Network Slicing in NG RAN

I have been asked to explain in a nutshell how network slicing works in NG RAN. The most important facts you will find in the infographic below.

A network slice is virtual part of a network that offers full end-to-end connectivity for particular services and - optionally - for tenants. A tenant is a 3rd-party company that rents a virtual part of a public mobile operator's network. This allows the tenant to run its own private nation-wide mobile network without owning any hardware.

The network slicing is enabled by virtualization and all network functions can be divided into different slices as well. Thus, you can find in the figure the User Plane Function (UPF), gNB Central Unit for User Plane (gNB-CU UP) and gNB Distributed Unit (gNB-DU) all sliced.

It is also possible that a network function is dedicated for a particular network slice as in case of (gNB-) CU UP 2. 

In general - and this is the benefit of the cloudification - the NG RAN is a highly dynamic environment in which additional NW functions can be added (and later released) whenever this is necessary. Mostly this will be triggered by the load on CPU and memory resources. Here comes the automation into the games that deals in large parts with load balancing. Ideally automation enables a zero-touch network management. 

(click to enlarge)

However, the most precious of all RAN resources, the radio resources, cannot be administrated so flexibly and easily. Indeed, there are several automation instances that deal with radio resource management. Open RAN Alliance has defined the RAN Intelligent Controller (RIC) that is split into the Near-Realtime-RIC (RT RIC) that shall operate with a latency between 10 and 500 ms while the Non-Realtime RIC (NRT RIC) deals with non-time critical task, e.g. typical SON functions like Automatic Neighbor Reporting (ANR).

While the RIC can deal with a lot of problems there is one thing it cannot do: adding physical layer radio resources on demand. The physical resources are limited by the number of remote radio heads/antennas and as long as we have only static beamforming the physical resources covering a geographical sector are also limited by hardware and their distribution must be carefully planned. Thus, I think it is fair to say that the RIC (or a similar proprietary automation function) has to deal with the most complex situations in the RAN.

Radio resources can also be sliced in different ways. My figure illustrates a kind of slicing on the physical layer where different physical resource blocks (PRB) are allocated to different network slices. 

However, this is not the only way how the resources of a cell or a beam can be sliced. Beside a split of PRBs it is also possible to slice on the MAC layer where logical channels (slice-specific radio bearers) are mapped onto transport channels or on PDPC layer as it was described and demonstrated by the 5G NORMA project (Chapter 2.1, page 17 ff.).

What in the end will be implemented by the RAN equipment manufacturers is a question I that cannot answer today. 

Reducing 5G Device Power Consumption Using Connected-mode Discontinuous Reception (C-DRX)

Back in 2019, when we were still participating in physical event, I heard Sang-Hoon Park, ESVP, Head of Regional Network O&M Headquarter, KT talk about 'KT’s journey to large-scale 5G rollout' at Total Telecom Congress.

Interesting nugget from KT about battery life. 63% of users care about battery life but only 19% about design. Also the battery capacity has evolved significantly over generations. Finally C-DRX will play a big role in 5G battery saving @totaltelecom #TTCongress pic.twitter.com/665sokRH0T

— 3G4G (@3g4gUK) October 30, 2019

South Korea is blessed with three highly competitive MNOs and due to this, the government asked them to launch their 5G networks at the same time in 2018. I have also blogged about how KT is working on reducing the latency of their network here.

Anyway, as you can see in the picture above, using Connected-mode Discontinuous Reception (C-DRX), KT was able to show huge power saving in the 5G Samsung smartphone. They also made a video embedded below:

KT has some more details from their blog post back in 2019 here. Also some more details on RayCat here. Both the sites are in Korean but you can use Google translate to get more details.

What is KT battery saving technology (C-DRX)?

KT's'battery saving technology' is shortened to'Connected Mode Discontinuous Reception' and is called C-DRX. In simple terms, it is one of the technologies that reduces battery usage by periodically switching the communication function of a smartphone to a low power mode while data is connected.

In CDRX technology, the base station and the terminal share CDRX information through RRC setting and reconfiguration, so when there is no packet transmission/reception by the terminal, the terminal transmission/reception terminal can be turned off to reduce battery consumption, and the CDRX setting is optimized to reduce the user's battery consumption. It is possible to increase the available time for related applications.

In order to reduce the battery consumption of the terminal, it is a technology that controls the PDCCH monitoring activity, which is a downlink control channel related to the terminal identifier, through RRC. The base station controls the CDRX through RRC, and how the communication company optimizes and applies this was a big task. Is the first in Korea to optimize this technology and apply it to the national network.

