CPCN

Control Plane data transfer Charging Node

Management →
Introduced in Rel-17

CPCN is a charging node that collects and processes charging data for control plane data transfers via nodes like the MME and SCEF, enabling accurate billing for services such as IoT data delivery.

Category
Management
Introduced
Rel-17
Where
Core Network › 5G Core
Specifications
3 specs
CPCN Description Purpose Related Classification Specifications

Description

The Control Plane data transfer Charging Node (CPCN) is a specialized charging function introduced in 3GPP Release 17 to handle charging for data transfers that occur over the control plane rather than the traditional user plane. In 3GPP networks, certain services—particularly IoT applications and non-IP data delivery (NIDD)—leverage the control plane for small, infrequent data transmissions to optimize network efficiency and device battery life. The CPCN collects, processes, and forwards charging data records (CDRs) generated by network nodes involved in these control plane data transfers, specifically the Mobility Management Entity (MME), Service Capability Exposure Function (SCEF), and Interworking SCEF (IWK-SCEF).

Architecturally, the CPCN operates within the charging system framework defined in 3GPP specifications, interfacing with network functions via standardized reference points. It receives charging events and session information from MME, SCEF, and IWK-SCEF through the Rf (offline charging) or Ro (online charging) interfaces, depending on the deployment scenario. The CPCN aggregates this data, applies charging policies based on subscriber profiles, service types, and data usage, and generates formatted CDRs for billing systems. It supports both event-based charging (for individual transactions) and session-based charging (for prolonged control plane data sessions), ensuring flexibility for diverse IoT service models.

Key components of the CPCN include the charging trigger function, which detects control plane data transfer events; the charging data processing engine, which applies tariff rules and correlates events from multiple nodes; and the CDR generation module, which produces standards-compliant records for downstream billing. The CPCN also integrates with policy control functions to enforce spending limits and real-time charging controls. Its role is critical in monetizing control plane data services, providing operators with detailed visibility into resource usage for IoT deployments, and ensuring regulatory compliance for charging accuracy.

In operation, when an IoT device initiates a control plane data transfer—for example, sending sensor data via NIDD—the MME or SCEF involved in the transaction generates charging information, including data volume, timestamps, device identifier, and service parameters. This information is sent to the CPCN, which validates the data against subscriber policies, calculates charges based on configured tariffs, and creates a CDR. For online charging, the CPCN may interact with the Online Charging System (OCS) to authorize the transaction in real-time before allowing the data transfer to proceed. This ensures prepaid subscribers do not exceed their limits and enables immediate billing for pay-as-you-go IoT services.

Purpose & Motivation

The CPCN was created to address the charging challenges introduced by control plane data transfer mechanisms in 3GPP networks, particularly for IoT and machine-type communication (MTC) services. Prior to its introduction, charging for data transmitted over the control plane was handled inconsistently or as part of general packet data charging, which lacked the granularity and accuracy needed for IoT-specific billing models. Traditional charging systems were optimized for user plane data (e.g., smartphone internet browsing) and struggled to capture the unique characteristics of control plane data transfers, such as small message sizes, infrequent transmission patterns, and non-IP protocols.

Historically, as 3GPP evolved to support massive IoT deployments in Releases 13-16, features like Control Plane CIoT EPS Optimization and NIDD became essential for efficient IoT communication. However, the charging architecture lagged behind, creating a gap in monetization capabilities. Operators needed a way to bill for these services accurately, whether based on message count, data volume, or event-based triggers. The CPCN fills this gap by providing a dedicated charging node that understands the specifics of control plane data transfers, enabling new revenue streams for IoT services while ensuring fair usage tracking.

The CPCN solves several limitations of previous approaches: it separates control plane charging from user plane charging, allowing tailored tariff models; it supports charging for interworking scenarios (via IWK-SCEF) where IoT devices roam between 3GPP and non-3GPP networks; and it enables detailed charging correlation across MME and SCEF nodes, which is crucial for end-to-end service billing. By standardizing CPCN in 3GPP specifications, the industry ensures interoperability between network equipment and billing systems, reducing integration costs and accelerating IoT service deployment.

Classification

Part ofSCEF
Related approachesIWK-SCEF

Evolution Across Releases

Rel-17 Initial

Introduced CPCN as a dedicated charging node for control plane data transfers. Defined initial architecture in TS 28.816, charging parameters in TS 32.253, and charging scenarios in TS 32.298. Enabled charging for data transmitted via MME, SCEF, and IWK-SCEF, supporting IoT services like NIDD and CIoT EPS optimization. Established interfaces with network functions and billing systems.

Explore further

Broader topics and technologies where CPCN plays a role.

Defining Specifications

3GPP specifications that define or reference CPCN, with the latest known release. Sourced from the 3GPP document catalog — see methodology.

SpecificationTitleRelease
TR 28.816 vh00 Charging for 5G Cellular IoT Rel-17
TS 32.253 vj00 Charging for Control Plane Data Transfer Rel-19
TS 32.298 vj30 Charging Data Record (CDR) Parameter Specification Rel-19
Patrick Zandl

About the author: Patrick Zandl (b. 1974)

Telecommunications specialist, technology journalist (founder of the Mobil server), and developer who has been running since 2025 — the largest Czech-language resource on AI-assisted programming. Formerly Chief Wizard Architect at Prusa3D and head of development for Turris at CZ.NIC; currently a consultant and instructor on AI implementation in companies.