Home5GHow will 3GPP Release 17 and 18 accelerate 5G manufacturing?

How will 3GPP Release 17 and 18 accelerate 5G manufacturing?

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The development of Release 17 and 18 and its potential impact in 5G manufacturing

 

3GPP release 18 represents a major evolution of the 5G System and due to this the 3GPP has decided to brand it as the first release of 5G Advanced. Among other improvements, Rel-18 will include major enhancements in the areas of artificial intelligence (AI) and extended reality that will enable highly intelligent network solutions that can support a wider variety of use cases, some of them in the 5G manufacturing space.

The 3GPP has passed the midpoint in its work on its release 17 (Rel-17) specifications, with plans to publish them at the end of the first quarter of 2022.

Meanwhile, the 3GPP RAN standardization team began discussing the scope of Rel-18 in June 2021 at the 3GPP RAN Rel-18 Workshop and aims for approval of the detailed scope by December 2021. Of the more than 500 proposals that were submitted to the workshop.

The primary aim of Rel-17 is to improve 5GS performance, support new use cases and verticals, and provide ubiquitous connectivity in different deployment conditions and scenarios. Rel-18 introduces further intelligence into wireless networks by implementing machine-learning-based techniques at different levels of the network.

According to a recent article by Ericsson Technology Review, several of the features in Rel-17 are intended to enhance network performance for existing services and use cases, while others address new use cases and deployment options. 5G Advanced will build on Rel-17, providing intelligent network solutions and covering numerous new use cases in addition to previously defined use cases and deployment options.

“One key component of 5G Advanced is the use of artificial intelligence (AI) based on machine learning (ML) techniques. AI/ML is expected to trigger a paradigm shift in future wireless networks. AI/ML-based solutions will be used to introduce intelligent network management and solve multi-dimensional optimization issues with respect to real-time and non-real-time network operation,” Ericsson said.

Rel-17 includes significant enhancements to several radio access network (RAN) functionalities that are already deployed in live New Radio (NR) networks. Rel-17 MIMO enhancements address four areas: beam management; multiple transmission and reception point (mTRP) for ultra-reliable, low-latency communication (URLLC); mTRP for enhanced mobile broadband (eMBB); and TDD and FDD reciprocity.

“In Rel-17, NR positioning is further improved for specific use cases such as factory automation by targeting 20-30cm location accuracy for certain deployments. Rel-17 also introduces further enhancements to latency reduction to enable positioning in time-critical use cases such as remote-control applications,” Ericsson said.

Ericsson noted that 5G Advanced will also introduce more intelligence into wireless networks by including suitable machine-learning-based techniques in different levels of the network. “Future enhancements will also cover a wide variety of new verticals and use cases powered by artificial intelligence/machine learning technologies based on a single platform. As the work progresses, we are committed to ensuring that like 5G, 5G Advanced has the ability to support all use cases from one system design, focusing on forward compatibility and diverse configurability while ensuring maximum simplicity,” the vendor said.

According to a recent article by Antti Toskala, Bell Labs Fellow at Nokia, Rel-18 will provide a foundation for more demanding applications such as truly mobile extended reality services.

“The standard will also inject more intelligence into the network, utilizing machine learning to adapt to its environment. As with previous releases, Release 18 will boost fundamental radio and system performance, but it will also bring mobile broadband to new classes of devices and open 5G to new industries. For instance, 5G-Advanced will connect millions of home automation and industrial sensors to the mobile network and help control power-distribution and rail traffic-management networks,” wrote Toskala.

“Machine learning is also being investigated as a means of improving radio performance. These and many more features have the potential to elevate 5G-Advanced to new levels of system performance and capability, allowing the standard to deliver reliable high-quality services that today can only be supported over fixed connections,” Toskala continued.

 

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