In simple terms, the smartphone is not using communication, but it turns off the power completely and enters the standby state to reduce power consumption. When not in use, it completely turns off the power wasted in transmitting and receiving even during the standby time, thus extending the user's smartphone usage time.

As can be seen from the picture above, battery saving technology saves battery by completely turning off the communication function when there is no data or voice call. If the network does not have the battery saving technology applied, it is always connected to the communication network and waits even when not in use. Then, the battery is always connected to the communication function and the battery saving technology overcomes this part.

When Qualcomm announced their Industry’s First Mobile Platform with Integrated 5G back in 2019, the press release said:

The new integrated Snapdragon 5G mobile platform features Qualcomm® 5G PowerSave technology to enable smartphones with the battery life users expect today. Qualcomm 5G PowerSave builds on connected-mode discontinuous reception (C-DRX, a feature in 3GPP specifications) along with additional techniques from Qualcomm Technologies to enhance battery life in 5G mobile devices – making it comparable to that of Gigabit LTE devices today. Qualcomm 5G PowerSave is also supported in the Snapdragon X50 and X55 5G modems, which are expected to power the first waves of 5G mobile devices introduced this year.

The picture is from the slide deck here. See links in further reading below to learn more about this feature.

Further Reading:

• All about Wired and Wireless Technology: LTE Connected Mode DRX (link)
• Netmanias: Future LTE Designed by SK Telecom: ​(2) Application of C-DRX, July 2017 (link)
• Ericsson: A technical look at 5G mobile device energy efficiency, Feb 2020 (link)
• ZTE via IEEE Access: Power Saving Techniques for 5G and Beyond, July 2020 (link)

Related Posts:

• Operator Watch Blog: All three mobile network operators in South Korea launched 5G on Dec 1, 2018
• Operator Watch Blog: How is KT Reducing the Latency of their 5G Network 

Open RAN Explanation, Videos, White papers and Other Resources

Couple of years back, just before MWC 2019, we made what I would like to think of as the first proper explanation of Open RAN. I posted it on this blog here and the video has been viewed nearly 45,000 times. At that time, the concept of Open RAN was still quite new and in my day job with Parallel Wireless*, I was spending quite some time explaining what it really means.

Anyway, I think it made the concept of Open RAN so easy to understand that I have seen tens, if not hundreds, of people copy it, but only a few kind people give credit. 

With the Telecom Infra Project (TIP) and O-RAN driving the ecosystem further, I along with my Parallel Wireless colleagues, created a series of videos to explain the concept a bit more in detail. As expected, the introductory videos have been extremely popular while the others have been reasonably popular as well. The concept from these videos have been copied even far and wider than the original one. 

Embedded below is the playlist of all the videos (6 currently but 1 more in works):

In addition to these, I maintain a list of Open RAN whitepapers (publicly available without registration), some good articles, etc. on the 3G4G website here. I try and update the site on a regular basis so feel free to put any resources in the comments of this post and I will add them on the site during the next update.

Related Posts:

• The 3G4G Blog: O-RAN Introduction for Beginners
• The 3G4G Blog: A quick tutorial on Open RAN, vRAN & White Box RAN
• 3G4G: Open RAN, OpenRAN and O-RAN
• Telecoms Infrastructure Blog: Small Cells World Summit Open RAN Webinar
• The 3G4G Blog: From traditional RAN to Open RAN - O-RAN: Goals and Challenges
• Telecoms Infrastructure Blog: NTT Docomo's 5G Network is based on 'Open RAN' Principles 

*Full Disclosure: I work for Parallel Wireless as a Senior Director, Technology & Innovation Strategy. This blog is maintained in my personal capacity and expresses my own views, not the views of my employer or anyone else. Anyone who knows me well would know this. 

Free 6G Training

Last year we announced the launch of Free 5G Training. It was successful beyond our imagination. While we have just over 1,300 Twitter followers, on LinkedIn, we have over 30,000. The 5G for Absolute Beginners Udemy course already has over 6,000 students. This was a good enough motivation for us to launch a 6G equivalent with world's first 6G training course.

Back in November, we soft-launched the Free 6G Training website/blog along with Twitter and LinkedIn. The initial engagement and following are already very encouraging. 

We also created 'An Introduction to 6G Training Course' here. 6G Candidate technologies, that require most details and is the main area of focus for 6G will be added as and when I find time and have enough material.

There is also a new 6G Wireless R&D LinkedIn group that has been started to share information and discuss doubts, etc. I am hoping many people will be able to join.

