The fifth generation of cellular wireless networks, 5G, isn’t just faster cellular; it’s a foundational shift in how devices, machines, and infrastructure connect in real time. With ultra-low latency, high capacity, and edge intelligence, 5G is enabling entirely new classes of applications across industries.

The evolution of 5G-Advanced to 6G will deliver significant enhancements for the wireless industry. Here is what’s next for wireless networks and why it matters.

5G enters its advanced phase

Now with over 2.4 billion connections worldwide, 5G has already delivered major upgrades in mobile data rates, spectrum efficiency, and network flexibility. But as the first wave of commercial deployments matures, the wireless industry is in the midst of a shift toward a more sophisticated phase of 5G, known as 5G-Advanced, that represents a technically significant step forward.

Standardized through 3rd Generation Partnership Project (3GPP) Releases 18 and 19, 5G-Advanced introduces new architectural tools, enhanced performance features, and a foundation for emerging applications such as industrial automation, extended reality (XR), artificial-intelligence-native services, and extended coverage through satellites.

For engineers, it’s a chance to rethink how wireless infrastructure interacts with connected devices—not just for throughput but for awareness, responsiveness, and reliability.

Release 18 sets the baseline for 5G-Advanced

3GPP Release 18, finalized in 2024, officially began the 5G-Advanced era. It builds on the existing 5G New Radio framework while introducing updates in several critical areas:

• Enhanced uplink performance, including supplementary uplink and carrier aggregation
• Energy-efficiency improvements, particularly for massive MIMO deployments
• Expanded support for reduced-capability devices
• Integration of AI/machine-learning inference into network management functions
• Initial standardization for integrated sensing and communication (ISAC)

Release 19, currently in progress and slated for a December 2025 release, will extend this work with refinements in deterministic networking, satellite interoperability, and deeper AI integration. Together, these releases reshape how the network behaves, making it more adaptable and capable of real-time decision-making.

Integrated sensing adds spatial intelligence

One of the most novel additions in 5G-Advanced is ISAC. This capability allows 5G base stations to estimate object presence and environmental motion using reflected radio signals, effectively turning standard wireless infrastructure into a type of radar system.

In practice, ISAC is already being explored in traffic management for detecting vehicles or pedestrians at intersections, in smart factories where spatial awareness helps coordinate autonomous robots, and in emergency scenarios for locating individuals in smoke-obscured or debris-filled areas. These use cases illustrate how sensing data, when layered onto existing communications signals, creates a dual-purpose system without requiring dedicated sensing hardware.

From an engineering perspective, ISAC opens new design opportunities—and challenges. Dual-use radios must optimize waveform design for both tasks, and network-side processing will require fast distributed algorithms capable of fusing sensing with mobility data in real time. As ISAC matures, it could enable a class of location-aware, situationally adaptive services across urban infrastructure, industrial automation, and public safety networks.

AI at the edge: a distributed intelligence model

5G-Advanced also formalizes the use of AI/ML as core system functions. In Release 18, standardized interfaces support:

• AI model training and inference within the radio access network and core
• Real-time data collection from radio and service layers
• AI-driven predictions for mobility, resource scheduling, and interference mitigation

This allows the network to self-optimize in response to shifting conditions. For example, AI-assisted beam management can enhance signal quality in dense urban environments, while predictive scheduling reduces latency for applications such as XR or autonomous systems.

Crucially, AI is being extended to the edge. Rather than sending raw sensor or traffic data to the cloud, edge platforms can now process, interpret, and act on data locally. This supports latency-sensitive applications such as autonomous robotics or augmented-reality headsets while also reducing backhaul load. Edge-based anomaly detection, traffic forecasting, and congestion mitigation are already being trialed in early 5G-Advanced deployments.

Looking ahead, Release 19 will bring deeper AI/ML integration, including energy-efficiency optimizations, adaptive quality-of-service (QoS) enforcement, and cross-layer coordination—critical for supporting applications that need deterministic performance.

Satellite integration closes the coverage gap

5G-Advanced also marks a turning point for non-terrestrial networks (NTNs). Where satellites once operated separately from mobile networks, current standards are integrating LEO satellite connectivity directly into 5G architectures.

Through ongoing 3GPP work (notably in Releases 17–19), the industry is standardizing how terrestrial and satellite systems interoperate, including:

• Common radio interfaces
• Shared mobility management and QoS enforcement
• Support for direct-to-device communication with standard smartphones

This opens the door for resilient, global coverage—especially in rural, maritime, or emergency scenarios where terrestrial infrastructure is limited or vulnerable.

For designers and systems engineers, this means that hybrid connectivity architectures are becoming technically and commercially viable. Applications in agriculture, energy, defense, and transportation may now be served by a single, 5G-based system that spans land, air, and sea.

Looking ahead: foundational work for 6G

5G-Advanced is not just a stopgap between 5G and 6G. Many of the capabilities explored in Releases 18 and 19, such as ISAC, AI-native orchestration, and spectrum flexibility, are forming the blueprint for future 6G systems.

Key trends expected to influence 6G include:

• Sub-terahertz frequency operation
• Native support for joint communication and sensing
• Deep integration of AI at all layers
• Precision positioning and timing services
• Support for extreme-scale IoT and holographic media

In this context, work on 5G-Advanced can be viewed as a validation layer. Engineers building today’s infrastructure are also laying technical and architectural groundwork for the 2030s.

Implications for system and device design

As 5G-Advanced capabilities become commercialized, they bring new design considerations across both hardware and software domains. Processing at the edge will play a larger role, driving demand for greater compute power, AI acceleration, and real-time I/O capacity within base stations and access points. Sensor fusion architectures may need to evolve to incorporate environmental data generated by the network itself, reshaping how autonomy is implemented in vehicles, drones, and robotics systems.

At the RF level, antenna design will need to support dual-purpose configurations that accommodate both communication and sensing, particularly for ISAC and NTN applications. Power optimization will also require closer integration between AI-managed network behavior and the energy states of connected devices, ensuring efficiency across dynamically changing workloads.

On the software side, developers will increasingly take advantage of real-time network APIs, dynamic slicing, and AI-enriched analytics to create services tailored to specific application needs, whether in industrial automation, XR, or other emerging verticals.

Meanwhile, software engineers and application developers can begin to leverage real-time network APIs, network slicing, and predictive analytics to offer differentiated services.

Where we go from here

The wireless industry is moving toward a new model, where connectivity, computing, and sensing coexist in a tightly coupled architecture. 5G-Advanced is enabling that shift with tangible, standards-backed updates in sensing, AI integration, and global coverage.

For engineers, the implications go beyond speed or bandwidth. The network itself is becoming context-aware, self-optimizing, and more responsive to application demands. That’s not just a generational upgrade; it’s a new design paradigm.

About the author

Viet Nguyen is president of 5G Americas, a leading industry trade association advancing 5G, 5G-Advanced, and the evolution toward 6G in North America. With over two decades of experience in telecommunications, enterprise technology, public affairs, and media strategy, he has held leadership roles at Microsoft, T-Mobile USA, and Spectrum Networks. Prior to his current role, he served as vice president of public relations and technology at 5G Americas, where he led strategic communications and industry engagement. He holds a B.A. in political science from the University of Washington.

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