5G QoS for Industrial Automation

Last updated on Mar 16, 2023

Introduction:

5G or Fifth Generation mobile networks are designed to deliver higher data speeds, lower latency, and higher network capacity than the previous generations of mobile networks. The development of 5G has been driven by the need to provide better connectivity for a wide range of applications, including industrial automation. In industrial automation, 5G is expected to play a key role in enabling the deployment of advanced technologies such as the Industrial Internet of Things (IIoT) and autonomous robots.

One of the key challenges in using 5G for industrial automation is the need to ensure Quality of Service (QoS) for critical applications. QoS refers to the ability of a network to deliver a certain level of service to different applications or users. In industrial automation, QoS is critical because many applications, such as real-time control of machines, require low latency and high reliability. This article will discuss the technical aspects of 5G QoS for industrial automation.

5G QoS Framework:

The 5G QoS framework is designed to provide different levels of service to different applications or users. The 5G QoS framework is based on three main components: QoS flows, QoS classes, and QoS parameters.

QoS Flows:

QoS flows are used to identify different data streams and to assign different QoS parameters to these data streams. Each QoS flow is associated with a particular application or user and is identified by a unique flow identifier (FlowID). QoS flows are used to differentiate between different data streams and to ensure that each data stream receives the appropriate level of service.

QoS Classes:

QoS classes are used to define the different levels of service that can be provided to different applications or users. Each QoS class is associated with a particular set of QoS parameters that define the level of service that will be provided to the data streams associated with that QoS class. The different QoS classes that are defined in 5G are:

Conversational Class: This QoS class is designed to provide real-time, low-latency communication for applications such as voice and video calling.
Streaming Class: This QoS class is designed to provide high-throughput, low-latency communication for applications such as streaming video and audio.
Interactive Class: This QoS class is designed to provide low-latency communication for applications such as gaming and virtual reality.
Background Class: This QoS class is designed to provide low-priority communication for applications such as software updates and backups.

QoS Parameters:

QoS parameters are used to define the specific level of service that will be provided to a particular data stream. The QoS parameters that are used in 5G are:

Latency: Latency is the time delay between the transmission of a data packet and the receipt of the packet at its destination. Low latency is critical for applications such as real-time control of machines.
Reliability: Reliability refers to the ability of a network to deliver data packets without errors or losses. High reliability is critical for applications that require the delivery of critical data.
Throughput: Throughput is the amount of data that can be transmitted over a network in a given period of time. High throughput is critical for applications that require the transmission of large amounts of data.
Jitter: Jitter is the variation in the delay between the transmission of data packets. Low jitter is critical for applications that require low-latency communication.

5G QoS for Industrial Automation:

In industrial automation, 5G is expected to play a key role in enabling the deployment of advanced technologies such as the Industrial Internet of Things (IIoT) and autonomous robots. These applications require low latency, high reliability, and high throughput communication. The 5G QoS framework is well-suited to meet these requirements.

One of the key advantages of 5G is its ability to support network slicing, which allows operators to create dedicated virtual networks for different applications or use cases. This means that operators can allocate resources such as bandwidth, latency, and reliability to specific applications or users based on their requirements. For example, an operator could create a dedicated network slice for a factory automation system that requires low-latency communication and high reliability, while another network slice could be created for a surveillance system that requires high throughput but can tolerate higher latency.

The 5G QoS framework allows operators to provide different levels of service to different applications or users within each network slice. For example, within the network slice dedicated to factory automation, a conversational class QoS could be assigned to real-time control applications, while a streaming class QoS could be assigned to video monitoring applications.

In addition, 5G provides support for edge computing, which allows data processing and analysis to be performed closer to the source of the data. This reduces latency and enables real-time decision-making. Edge computing is particularly useful for industrial automation applications where real-time control is critical.

5G QoS for industrial automation can be further enhanced by the use of Quality of Experience (QoE) monitoring. QoE monitoring involves measuring the perceived quality of the service by the end-users. QoE monitoring can provide valuable feedback on the performance of the network and allow operators to identify and resolve issues before they impact the end-users.

Challenges in implementing 5G QoS for Industrial Automation:

While 5G QoS has the potential to greatly enhance industrial automation, there are several challenges that need to be addressed. One of the main challenges is the need for a common standard for QoS that can be used across different applications and industries. While the 5G QoS framework provides a good starting point, there is a need for a common language and understanding of QoS requirements and parameters.

Another challenge is the need for interoperability between different vendors and equipment. Industrial automation systems are often comprised of equipment and devices from multiple vendors, which can lead to compatibility issues. Interoperability testing and certification programs can help address this issue.

Finally, there is a need for security and privacy measures to be incorporated into 5G QoS for industrial automation. Industrial automation systems often contain sensitive and critical data, which needs to be protected from cyber-attacks and unauthorized access.

Conclusion:

5G QoS provides a powerful framework for enabling industrial automation applications. The ability to allocate resources and provide different levels of service to different applications and users is critical for industrial automation systems that require low latency, high reliability, and high throughput communication. The implementation of 5G QoS for industrial automation will require a common standard, interoperability testing, and security and privacy measures. With the proper implementation, 5G QoS has the potential to greatly enhance industrial automation and enable the deployment of advanced technologies such as the Industrial Internet of Things (IIoT) and autonomous robots.