TY - JOUR
T1 - Hydra-RAN Perceptual Networks Architecture
T2 - Dual-Functional Communications and Sensing Networks for 6G and Beyond
AU - Abd, Rafid I.
AU - Findley, Daniel J.
AU - Kim, Kwang Soon
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2024
Y1 - 2024
N2 - After researchers devoted considerable efforts to developing 5G standards, their passion began to focus on establishing the basics for the standardization of 6G and beyond. The utilization of millimeter wave (MMW) and terahertz (THz) frequency bands, combined with sensors and artificial intelligence (AI), has gained significant attention in the research community for the development of the next generation of sensory and radio access networks (NG-SRANs). Leveraging the advantages of communication and sensor systems' common characteristics will open horizons for merging the two networks, thereby creating a unified perceptive and intelligence network. Overall, while using MMW and THz frequencies is certainly valuable, the ability to gather and transmit data in real-time makes sensors extremely effective in communication networks. In contrast, AI, machine learning (ML), and deep learning (DL) have become predominant methods for solving data analysis problems across a wide range of domains, such as analyzing large amounts of different sensor data, decision-making, channel estimation, self-organization, and self-healing. This paper proposes a novel design for a potential 6G network and beyond called the Hydra radio access network (H-RAN) perceptual networks architecture, which is designed based on NG-SRAN. From a design perspective, H-RAN aims to merge communication and sensing networks into a single network in which two functionalities are attempted to mutually complement each other, namely communication-aided sensing and sensing-aided communications networks. However, such a network provides an adequate platform for a wide range of AL/ML algorithms, such as real-time decision-making, self-organization, and self-healing. As a result, H-RAN perceptual networks architecture is expected to be more efficient, reliable, and secure than existing conventional networks, and is likely to play a critical role in a wide range of applications, including but not limited to mobile broadband, sensing systems, smart cities, autonomous vehicles, the internet of things (IoT) connectivity, vehicle-to-everything (V2X) communication, etc. This study gives a detailed overview of how H-RAN will revolutionize conventional future sensors and cellular networks through a comprehensive analysis of H-RAN architectural components and functionalities.
AB - After researchers devoted considerable efforts to developing 5G standards, their passion began to focus on establishing the basics for the standardization of 6G and beyond. The utilization of millimeter wave (MMW) and terahertz (THz) frequency bands, combined with sensors and artificial intelligence (AI), has gained significant attention in the research community for the development of the next generation of sensory and radio access networks (NG-SRANs). Leveraging the advantages of communication and sensor systems' common characteristics will open horizons for merging the two networks, thereby creating a unified perceptive and intelligence network. Overall, while using MMW and THz frequencies is certainly valuable, the ability to gather and transmit data in real-time makes sensors extremely effective in communication networks. In contrast, AI, machine learning (ML), and deep learning (DL) have become predominant methods for solving data analysis problems across a wide range of domains, such as analyzing large amounts of different sensor data, decision-making, channel estimation, self-organization, and self-healing. This paper proposes a novel design for a potential 6G network and beyond called the Hydra radio access network (H-RAN) perceptual networks architecture, which is designed based on NG-SRAN. From a design perspective, H-RAN aims to merge communication and sensing networks into a single network in which two functionalities are attempted to mutually complement each other, namely communication-aided sensing and sensing-aided communications networks. However, such a network provides an adequate platform for a wide range of AL/ML algorithms, such as real-time decision-making, self-organization, and self-healing. As a result, H-RAN perceptual networks architecture is expected to be more efficient, reliable, and secure than existing conventional networks, and is likely to play a critical role in a wide range of applications, including but not limited to mobile broadband, sensing systems, smart cities, autonomous vehicles, the internet of things (IoT) connectivity, vehicle-to-everything (V2X) communication, etc. This study gives a detailed overview of how H-RAN will revolutionize conventional future sensors and cellular networks through a comprehensive analysis of H-RAN architectural components and functionalities.
KW - 6G networks and beyond
KW - broad exploitation of AI/ML engines
KW - dual-functional networks
KW - integration of sensor and communications networks
KW - perceptive networks
KW - self-organization/self-healing/IoT
KW - sensing/radio access networks (SRANs)
UR - http://www.scopus.com/inward/record.url?scp=85179780043&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85179780043&partnerID=8YFLogxK
U2 - 10.1109/ACCESS.2023.3341491
DO - 10.1109/ACCESS.2023.3341491
M3 - Article
AN - SCOPUS:85179780043
SN - 2169-3536
VL - 12
SP - 2162
EP - 2185
JO - IEEE Access
JF - IEEE Access
ER -