As shared by Shen Jianda, Vice President of ZTE, ZTE is addressing this shift through two complementary approaches: simplifying sites through multi-band and multi-mode convergence, and improving network efficiency through AI-driven optimisation. Together, they aim to reduce the cost and complexity of network evolution while extracting more capacity and value from existing infrastructure.
Multi-Band and Multi-Mode Convergence: Simplifying the Site
The first task is physical consolidation. ZTE’s Ultra Broadband Radio (UBR) portfolio combines multiple frequency bands, channels and sectors in fewer radio units. Its low- and mid-band portfolio includes three-, four- and five-band UBR solutions, alongside a 6T Omni UBR and differentiated 12T products. Super-N 2.0 power amplifiers and lightweight designs further help reduce equipment footprint, tower loading and energy consumption.
Commercial deployments illustrate the potential savings. A world-first five-band UBR deployed with TIM Brazil and MTN South Africa reduced the number of tower radio units by 50%, equipment weight by 23%, wind load by 18% and power consumption by 42.7%. In a four-band UBR deployment in Malaysia, site channel capability increased from 2T to 4T whilst the number of RRUs per site fell from nine to three, reducing tower rental and deployment requirements whilst facilitating 4G and 5G coexistence.
Yet site simplification is not simply about removing radio units. Consolidated hardware must also support more modes, more bands and greater capacity.
ZTE extends this principle to Massive MIMO in three dimensions. First, more modes are integrated into a single unit: its FDD Massive MIMO (FMM) supports 2G, 3G, 4G and 5G, while the world’s first FDD-TDD dual-mode Massive MIMO brings the two duplex modes together in one unit. Second, more bands are consolidated: dual- and tri-band Massive MIMO products can integrate multiple bands into a single unit—for example, 700/800/900 MHz in the low band, or 2.6/3.5 GHz in the mid band. This allows operators to consolidate spectrum assets where technically appropriate, reducing the need for separate radio equipment. Third, higher transmit power provides greater capacity and coverage from the consolidated hardware, with maximum transmit power reaching 720W for FDD Massive MIMO and 500W for TDD Massive MIMO.
Commercial deployments demonstrate the maturity of ZTE’s Massive MIMO portfolio. FDD Massive MIMO has been commercially deployed across diverse markets worldwide, including Malaysia, Pakistan, Kazakhstan, Côte d’Ivoire, Nigeria and Kyrgyzstan. Dual-band TDD Massive MIMO has also been widely deployed in markets including Indonesia, Italy, Algeria, Cameroon and Peru. Meanwhile, the world’s first FDD-TDD dual-mode Massive MIMO has been commercially deployed in Gabon at scale.
The hardware provides the foundation. AI provides the next step—making that capacity more adaptive to actual demand.
AI-Powered Massive MIMO: Higher Speeds, Greater Capacity
More radio capacity does not automatically mean that capacity is used efficiently. Traffic fluctuates throughout the day, users move across the network, radio conditions change and demand shifts between frequency bands. ZTE’s AI-powered Massive MIMO suite therefore applies intelligence at three levels: adapting cell configuration to traffic, improving user-level scheduling, and coordinating resources across bands.
For FDD Massive MIMO, AI makes cell configuration responsive to traffic demand. ZTE’s intelligent sectorisation dynamically adjusts the number of cells within a sector according to traffic load. During low-traffic periods, the system can operate with fewer cells; during busy periods, it can dynamically expand to as many as six cells per sector. By matching cell configuration more closely to actual demand, intelligent sectorisation can deliver up to 20% additional capacity gain compared with the industry average.
For TDD Massive MIMO, AI focuses on allocating capacity more efficiently among users. AI-enhanced MU-MIMO improves user pairing by identifying users that can be served more efficiently together, increasing MU-MIMO efficiency in high-capacity scenarios. AI-enhanced adaptive modulation and coding (AI AMC) tracks changes in user and radio conditions in real time and selects more appropriate transmission and scheduling parameters. This allows radio resources to follow changes in user status more precisely.
At the cross-band level, AI turns separately managed radio resources into a coordinated resource pool. Instead of optimising each frequency band independently, the system jointly coordinates beam, power, frequency and time resources across multiple bands. This allows available resources to be allocated more dynamically as traffic patterns, radio conditions and user distribution change.
These capabilities are supported by a lightweight plug-in AI board in the BBU, where embedded algorithms process complex wireless-channel conditions and large volumes of live-network data. This approach reduces computational complexity by fourfold and has demonstrated capacity gains of up to 5 times for 5G and 3 times for 4G in applicable scenarios compared with conventional 4T4R macro cells. The AI engine can also coordinate frequency and beam selection with functions such as load balancing and handover management, helping improve service consistency across the network.
Commercial deployment provides another test of the approach. In Pakistan, Zong’s dual-band FMM deployment increased network traffic by 140% and downlink speeds by 270%. Building on these gains, AI-powered optimisation delivered a further improvement, increasing average user downlink throughput by up to 39.4% during busy hours and 34.3% on a daily basis, while boosting traffic load by up to 17.1% and 21.5%, respectively.
Together, hardware convergence and AI optimisation offer operators two complementary ways to improve network economics: simplifying the physical network while making radio resources more adaptive to demand. The aim is not simply to add capacity, but to make better use of infrastructure and spectrum already deployed.
“ZTE has long been committed to delivering differentiated and competitive products and solutions to global operators,” said Shen. “Looking ahead, we will continue to combine advances in radio technology with AI, working with operators worldwide to build networks that are simpler, more efficient and more intelligent, and to translate these improvements into tangible business value.”
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