Digital-Twin-Enabled 6G Vision, Architectural Trends, and Future Directions

We have discussed Digital Twin here and in our training here. In the Digital Twins: The Ultimate Guide, XMPro identified three patterns for IoT use cases and created three digital twin types based on these patterns: 

  • Status Twin: Typically used for basic condition monitoring applications such as dashboards and simple alerting systems. It indicates operating parameters and is generally created with visualization tools. XMPro provides dashboard and HMI views in support of these twins.
  • Operational Twin: Provides more extensive information that is typically used in decision support by operators, reliability engineers, and other decision-makers. It is linked to a set of actions or workflows where users can interact with the twin and change operating parameters where control capability is allowed.
  • Simulation Twin: Leverages different types of simulation or artificial intelligence capabilities to predict, forecast, or provide insight into future operational states. You can use it for predictive maintenance or to improve the recovery yield of a processing plant.

We are describing this here because the paper referred below uses Operational Twin for their research.

The authors in the new research paper, submitted to the IEEE for possible publication, available on arXiv, 'Digital-Twin-Enabled 6G: Vision, Architectural Trends, and Future Directions', argue that digital twin will serve as a key enabler of 6G services. The paper describes a digital twin-based architecture for 6G and an outlook on future research. the abstract says:

Internet of Everything (IoE) applications such as haptics, human-computer interaction, and extended reality, using the sixth-generation (6G) of wireless systems have diverse requirements in terms of latency, reliability, data rate, and user defined performance metrics. Therefore, enabling IoE applications over 6G requires a new framework that can be used to manage, operate, and optimize the 6G wireless system and its underlying IoE services. Such a new framework for 6G can be based on digital twins. Digital twins use a virtual representation of the 6G physical system along with the associated algorithms (e.g., machine learning, optimization), communication technologies (e.g., millimeter-wave and terahertz communication), computing systems (e.g., edge computing and cloud computing), as well as privacy and security-related technologists (e.g., blockchain). First, we present the key design requirements for enabling 6G through the use of a digital twin. Next, the architectural components and trends such as edge-based twins, cloud-based-twins, and edge-cloud-based twins are presented. Furthermore, we provide a comparative description of various twins. Finally, we outline and recommend guidelines for several future research directions.

The authors describe their main contributions as part of the paper as follows:

  • We present the key design requirements to realize the vision of digital-twin-enabled 6G systems. These requirements are decoupling, scalable intelligent analytics, blockchain-based data management as well as scalability and reliability.
  • We propose an architecture for digital-twin-enabled 6G and present its various trends based on deployment fashion of twins.
  • Finally, we provide an outlook on future research directions. 

To the best of our knowledge, this is the first work to study digital-twin-enabled 6G systems. In contrast to existing works on 6G, this paper presents a new perspective regarding the development of intelligent, self-sustaining 6G wireless systems enabled by digital twin.

The PDF is available here.

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