In the 6G era, the demand for collaborative operations among heterogeneous intelligent agents, such as robots and unmanned aerial vehicles, is growing rapidly. Traditional network design approaches that treat communication links as the fundamental unit and prioritize transmission performance metrics such as data rate are encountering bottlenecks. Unmanned operations are often carried out in the form of a reflex-arc-like closed loop of “Sensing-Communication-Computing-Control” (SC³). This paper presents a survey based on a new model that takes the SC³ closed loop as the basic unit, introduces new metrics including the closed-loop negentropy rate and new network elements such as the edge information hub, elaborates a novel framework for closed-loop-oriented network optimization design, and discusses future development directions.

With the evolution of 6G networks toward convergence of communication and computing, conventional networks relying primarily on transmission rate optimization are insufficient to satisfy the requirements of high bandwidth, low latency, and intensive computing. Focusing on coordination of heterogeneous resource in integrated communication and computing networks, this paper introduces the architectures of 6G networks and the mechanisms of resource collaboration, and analyzes two representative paradigms, namely computing-assisted communication and communication-assisted computing, including semantic communication and collaborative mobile edge computing. Furthermore, key issues in intelligent resource management, such as end-to-end communication efficiency, multi-user communication resource competition, and computing resource competition, are discussed, providing insights into resource coordination and optimization for future 6G networks.

The deep integration of 5G-Advanced (5G-A) and Artificial Intelligence (AI) is emerging as a key driving force behind industrial intelligent transformation. Focusing on the development trends of communication-intelligence convergence, this paper systematically reviews the theoretical framework and application scenarios of 5G-A and AI integration from the perspective of the coordinated evolution of communication-data-computing-intelligence. It further examines emerging integrated application paradigms in representative sectors such as industrial manufacturing and intelligent transportation. Building on the current state of industrial development, the paper also provides a forward-looking analysis of future trends in network capability evolution, edge intelligence, industry collaboration, and ecosystem development driven by the integration of 5G-A and AI. This study argues that the convergence of 5G-A and AI will accelerate the evolution of industrial terminals from “connected devices” to “intelligent terminals”, while promoting the transformation of communication networks from “data transmission infrastructure” toward “intelligent service infrastructure”, thereby providing important support for the deep integration of the digital economy and the real economy.

Currently, the large-scale application of embodied intelligence still faces three key bottlenecks: limited on-device computing capacity, short battery endurance, and prohibitive hardware costs. Although the current 5G-Advanced (5G-A) edge computing achieves basic connectivity-computation integration, edge resources are implemented as add-on components, yielding loose coupling of communication and computing resources and poor AI-service quality in dynamic radio channels. To address these limitations, this paper develops a 6G communication-computing-intelligence converged network architecture for embodied intelligence use cases, where communication, computing, data and model resources are placed under native network orchestration. The effectiveness of this approach is validated through a prototype system demonstrating device-edge synergy. Finally, the paper further analyzes the enabling role of 6G’s communication-computing-intelligence convergence in driving the evolution of embodied intelligence applications.

With the deep integration of artificial intelligence (AI) and robotics, embodied AI is evolving from monolithic and closed task execution toward autonomous collaboration and continuous evolution in real dynamic environments. This paper provides an analysis of the future evolution of embodied AI, identifying heterogeneity, generalization, and distributed collaboration as key evolutionary paths. Based on these insights, this paper proposes a systematic evolution architecture comprising embodied agents, near-source agents, cloud agents, and the internet of agents, providing a reference for the scalable, collaborative, and networked development of embodied AI.

With the rapid development of closed-loop services including industrial control, low-altitude intelligent connectivity, and cooperative vehicle-infrastructure systems, the conventional 5G network can hardly satisfy the performance requirements for closed-loop control, such as millisecond-level latency, microsecond-level jitter and high reliability. One of the core directions of 5G-Advanced (5G-A) is to realize the native integration of communication, computation and control. This paper sorts out the key technical system supporting communication-computation-control integration in 5G-A, designs a native integrated network architecture, proposes a three-phase evolution path for basic telecom operators to migrate existing 5G networks towards the native communication-computation-control architecture, and analyzes its relationship with 6G. The research indicates that the native communication-computation-control integration of 5G-A acts as a core enabler for industrial digital upgrading, and serves as an important technical and commercial verification foundation for the native integrated architecture of 6G.

