PDTQ

Planned Data Transfer with QoS requirements

Services →
Introduced in Rel-18

PDTQ is a service feature for scheduling data transfers with guaranteed Quality of Service, allowing the network to plan resource allocation in advance for applications like software updates.

Category
Services
Introduced
Rel-18
Where
Core Network › 5G Core
Specifications
5 specs
PDTQ Description Purpose Related Classification Detected Changes Specifications

Description

Planned Data Transfer with QoS requirements (PDTQ) is a service capability introduced in 3GPP Release 18, defined within the 5G System (5GS) architecture. It enables an Application Function (AF) to request the network to schedule a future data transfer for a User Equipment (UE) with specific QoS guarantees. The core mechanism involves the AF sending a request to the Policy Control Function (PCF) via the Network Exposure Function (NEF), detailing the required data volume, target time window, QoS parameters (such as 5QI, Guaranteed Flow Bit Rate, Maximum Flow Bit Rate), and the destination Data Network Name (DNN). The PCF then authorizes this request and translates it into policy rules for the Session Management Function (SMF). The SMF is responsible for establishing or modifying the appropriate Protocol Data Unit (PDU) Session to fulfill the planned transfer, coordinating with the User Plane Function (UPF) and the Access and Mobility Management Function (AMF) to ensure the UE is reachable and resources are allocated in the Radio Access Network (RAN) at the scheduled time.

Architecturally, PDTQ leverages the existing 5G service-based interfaces, primarily Nnef (between NEF and AF) and Npcf (between NEF and PCF). The PCF uses the Npcf_SMPolicyControl service to provision the authorized policy to the SMF. A key component is the 'Planned Data Transfer' policy control request trigger, which instructs the SMF to prepare for the future session activity. The SMF may pre-establish QoS Flows and notify the RAN via the AMF about the upcoming data transfer, allowing for advanced radio resource scheduling. This proactive orchestration distinguishes PDTQ from reactive QoS mechanisms.

The role of PDTQ in the network is to optimize resource utilization and enhance user experience for non-real-time, bulk data applications. By shifting predictable, large data transfers to off-peak hours or periods of low network congestion, it helps in traffic smoothing and load balancing. It ensures that applications like operating system updates, large file downloads, or media content pre-caching are completed reliably and within a specified time frame without contending with latency-sensitive services like voice or video streaming. This makes it a foundational enabler for efficient network slicing and differentiated service offerings.

Purpose & Motivation

PDTQ was created to address the growing demand for efficient and predictable handling of background data traffic in 5G networks. Prior to its introduction, background data transfers (e.g., software updates, cloud backups) competed for resources with foreground user applications in a best-effort manner, often leading to unpredictable completion times, potential battery drain on the UE due to repeated retries, and congestion during peak hours. Network operators lacked a standardized mechanism to schedule and guarantee QoS for such planned transfers, limiting their ability to manage network load proactively.

The historical context stems from the evolution of smart devices and IoT, which generate significant amounts of deferrable data. The motivation for PDTQ was to provide a standardized interface for over-the-top (OTT) application providers and enterprise services to negotiate guaranteed data delivery slots with the mobile network. This solves the problem of inefficient 'background' data handling, transforming it into a 'planned' network-managed service. It addresses limitations of previous approaches like basic QoS Class Identifiers (QCIs/5QIs) applied reactively, which could not account for future time-based scheduling, and proprietary solutions that lacked interoperability.

Ultimately, PDTQ enables new business models and service level agreements (SLAs) for scheduled data delivery. It allows operators to offer premium 'assured delivery' services to content providers and enterprises, improving network efficiency through traffic shaping and creating new revenue streams. It is a key step towards making the 5G network a more intelligent and programmable platform for diverse data services.

Classification

Part of5QI
Related approachesNEF

Release Timeline

Detected Changes Across Releases

from 3GPP Change Requests

Specific changes extracted from the „Change history“ tables of 3GPP specifications (18 CRs across 3 releases). Complements the general historical overview above with the evidence-based evolution of this function.

Rel-18 14 changes

In Release 18, the PDTQ (Planned Data Transfer with QoS requirements) function was enhanced with the introduction of a formal PDTQ policy negotiation procedure and a corresponding PDTQ warning notification procedure for policy re-negotiation. It also explicitly integrated "DN Performance Analytics" as an input for the PCF to calculate PDTQ policies, alongside existing "Network Performance" analytics. Furthermore, the release specified the storage and management of PDTQ policy data in the UDR and introduced service operations like Npcf_PDTQPolicyControl_Create, while also addressing error handling in roaming scenarios.

  • DN Performance Analytics usage in PDTQ policy TS 23.503CR0799
  • Updates on PDTQ policy TS 23.503CR1009
  • Support of PDTQ Policy Negotiation procedure TS 29.513CR0458
  • Support of PDTQ warning notification procedure TS 29.513CR0459
  • Update the procedures for PDTQ policy negotiation and warning notification TS 29.513CR0487
  • Resolve the Editor's Note for PDTQ warning notification procedure TS 29.513CR0524

+ 8 more changes

Rel-19 3 changes

In Release 19, the PDTQ (Planned Data Transfer with QoS requirements) function introduced clarifications and corrections to its procedures, specifically for PDTQ selection and resource management. The enhancements refined how the PCF uses analytics on "Network Performance" or "DN Performance" from the NWDAF to determine and re-negotiate candidate PDTQ policies with the AF. This included improved handling of policy updates and notifications when network conditions change, based on the AF's acceptance of re-negotiation during the initial request.

  • Clarification on PDTQ selection procedures TS 29.543CR0010
  • PDTQ Corrections TS 29.519CR0642
  • PDTQ Resource Management corrections TS 29.543CR0014
Rel-20 1 change

In Release 20, the PDTQ (Planned Data Transfer with QoS requirements) function was newly introduced as a standardized capability. This allows an Application Function (AF) to request, via the NEF and PCF, a negotiated time window for data transfer with specific QoS guarantees, with policies informed by network analytics. The release also defined procedures for policy re-negotiation and integrated PDTQ policy control as part of new mechanisms for network energy saving.

  • Adding BDT, PDTQ and UE policy control for network energy saving TS 23.503CR1612

Explore further

Broader topics and technologies where PDTQ plays a role.

Defining Specifications

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

SpecificationTitleRelease
TS 23.503 vk00 5G Policy and Charging Control Framework Rel-20
TR 26.927 vj00 AI/ML in 5G Media Services Study Rel-19
TS 29.513 vj40 5G PCC Signalling Flows & QoS Mapping Rel-19
TS 29.519 vj40 UDR Usage for Policy & Exposure Data Rel-19
TS 29.543 vj20 5G Data Transfer Policy Control Services Stage 3 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.