If you are a 6G expert or researcher or have ideas on how I can do better or want to contribute with articles, presentations, videos, etc., please feel free to get in touch on LinkedIn.

One final thing, along with all this, the 3G4G page has a section on '6G and Beyond-5G Wireless Technology'. I add links to all publicly available whitepapers and other good material out there. 

It may also be useful to know that the 3G4G page has a search box on top that searches across all our channels and can be helpful in finding information on any mobile technology related topic.

NWDAF in 3GPP Release-16 and Release-17

We looked at Network Data Analytics Function, NWDAF, in detail here. While the 3GPP Release-16 work just starting back then, we have now completed Rel-16 and looking at Release 17. 

The 5G Core (5GC) supports the application of analytics to provide Intelligent Automation of the network, In Rel-16 the set of use cases that are proposed for the NWDAF has been widely expanded. 

In an earlier post, we looked at the ATIS webinar discussing Release-16 & forthcoming features in Rel-17. Puneet Jain, Director of Technical Standards at Intel and 3GPP SA2 Chairman talked briefly about NWDAF. The following is from his talk:

Release-16 provides support for Network Automation and Data Analytics.  Network Data Analytics Function (NWDAF) was defined to provide analytics to 5G Core Network Functions (NFs) and to O&M. It consists of several services that were defined in 3GPP Rel-16 and work is now going in Release 17 to further extend them. 

In release 16 Slice load level related network data analytics and observed service experience related network data analytics were defined. NF load analytics as well Network Performance analytics was also specified. NWDAF provides either statistics or prediction on the load communication and mobility performance in the area of interest. 

Other thing was about the UE related analytics which includes UE mobility analytics, UE communication analytics, Expected UE behavior parameter, Related network data analytics and abnormal behavior related network data analytics.

The NWDAF can also provide user data congestion related analytics. This can be done by one time reporting or continuous reporting in the form of statistics or prediction or both to any other network function. 

QoS sustainability analytics, this is where the consumer of QoS sustainability analytics may request NWDAF analytics information regarding the QoS change statistic for a specific period in the past in a certain area or the likelihood of QoS change for a specific period in future, in certain areas. 

In Release 17, studies are ongoing for network automation phase 2. This includes some leftover from Release 16 such as UE driven analytics, how to ensure that slice SLA is guaranteed and then also new functionality is being discussed that includes things like support for multiple NWDAF instance in one PLMN including hierarchies, how to enable real-time or near-real-time NWDAF communications, how to enable NWDAF assisted user pane optimization and last which is very interesting is about interaction between NWDAF and AI model and training service owned by the operator.

This article on TM Forum talks about NWDAF deployment challenges and recommendations:

To deploy NWDAF, CSPs may encounter these challenges:

• Some network function vendors may not be standards compliant or have interfaces to provide data or receive analytics services.
• Integrating NWDAF with existing analytics applications until a 4G network is deployed is crucial as aggregated network data is needed to make decisions for centralized analytics use cases.
• Many CSPs have different analytics nodes deployed for various use cases like revenue assurance, subscriber/marketing analytics and subscriber experience/network management. Making these all integrated into one analytics node also serving NWDAF use cases is key to deriving better insights and value out of network data.
• Ensuring the analytics function deployed is integrated to derive value (e.g., with orchestrator for network automation, BI tools/any UI/email/notification apps for reporting).

Here are some ways you can overcome these challenges and deploy efficient next-generation analytics with NWDAF:

• Mandate a distributed architecture for analytics too, this reduces network bandwidth overhead due to analytics and helps real-time use cases by design.
• Ensure RFPs and your chosen vendors for network functions have, or plan to have, NWDAF support for collecting and receiving analytics services.
• Look for carrier-grade analytics solutions with five nines SLAs.
• Choose modular analytics systems that can accommodate multiple use cases including NWDAF as apps and support quick development.
• Resource-efficient solutions are critical for on-premise or cloud as they can decrease expenses considerably.
• Storage comes with a cost, store more processed smart data and not more raw big data unless mandated by law.
• In designing an analytics use case, get opinions from both telco and analytics experts, or ideally an expert in both, as they are viewed from different worlds and are evolving a lot.

This is such an important topic that you will hear more about it on this blog and elsewhere.

Related Posts:

• The 3G4G Blog: ATIS Webinar on '5G Standards Developments in 3GPP Release 16 and Beyond'
• The 3G4G Blog: Automating the 5G Core using Machine Learning and Data Analytics
• The 3G4G Blog: Artificial Intelligence - Beyond SON for Autonomous Networks
• 3G4G: 5G Service Based Architecture (SBA)