6G Networks and the AI Revolution-Exploring Technologies, Applications, and Emerging Challenges - PubMed Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2024 Mar 15;24(6):1888.
doi: 10.3390/s24061888.

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

Affiliations
Review

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

Robin Chataut et al. Sensors (Basel). .

Abstract

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.

Keywords: 5G; 6G; Internet of Things; artificial intelligence; blockchain; machine learning; millimeter waves; quantum communication; terahertz communication; ultra-massive MIMO.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Figures

Figure 3
Figure 3
Features of 6G network.
Figure 1
Figure 1
Organizational structure of the paper.
Figure 2
Figure 2
Evolution of mobile communications: a chronological depiction of the advancements in mobile network technology from 1G in 1981 to the expected 6G in 2030. This visual encapsulates the major milestones in mobile communications, including the emergence of 2G and the introduction of SMS in 1992, the advent of 3G and mobile data in 2001, the expansion to 4G and high-speed internet access in 2011, and the integration of IoT with 5G in 2020. The future projection of 6G suggests a paradigm shift to smarter, AI-driven networks supporting 3D internet and enhanced video capabilities.
Figure 4
Figure 4
Applications of 6G networks.
Figure 5
Figure 5
Challenges for 6G deployment.
Figure 6
Figure 6
Overview of key enabling technologies for 6G networks. This diagram illustrates the advanced technological pillars essential for the deployment of 6G networks, including quantum communication, beamforming, ultra-massive MIMO, reconfigurable intelligent surfaces, AI/ML, millimeter waves, UAV or satellite communication, and terahertz waves. Each technology is crucial for enhancing future wireless communication systems data rate, reliability, and overall efficiency.

Similar articles

Cited by

References

    1. IMT Traffic Estimates for the Years 2020 to 2030. International Telecommunication Union (ITU) [(accessed on 25 October 2023)]. Available online: https://www.itu.int/pub/r-rep-m.2370.
    1. Bangerter B., Talwar S., Arefi R., Stewart K. Networks and Devices for the 5G Era. IEEE Commun. Mag. 2014;52:90–96. doi: 10.1109/MCOM.2014.6736748. - DOI
    1. Sinclair M., Maadi S., Zhao Q., Hong J., Ghermandi A., Bailey N. Assessing the Socio-Demographic Representativeness of Mobile Phone Application Data. Appl. Geogr. 2023;158:102997. doi: 10.1016/j.apgeog.2023.102997. - DOI
    1. Huseien G.F., Shah K.W. A Review on 5G Technology for Smart Energy Management and Smart Buildings in Singapore. Energy AI. 2022;7:100116. doi: 10.1016/j.egyai.2021.100116. - DOI
    1. Baier P., Dürr F., Rothermel K. TOMP: Opportunistic Traffic Offloading Using Movement Predictions; Proceedings of the 37th Annual IEEE Conference on Local Computer Networks; Clearwater Beach, FL, USA. 22–25 October 2012; pp. 50–58. - DOI

Grants and funding

This research received no external funding.