Wireless Systems for Edge
Summary of Chapter 3 of the State of the Edge Report 2026 by Salih Ergüt, Chief Innovation & Strategy Officer at OREDATA.
This blog is part of a series highlighting key insights from the State of the Edge Report 2026. Each post explores one chapter from the report and provides a preview of the latest thinking from industry experts. To dive deeper into the trends, architectures, and recommendations shaping the future of edge computing, download the full report.
As edge computing continues to expand, wireless connectivity is becoming just as critical as compute infrastructure itself. Chapter 3 of the State of the Edge Report 2026 examines how advancements in 5G Standalone, Open RAN, Edge AI, private wireless networks, and satellite communications are enabling a new generation of intelligent edge applications.
The Wireless Foundation for Edge Computing
The chapter explains that the wireless industry is entering a new phase of maturity. Rather than introducing entirely new technologies, recent developments are focused on scaling proven innovations into production.
Several trends are driving this evolution:
- 5G Standalone (SA) networks are moving from deployment into widespread commercial operation.
- Open RAN is transitioning from proof-of-concept to real-world production deployments.
- Edge AI is transforming edge computing into an intelligence platform capable of local decision making.
- Non-Terrestrial Networks (NTNs) are extending wireless connectivity beyond traditional terrestrial infrastructure.
- RedCap is bringing cost-effective 5G connectivity to a broader range of IoT devices.
Together, these technologies are expanding what organizations can deploy at the edge while reducing dependence on centralized cloud infrastructure.
5G Standalone Unlocks the Full Potential of Edge
One of the chapter’s biggest themes is the importance of 5G Standalone architecture.
Unlike earlier 5G deployments that relied on existing 4G cores, Standalone networks are built entirely on cloud-native 5G infrastructure. This enables capabilities that were difficult or impossible with previous generations, including:
- Ultra-low latency communications
- Network slicing for different application requirements
- Cloud-native network automation
- Greater scalability for edge workloads
These capabilities are becoming essential for applications such as industrial automation, autonomous vehicles, robotics, and real-time analytics, where milliseconds matter.
Open RAN Becomes Commercial Reality
The chapter also explores how Open RAN has evolved from an industry vision into commercial deployment.
Instead of relying on a single vendor for radios, baseband equipment, and software, Open RAN enables operators to mix and match components from multiple vendors through standardized interfaces.
Major telecommunications providers are now deploying Open RAN in production environments, demonstrating that multi-vendor wireless networks are becoming operationally viable.
At the same time, the chapter notes that interoperability, testing, security, and workforce skills remain important challenges as deployments continue to scale.
Wireless Networks Bring Compute Closer to the Edge
Wireless infrastructure is no longer simply responsible for connecting devices.
Technologies such as Multi-access Edge Computing (MEC) integrate compute resources directly into mobile networks, allowing applications to process data much closer to where it is generated.
Combined with private 5G networks, organizations gain greater control over latency, reliability, and data residency.
Manufacturing provides some of the strongest examples of this shift. Private wireless networks are supporting applications including:
- Autonomous mobile robots
- Computer vision quality inspection
- Predictive maintenance
- Worker safety monitoring
Processing these workloads locally enables faster response times while reducing reliance on distant cloud infrastructure.
Edge AI and Intelligent Connectivity
The chapter highlights how AI is accelerating demand for more capable wireless infrastructure.
Modern edge AI applications require networks that can deliver reliable, low-latency connectivity while supporting local inference on increasingly powerful hardware.
Real-world deployments already demonstrate this shift, with organizations using edge AI for quality control, predictive maintenance, and industrial automation.
Rather than simply transporting data, wireless networks are becoming active participants in intelligent edge systems.
Looking Beyond Terrestrial Networks
Wireless innovation is extending beyond traditional cellular infrastructure.
The chapter explores the growing role of Non-Terrestrial Networks (NTNs), including satellite-based connectivity that can bring edge computing to remote and underserved locations.
It also highlights RedCap (Reduced Capability), a streamlined version of 5G designed for IoT devices that need greater performance than LPWAN technologies without the complexity and cost of full-featured 5G.
Together, these technologies broaden the range of environments where intelligent edge applications can be deployed.
Key Takeaway
Wireless connectivity has become a foundational layer of modern edge computing.
As 5G Standalone networks mature, Open RAN deployments expand, private wireless adoption accelerates, and Edge AI becomes more widespread, organizations can build edge infrastructure that is faster, more intelligent, and more resilient.
While challenges remain around interoperability, security, and operational complexity, the chapter concludes that wireless systems have moved beyond experimentation and are now enabling production-scale edge deployments across industries.
Read the Full Report
This chapter is just one part of the State of the Edge Report 2026, which brings together insights from industry leaders on the technologies, architectures, and trends shaping the future of edge computing.
Download the full report to explore all nine chapters and learn how organizations are building the next generation of edge infrastructure.
