Why Private Network Assurance
Needs a Holistic Approach

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Private networks have become indispensable for enterprises that require secure, high-performance, and reliable connectivity. According to Analysis Mason, global spending on private LTE and 5G networks is projected to reach $9.2 billion by 2028. However, building and maintaining successful private networks require more than just infrastructure; they demand a holistic approach emphasizing proactive management and complete visibility. There is an old adage that says, “You can’t control what you don’t see,” and it is particularly true in this context. Private network operators need actively managed networks to support the complex requirements of mission-critical operations.

Drivers for Private Networks

The adoption of private networks is driven by a combination of needs: mission-critical system reliability, operational efficiency, and enhanced security.

Mission-Critical Systems: Private networks are essential for industries where uninterrupted service is crucial. For example, an unexpected network outage in large airports that halts communication for just five minutes can result in planes idling on the tarmac, delaying operations and costing millions. In such settings, private networks ensure low latency and high availability, allowing systems like real-time logistics, baggage handling, and ground crew communication to function seamlessly.

Operational Efficiency: Private 5G networks enable real-time data processing, which is essential for the smooth operation of connected devices and automated machinery. Unlike public networks, private 5G networks offer complete control over data routing and resource allocation, making them more suitable for environments with heavy data requirements, such as smart factories. These networks support instantaneous data transfers, enabling quicker decision-making and faster response times, boosting productivity and agility across an enterprise.

Security and Control: Enterprises seeking higher security and data control levels often opt for private networks rather than relying solely on public communication service providers (CSPs). While CSPs can provide reliable and broad coverage, they cannot match, at least for now, the customizable security features of a dedicated network. Private networks allow enterprises to implement advanced security protocols, such as zero-trust architecture and specialized encryption, reducing exposure to potential threats. This capability is vital for industries that handle sensitive data, including healthcare and finance.

Enterprises may choose private networks over public CSP reliance for several reasons:

Custom Network Management: Tailored network settings allow businesses to prioritize and secure mission-critical applications.
Data Sovereignty: Full control over data ensures compliance with industry regulations and minimizes risks of external breaches.
Dedicated Resources: Unlike public networks with shared bandwidth, private networks guarantee dedicated resources, ensuring consistent performance even during peak demand.

The Influence of Standards on Private Networks

The standards set by 3GPP have shaped the evolution of private network capabilities. These standards guide how CSPs and private network operators deploy and enhance their network services.

Current Challenges with Standards

While 3GPP Releases 15 to 17 introduced crucial capabilities like enhanced mobile broadband and basic network slicing, they still need to fully address the specific needs of large-scale, high-stakes private networks. CSPs operating on shared infrastructure face limitations in customization and data isolation, which can hinder their ability to support industries with rigorous performance and security requirements. The introduction of 3GPP Release 18, 5G-Advanced, brings enhancements that significantly improve network capabilities. These include:

Expanded Network Slicing: The ability to allocate specific service levels to different network segments ensures high performance for priority applications.

AI and Machine Learning: Integrating AI and machine learning improves network automation, predictive maintenance, and real-time optimization, enabling more responsive and adaptive network management.