This survey formally categorizes state-of-the-art DTN architectures into passive monitoring twins and active control twins, and provides an in-depth evaluation of their underlying enabling technologies, specifically ray-tracing, reconfigurable intelligent surfaces, artificial intelligence, and mobile edge computing.
Abstract
The transition to the Sixth Generation (6G) of mobile networks requires proactive and deterministic orchestration to satisfy the stringent key performance indicators of future services, including ultra-reliable low-latency communications, enhanced mobile broadband, and massive machine-type communications. Digital Twin Networks (DTN) have recently emerged as a foundational technology to meet these demands, offering real-time and high-fidelity virtual replicas of the physical network. Although the current literature explores DTNs conceptually, a gap exists in the coverage of technical classification and computational feasibility evaluations. This survey addresses this gap by formally categorizing state-of-the-art DTN architectures into passive monitoring twins and active control twins. We provide an in-depth evaluation of their underlying enabling technologies, specifically ray-tracing, reconfigurable intelligent surfaces, artificial intelligence, and mobile edge computing. Importantly, this paper conducts a detailed mathematical and computational complexity analysis of state-of-the-art solutions to assess hardware scalability and inference bottlenecks. These architectures are then linked to various forthcoming 6G use cases, including smart cities, Industry 5.0, healthcare, and smart grids. Finally, we synthesize crucial unresolved challenges, highlighting graphics processing unit hardware limitations, cyber-physical actuation latency, and the need for a zero-trust security paradigm, offering strategic research directions to realize the unified internet of everything.
This dissertation focuses on the design, optimization, and experimental evaluation of NextG RANs integrating Open RAN principles, data-driven control loops, and intelligent resource allocation, demonstrating NextG RANs reconfigurable in real time to meet 6G requirements.
Sixth generation wireless mobile networks face many challenges. With the integration of non-terrestrial networks, wireless backhauls, multi-access edge computing, nomadic and non-public networks, the traditional assumption of a static and predictable control plane infrastructure has to be abandoned. The control plane network functions will no longer be deployed in a central location but geographically spread across the infrastructure. Different types of backhaul connections and deployment modes will mean less reliable and predictable control plane connections. This means that the core network has to be designed with these problems in mind. Running the 5G service-based architecture over a best-effort IP network is not sufficient in this regard. To address these new challenges, we propose the organic control plane. With an improved core network architecture and a robust control plane fabric, it is able to handle the heterogeneous and complex network infrastructure of the future, without compromising on performance. We implemented an organic 6G control plane, by combining our control plane fabric KIRA and our core network Open6GCore. Our evaluation using docker and Containernet shows that there is no significant performance impact, while providing improved dependability, scalability and flexibility.
Fabian Eichhorn, M. Corici, Thomas Magedanz et al.· IEEE Conference on Network S...· 0 citations
As the transition toward sixth-generation (6G) wireless networks accelerates, the demand for ultra-low latency and high energy efficiency has become paramount. Traditional Mobile Edge Computing (MEC) frameworks face significant challenges in highly dynamic and interference-limited environments. This survey explores a synergistic architectural framework that integrates Fluid Antenna Systems (FAS), Reconfigurable Intelligent Surfaces (RIS), and Hybrid Non-Orthogonal Multiple Access (NOMA)-MEC to address these requirements. We investigate how FAS-enabled port selection enhances channel disparity for optimized NOMA pairing, while RIS-controlled interference landscapes provide the stability necessary for robust Successive Interference Cancellation (SIC) decoding. This comprehensive survey provides a detailed roadmap for future research, highlighting the critical role of programmable physical layers in enabling the next generation of intelligent edge computing systems.
Kiet Nguyen Tuan Tran, Huy Dang Mac, Tung Son Do et al.· International Conference on...· 0 citations
A literature review approach is employed to synthesize domestic and international research findings on 6G, focusing on its key enabling technologies, typical application scenarios, and development bottlenecks, revealing that technologies including terahertz communication, reconfigurable intelligent surfaces (RIS), integrated sensing and communication (ISAC), and space-air-ground-sea integrated networking serve as the core pillars of 6G.
Tian Yang· Applied and Computational En...· 0 citations
This review systematically traces how mobile network technology has evolved from second-generation (2G) through fifth-generation (5G) systems, looks at how each generation has been applied in smart grid settings, and sets out what each generation could and could not do.
Musaab Abdelmageed Abdelraheem Abdalla· International Journal of Sci...· 0 citations
As many emerging applications like industrial internet, autonomous driving, and telemedicine works well only over strictly high performance networks, the deterministic networking technology has become a critical supporting infrastructure. In this article, we review the evolution roadway and supporting theories of deterministic networking technology. We characterize the core demands of 6G wireless deterministic networks on four dimensions: the performance dimension, the spatial dimension, the functional dimension, and the management dimension. Despite immense challenges, it is believed that 6G deterministic networks have a prospect future by exploring several key enabling technologies including advanced air interface technologies, innovative network architecture, the comprehensive integration of communication, sensing, computing, and control, as well as intelligent scheduling.