Qualitative Survey on Artificial Intelligence Integrated Blockchain Approach for 6G and Beyond

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F23%3A50020767" target="_blank" >RIV/62690094:18450/23:50020767 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/10262312" target="_blank" >https://ieeexplore.ieee.org/document/10262312</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ACCESS.2023.3319083" target="_blank" >10.1109/ACCESS.2023.3319083</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Qualitative Survey on Artificial Intelligence Integrated Blockchain Approach for 6G and Beyond

Popis výsledku v původním jazyce

Utilizing the 0.1 to 10 THz spectrum in the next-generation wireless communication networks holds potential for futuristic applications. However, managing resources to accommodate numerous devices raises privacy and security concerns. Further, technology proliferation entwines devices, infrastructure complexity, and resources. Indeed, the transition from 5G (fifth-generation) to 6G (sixth-generation) signifies a progression towards high-speed data rates, minimal latency, and seamless integration of artificial intelligence, enabling ground-breaking applications and services. However, it complicates network management, privacy, resource allocation, and data processing. Notably, integrating Blockchain Technology (BCT) and Machine Learning (ML) is a promising solution, enhancing security, decentralization, trust in ML decisions, and efficient data sharing. This survey thoroughly reviews the integrated ML and BCT, showcasing their collaborative enhancement of network security, decentralization, trust in ML decisions, immutability, and efficient model sharing. Furthermore, we also delve into various distinctive topics, such as BCT-enabled spectrum refarming, rate splitting multiple access, 6G radar-based communication, reconfigurable intelligent surfaces, visible light communication, and integrated sensing and communication. Moreover, it also explores the integration of ML and BCT in novel 6G communication technologies, including molecular, holographic, and semantic communication. Finally, critical open issues, challenges, solutions, and futuristic scope are identified for forthcoming researchers.

Název v anglickém jazyce

Qualitative Survey on Artificial Intelligence Integrated Blockchain Approach for 6G and Beyond

Popis výsledku anglicky

Utilizing the 0.1 to 10 THz spectrum in the next-generation wireless communication networks holds potential for futuristic applications. However, managing resources to accommodate numerous devices raises privacy and security concerns. Further, technology proliferation entwines devices, infrastructure complexity, and resources. Indeed, the transition from 5G (fifth-generation) to 6G (sixth-generation) signifies a progression towards high-speed data rates, minimal latency, and seamless integration of artificial intelligence, enabling ground-breaking applications and services. However, it complicates network management, privacy, resource allocation, and data processing. Notably, integrating Blockchain Technology (BCT) and Machine Learning (ML) is a promising solution, enhancing security, decentralization, trust in ML decisions, and efficient data sharing. This survey thoroughly reviews the integrated ML and BCT, showcasing their collaborative enhancement of network security, decentralization, trust in ML decisions, immutability, and efficient model sharing. Furthermore, we also delve into various distinctive topics, such as BCT-enabled spectrum refarming, rate splitting multiple access, 6G radar-based communication, reconfigurable intelligent surfaces, visible light communication, and integrated sensing and communication. Moreover, it also explores the integration of ML and BCT in novel 6G communication technologies, including molecular, holographic, and semantic communication. Finally, critical open issues, challenges, solutions, and futuristic scope are identified for forthcoming researchers.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

IEEE Access

ISSN

2169-3536

e-ISSN

2169-3536

Svazek periodika

11

Číslo periodika v rámci svazku

October

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

47

Strana od-do

105935-105981

Kód UT WoS článku

001081631300001

EID výsledku v databázi Scopus

2-s2.0-85173059063