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.
Recent years have seen the evolution of the traditional Radio Access Network (RAN) toward more open, programmable, disaggregated, and intelligent architectures, known as an Open RAN. Future Next Generation (NextG) networks are envisioned to be AI-native, enabling data-driven closed-loop optimization of Base Station resources, while Reconfigurable Intelligent Surfaces (RIS) emerge as key enablers for wireless propagation and spectral efficiency toward 6G and beyond. 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. The work emphasizes cross-layer optimization, including energy-efficient power control, and explores AI-driven network slicing, scheduling, and link adaptation, demonstrating NextG RANs reconfigurable in real time to meet 6G requirements, first analyzing architectural enablers and modeling frameworks, then prototyping and evaluating solutions on experimental platforms and Digital Twins. Main contributions include: (i) Deep Reinforcement Learning (DRL) solutions for network slicing and scheduling; (ii) PandORA, a framework for automatic design, training, and deployment of DRL-based Open RAN applications on the Colosseum wireless network emulator; (iii) physical-layer RIS channel modeling and optimized resource allocation across spectrum bands; (iv) system-level evaluation of RIS-assisted channels for eMBB and URLLC traffic; (v) integration of RIS within Open RAN; (vi) online RL solutions for link adaptation; and (vii) spectrum sharing between cellular and Non-Terrestrial Network links via power control and beamforming. This work provides algorithmic designs, frameworks, and validation from simulation and hardware-in-the-loop emulation to over-the-air 5G testbed experiments, addressing industry and academic needs for wireless research.
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
The iterative evolution of mobile communication technology serves as a core driver of the digital economy's growth. With 5G having achieved large-scale global commercialization, research into 6G—aimed at meeting the demands of the "Internet of Intelligent Things" and ubiquitous connectivity—is now fully underway worldwide. This paper employs a literature review approach to synthesize domestic and international research findings on 6G, focusing on its key enabling technologies, typical application scenarios, and development bottlenecks. The study reveals 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. 6G is poised for deep integration into scenarios like intelligent immersive communication and the Industrial Internet, while hardware development, algorithm optimization, and the unification of standards remain primary challenges. Future work needs to coordinate progress in core technological breakthroughs, standardization and engineering deployment to achieve high-performance and ubiquitous intelligent connectivity.
Tian Yang· Applied and Computational En...· 0 citations
Their wide coverage, scalability and cost-effective infrastructure have made mobile cellular networks key enablers of smart grid modernization. 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.
Early on, second-generation GSM and GPRS supported basic Automatic Meter Reading (AMR) and simple SCADA polling, but high latency and unidirectional communication constrained what these networks could realistically support. Third-generation UMTS and HSPA improved on this by introducing bidirectional Advanced Metering Infrastructure (AMI), including remote connect and disconnect capability, which in turn made large-scale smart meter rollouts practical. With fourth-generation latency dropped to 20–50 ms, enabling real-time distribution automation and Phasor Measurement Unit (PMU) streaming. Fifth-generation NR takes this further still, introducing Ultra-Reliable Low-Latency Communication (URLLC) with latency as low as 1–5 ms, along with network slicing and Massive Machine-Type Communication (mMTC), which together address most of the remaining barriers to wireless grid protection.
Global pilot projects across Europe, China, and North America have validated these capabilities in live grid environments. Still Mobile communications for Smart Grids are facing challenges, including rural coverage economics, cybersecurity threats and legacy system migration. Each generation has systematically resolved the critical limitations of its predecessor, with 5G representing the most comprehensive wireless solution for smart grid applications to date.
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.