Against the backdrop of rapid advancements in Artificial Intelligence (AI), the capabilities of AI-driven cyber-attacks are undergoing a marked leap, profoundly reshaping the global landscape of cyberattack and defense. This paper systematically analyzes the significant enhancements in AI-driven attacks in terms of destructiveness, attack thresholds, and vulnerability discovery capabilities. It reveals the underlying logic that makes critical infrastructure a primary target of AI attacks, and dissects the common threats facing China’s infrastructure from three dimensions: the information layer, the platform layer, and the physical layer. On this basis, the paper further examines the key challenges confronting China’s infrastructure, including security risks arising from intelligent upgrades and the capacity bottlenecks of traditional defense systems. The findings indicate that urgent efforts are required to strengthen security governance during intelligent upgrades and to build a novel defense architecture tailored to the characteristics of AI-driven attacks, thereby reinforcing the security shield for infrastructure. As AI attacks are rapidly evolving from isolated attempts to large-scale threats, the coming years will witness a critical turning point. It is therefore strongly recommended that high priority be given to accelerating the development of a new defense system capable of effectively responding to the distinctive features of AI-enabled threats.

This paper focuses on the mid- and low-band spectrum resources for 5G and conducts an in-depth study on 5G spectrum policies covering demand analysis and frequency planning, allocation and licensing, interference coordination, and evaluation and feedback. The outstanding achievements enabled by China’s sophisticated spectrum policies in supporting the advancement of 5G are reviewed, including network deployment, industrial development, sector empowerment, and global impact. This paper summarizes the successful experience in spectrum management from the perspective of frequency resources supporting 5G development, providing a reference for the next-generation mobile communications to efficiently leverage spectrum resources and boost the vigorous development of the industry.

As quantum computing technology transitions from theoretical exploration to early application, large tech enterprises, startups, and telecommunications operators are actively deploying quantum computing service platforms to seize new opportunities in the future information industry. By systematically discussing the current state of quantum computing services both domestically and internationally and analyzing the strategic significance and overall advantages of operators entering the quantum computing service sector, this paper designs a functional architecture of the quantum computing service platform for Chinese telecom operators. It proposes a business operation model based on “multi-route integration, cloud-network-computing convergence, and collaboration ecosystem”, aiming to provide strategic decision-making reference for Chinese telecom operators in the quantum computing era.

To meet the requirements of real-time speech transcription display in conference simultaneous interpretation scenarios, the system must achieve low latency, high accuracy, and strong readability. For this purpose, systematic evaluation metrics and an offline streaming simulation assessment method are established to compare the performance differences between streaming (Sherpa-onnx) and non-streaming (Faster-Whisper) speech recognition solutions, offering a reference for research in related fields. Experimental results indicate that the streaming speech recognition approach, when coupled with a lightweight semantic post-processing strategy, exhibits overall performance that better satisfies the comprehensive demands of real-time speech transcription in industrial-grade conference systems.

In the current vehicle-road collaboration systems, only digital signatures are relied upon to ensure the integrity and authenticity of messages, without encrypting the message content for confidentiality. Due to the lack of encryption mechanisms, all vehicles can freely get vehicle-road collaboration systems service information without authorization, which limits the development of subscription-based or license-based commercial operations. To address this problem, this paper proposes a business model and technical solution based on existing vehicle-road collaboration systems architecture and secure communication protocols. While maintaining the current signature mechanism, symmetric encryption algorithms are adopted to encrypt the content of service messages, ensuring precise control over service recipients and message confidentiality. Experimental results show that the additional processing latency introduced by encryption and decryption operations is minimal and does not significantly impact the timeliness requirements of vehicle-road collaboration systems services, demonstrating the feasibility of large-scale deployment.

Hot update technology is widely utilized in mobile applications for scenarios such as rapid patching and lightweight updates. However, malicious developers abuse this mechanism to bypass App store security audits, posing potential security risks. To address the challenges of high monitoring costs, significant detection difficulties, and intense technical adversarial confrontanion associated with malicious hot updates, this paper proposes a detection method based on multi-feature analysis. This method performs a comprehensive analysis of the control flow features of hot update code, runtime behavioral features, and application fingerprint features. This paper collected a total of 12 982 Apps and 300 malicious samples for experimental analysis, and identified 11 newly detected malicious Apps and 29 malware familes. Experimental results demonstrate that the proposed method can effectively identify malicious hot update behaviors.