DIGITALISATION
What are the standards for 5G private networks? by Jessy Cavazos, 5G industry Solutions Manager, Keysight Technologies Industry, as a whole, and the manufacturing sector, in particular, will benefit from their development. 5G’s foray into the industrial world starts with the development of standards. 5G private networks also require government involvement for spectrum as well as civilian and military applications, and involvement from industry, for trials, testbeds and ecosystem solutions. Many industry organisations participate in the development of standards for 5G private networks. The most notable ones are the 3rd Generation Partnership Project (3GPP) and the 5G Alliance for Connected Industries and Automation (5G-ACIA).
3GPP Standards The first 5G standard release (3GPP Release 15) mainly focused on consumer services. The most recent release (Release 16) and the upcoming ones (Figure 1) offer
Figure 1: 3GPP Standards timeline. 22
THE SINGAPORE ENGINEER April 2022
specific capabilities for the industrial space. Release 16 introduces significant enhancements to achieve low latency, including the following: • Uplink pre-emption indication, where the gNodeB (gNB) can tell enhanced mobile broadband (eMBB) user equipment (UE) to stop previously scheduled uplink transmission and clear the channel for higher-priority, low-latency traffic from other UEs. • Improvements to physical uplink shared channel (PUSCH) repetitions. • Improvements for uplink grantfree transmission to allow UEs to send data sooner. • Uplink control information (UCI)
Ms Jessy Cavazos
changes to introduce the concept of traffic priority. Release 17 increases the integration of 5G with time-sensitive networks (TSN). This release will also introduce features that improve 5G positioning and reduce latency, which are critical capabilities for factory automation and remote control applications. Release 18 will be the first release to officially fall under the 3GPP ‘5G Advanced’ umbrella. This release will feature significant enhancements for network intelligence, including the implementation of machine learning (ML) techniques at different levels in the network. Artificial intelligence (AI) enhancements will be essential for more demanding industrial use cases.
