The Report Minimum Technical Performance Requirements for IMT-2030 (6G) was formally finalized at the 51st meeting of ITU-R Working Party 5D (WP 5D), which concluded on 12 February 2026. It marks the official transition of 6G from vision and concept to the implementation phase, laying a solid foundation for the subsequent submission and evaluation of candidate technology proposals, as well as the development of globally unified standards.
This report systematically defines multiple key performance indicators that 6G radio interface technologies shall meet. For example, peak network capacity in large-scale networking, ubiquitous determinism and composite requirements, among other factors, are posing new challenges for the development of 6G networks.
6G: The infrastructure for Human-Agent Synergy
Beyond the evolution of standards, we are witnessing the rapid advancement of AI. ZTE argues that the industry is moving from the mobile internet era to an agent-centric internet era, a shift that will transform service requirements across three dimensions: connected objects, interactive content and service paradigms. Connectivity, the company says, will expand from humans + things to humans + things + intelligent agents, with always-on agents demanding ubiquitous and deterministic connections. At the same time, interactive experiences are expected to evolve from visual-audio content to AI-driven multi-sensory immersion, increasing requirements for uplink and downlink performance, latency and jitter. Service paradigms will also change, as traditional application-centric networks evolve into agent networks that support service agents. These networks will need to deliver integrated information services that combine sensing, data processing and intelligence, with generative strategies to support diverse and ubiquitous AI services.
6G is the infrastructure for a Human-Agent Synergy world. In response, ZTE says it has built a full-chain, systematic 6G strategic technology layout across standards, chips, architecture and algorithms, encompassing two transformative technology directions and four evolutionary technology directions.
AI and space-air-ground integration as core pillars of ZTE 6G technical strategy
Against this backdrop, the company has outlined a strategic 6G technology roadmap built around two primary transformative directions: the deep integration of artificial intelligence and communications, and the convergence of space, air and ground networks.
The first major direction is the deep integration of AI and communications. ZTE’s vision of “Native AI” in 6G suggests that artificial intelligence will permeate not only the network layer, but also the radio access network (RAN) and the air interface itself. The company says AI has already demonstrated value in improving metrics such as spectral efficiency, but several key questions remain, including how to deliver more efficient and green infrastructure and how to coordinate the evolution of agentic networks and service agents.
The second direction is space-air-ground integration. As international research and standardization efforts progress, ZTE sees the convergence of satellite systems and cellular networks as an inevitable trend. By leveraging the large-scale industrial chain of terrestrial cellular networks, satellite payloads based on industrial-grade chips could achieve better performance and cost efficiency than traditional satellite systems. However, the company notes that true integration will require unified end-to-end design across architecture, air interface, spectrum and operational management.
Meanwhile, ultimate spectral efficiency, innovative AI IoT, functional expansion and trusted security stand as the four enduring evolutionary technology directions.
Efficiency is the key driver towards a well-balanced way of AI RAN
ZTE positions efficiency as a central design principle for 6G systems, especially as AI becomes more deeply embedded in network infrastructure. The company separates this integration into two distinct dimensions: “AI for RAN” and “RAN for AI”.
AI for RAN refers to the use of artificial intelligence to improve network performance, reduce energy consumption and lower operational expenses. According to ZTE, this area presents large-scale and deterministic demand, and dedicated chips offer the optimal cost-performance ratio. The company notes that only a small number of physical-layer AI modules have been standardized so far, and for functions with clear mathematical models, dedicated chips paired with traditional algorithms are more suitable than GPUs, which can consume more power and incur higher costs without delivering significant performance gains.
By contrast, RAN for AI explores the evolution of the radio access network into edge AI infrastructure. Here, ZTE sees several challenges. The distributed nature of RAN means its computing scale is far smaller than that of centralized cloud AI infrastructure. While edge AI offers latency advantages for specific use cases, the overall market remains uncertain, and operators have not yet seen returns that justify large-scale GPU investments. As a result, the company believes RAN for AI should follow a demand-driven deployment approach.
The convergence of AI and communications is an inevitable trend, and ZTE has been embracing AI proactively and driving continuous innovation along this path. The company introduced the NodeEngine computing base station in 2020, followed by the UniEngine hyper-converged device and, in 2024, the AIREngine intelligent computing engine for base stations. Furthermore, from a systematic end-to-end perspective, in 2025, we delivered the AIR solution; today, by shifting the focus from network performance to business value under the technical philosophy of serving AI with AI, AIR MAX aims to maximize efficiency in three directions: energy efficiency, labor efficiency and investment efficiency through the upgrade of technical architecture, production efficiency and business model.
GigaMIMO leads AI-native wireless, ushering in a new phase of 6G
ZTE’s GigaMIMO addresses key challenges around capacity, coverage and deterministic experience for large-scale 6G network deployments.
In the race to innovate core 6G technologies, ZTE has made multiple breakthroughs and developed a suite of corresponding prototypes—with its GigaMIMO architecture standing out as a flagship advancement for 6G tech innovation and the deep integration of AI. Leveraging its early work on massive MIMO dating back to the pre-5G era, the vendor has engineered both centralized and distributed GigaMIMO architectures, built to boost network capacity, expand coverage and elevate end-user experience.
• Powered by multi-dimensional technical innovation and refined AI integration—including AI-driven link adaptation, beam prediction and intelligent scheduling—ZTE’s centralized GigaMIMO prototype, which features 2048 antenna elements in the U6G band (6425–7125 MHz), has delivered significant performance breakthroughs in field tests, delivering a 10x increase in cell capacity and enabling co-site coverage with mid-band 5G.
• For its distributed GigaMIMO solution, ZTE has innovatively deployed a portfolio of AI collaborative scheduling technologies, such as high-precision inter-cell and inter-site synchronization, channel state information compression and feedback, and low-complexity joint beamforming enhancement. Validated in a commercial network in partnership with China Mobile, these technologies have boosted edge user experience by sixfold.
Additionally, through the co-design of massive MIMO and AI algorithms, spectral efficiency is enhanced by more than 30%, while ensuring consistent network experience and differentiated service capabilities, laying a solid foundation for the large-scale deployment of 6G.
The company is also working with ecosystem partners. Together with China Mobile, the company completed the industry’s first IoDT (Interoperability Development Testing) verification via a Qualcomm prototype based on GigaMIMO technology with 400 MHz in a single carrier.
Industry collaboration and immersive use cases
ZTE emphasizes that collaboration across the industry chain will be essential for 6G development.
As AI evolves from conversational interaction to closed-loop execution and physical AI, devices will face challenges related to computing power, form factor, battery life and cost. The company says this makes end-edge-cloud collaboration critical for enabling a broad range of AI services.
One of the early use cases the company is exploring is AI-powered immersive communication. ZTE expects technologies such as AI glasses and spatial computing to enable multi-sensory experiences that go beyond sight and sound to include touch and perception.
ZTE plans to showcase a range of 6G-related exhibits at the upcoming Mobile World Congress in Barcelona, Spain, highlighting both its long-term vision and ongoing technical work across AI integration, space-air-ground convergence and next-generation radio technologies.
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