in this rapidly evolving domain. This paper aims to be a cornerstone resource, providing essential insights, addressing unresolved research questions, and stimulating further investigation into the multifaceted realm of 6G networks. By highlighting the synergy between 6G and AI(Artificial Intelligence) technologies, we aim to illuminate the path forward in this rapidly evolving field.

show abstract

Allocation of power in NOMA based 6G-enabled internet of things using multi-objective based genetic algorithm

Cited by 2 publications

References 27 publications

6G Networks and the AI Revolution—Exploring Technologies, Applications, and Emerging Challenges

6G Networks and the AI Revolution—Exploring Technologies, Applications, and Emerging Challenges

6G Networks and AI Revolution - Exploring Technologies, Applications, and Emerging Challenges

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