Multi-technology :The future of IoT geolocation

In the big world of IoT, location tracking  is the  next  frontier!. Location tracking for humans is already an integral part of our lives especially for navigation. Traditional technologies enabling this are  not only expensive, they  have technical boundaries preventing scaling. For IoT geolocation to become a true reality, it is inevitable it has to be  extremely accurate, extremely low cost, and extremely low touch. 

Where is the market?

Research and Markets predict revenues from Geo IoT will reach $49 billion by 2021.

Just as location determination has become an essential element of personal communications, so shall presence detection and location-aware technologies be key to the long-term success of the Internet of Things (IoT). Geo IoT will positively impact many industry verticals. – Research and Market report about “Geo IoT Technologies, Services, and Applications Market Outlook: Positioning, Proximity, Location Data and Analytics 2016 – 2021.”

Connecting IoT objects is already a large market growing exponentially with the mix of unlicensed Low-Power Wide Area Network (LPWAN) technologies such as LoRaWAN, and combined more recent introduction of Cellular IoT technologies such as NB-IoT and LTE-M. Adding Geolocation to this introduces a whole range of new applications not possible before. Some of these applications are:

1. Asset Management
2. Fleet Management
3. Anti-theft scooter/bike rental
4. Logistics/parcel bags tracking
5. Worker safety for Oil and Gas
6. Elderly and Disabled care
7. Tracking solution for skiers
8. Pets and Animal tracking

The above applications represent large existing market which can be only be enabled with extremely low cost and low power trackers. This is the reason why LPWAN-enabled geolocation is in fact a separate product category for large existing market.

The challenges involved (Asset tracking as an example case study)

Railway cars, truck trailers, containers: tracking valuable assets on the move is a pain point for most large distributed organizations involved in logistics and supply chain, typically relying on partners such as distributors to correctly register check-in and check-out events. This registration process at specific checkpoints is usually manual, intermittent and subject to human errors.  To tackle this issue, an IoT low power asset tracking system using LPWAN (Low Power Wide Area Network) trackers brings a “timeless” checkpoint solution. Specifically, LoRaWAN™-based trackers, because of their low power, low cost and lightweight infrastructure, provide a first truly reliable tracking solution allowing to reduce downtime during transportation. 

In the logistics sector, many business cases involve additional costs due to inefficient utilization of assets. Transport companies need to invest in freight railway cars, car logistics companies need to invest in truck trailers, and of course there are the standard containers and pallets.

“The profitability of these business cases directly depends on the minimization of asset downtime: every day or hour lost in a warehouse, parking or rail station reduces the number of times the moving asset will generate profit in a year.”

However, measuring this downtime is also a challenge. Traditional solutions involved cellular or satellite trackers, which require significant CAPEX, but perhaps more importantly also ongoing OPEX due to battery replacements and connectivity costs. In some cases, trackers are located in hard to reach areas especially when mounted on railroad cars, or in oil and gas rigs, which makes it very costly to replace batteries especially if there are several hundreds of thousands of trackers deployed in the field. The battery replacement is done by humans and is one of the dominating OPEX factors in overall Total Cost of Ownership ( TCO) of the whole solution. These replacement costs actually made it difficult to justify the mass adoption of conventional geolocation solutions in the logistics sector.

LPWAN trackers: a game changer

LoRaWAN  is LPWAN connectivity standard developed by LoRa Alliance primarily for unlicensed ISM spectrum, to create disruption in both the technology and business models. On the technology front, the main impact is on drastic reduction of power consumption, which reduces battery usage and ultimately also OPEX related to ongoing maintenance. It also creates new opportunities for more dynamic tracking, as communication events are less costly. On the business model side, logistics companies can now trade off between CAPEX and OPEX: most LPWAN systems operate on an unlicensed band, for example the leading LoRaWAN™  technology operates in the 915MHz band in the US, the 868MHz band in Europe and equivalent ISM bands in other parts of the world. This means that logistics companies can invest in their own wireless networks to reduce or eliminate variable connectivity costs.

“The cost of LPWAN radio network gateways has decreased due to higher production volumes and are now affordable even to very small logistic centers, such as a car distributor. “

 Next generation LPWAN trackers

The potential of LPWAN-enabled tracking requires a new generation of hardware. The lower radio frequency power consumption is only a part of a massive effort to decrease overall power consumption of the whole system. This requires developing a multi-technology geolocation tracker platform that can combine GPS, Low-Power GPS, WiFi Sniffing, WiFi fingerprinting and Bluetooth with the goal of reducing power consumption and provide location information opportunistically in variety of scenarios such as (indoor/outdoor, urban/rural, slow/fast moving and so on). 

Another key factor is the usage of LPWAN technologies such as (LoRaWAN, NB-IoT, LTE-M) for transporting geolocation data back to the cloud. This is the key as traditional cellular technologies such as 2G/3G/4G are just too power hungry to meet the target goal of 5-10 year battery lifetime. However, there will be licensed Cellular IoT options based on NB-IoT/LTE-M that will be also be used for some of the applications.

LoRaWAN and Low Power GPS significantly increases battery lifetime

IoT geolocation asset tracking, logistics, rolling stock tracking, containers tracking, trucks tracking, supply chain, internet of things, LoRa

Merging an IoT network solution such as LoRaWAN with  multi-mode geolocation technologies for outdoor and indoor positioning increase by at least a factor of 10 the battery lifetime compared to the standard cellular solution using GSM/AGPS. Source: Actility

The Road Ahead:

The next frontier in IoT geolocation will be two fold. The first will be the multi-technology cloud platform that will combine intelligently Over-The-Top (OTT) geolocation technologies such as GPS, Low-Power GPS, WiFi and Bluetooth with network based TDoA geolocation technologies using LoRaWAN and/or Cellular. This requires close cooperation between public network operators with geolocation service providers.

Webinar: MULTI-TECHNOLOGY IOT GEOLOCATION
The future of IoT geolocation is multi-technology

In order to shed some light on the above mentioned points, we are hosting a webinar that explains where  we will explore the challenges of network-based geolocation and how it can be combined with other geolocation technologies such as GPS, WiFi and Bluetooth. We will explain how multi-technology geolocation differs from traditional cellular+GPS based geolocation, and show how it opens up an entirely new market and product category. We’ll also explore how multi-technology geolocation meets the requirements and use cases for connecting small sensors which are low-cost with very long battery lifetime. A guest speaker from KPN will share selected case studies demonstrating IoT geolocation deployments and discuss real-world experience. The webinar will conclude with outlook for technological evolution in the field, and give an overview of our Location portfolio.

What will you learn from this webinar?

1. What are the market opportunities and use cases enabled by IoT Geolocation?
2. What are the benefits of multi-technology geolocation?
3. What are the benefits of using LPWAN technologies(LoRaWAN, NB-IoT, LTE-M) for connectivity?
4. How LPWAN-enabled Geolocation will evolve in the future?
5. How is Actility building multi-technology geolocation platform?

Follow the link below for registration to the webinar,

https://www.actility.com/event/multi-technology-iot-geolocation-webinar/

For any questions, contact the author below,

https://www.linkedin.com/in/rohit-gupta-2b51503a/

Webinar resources post-event:

Slides

Multi technology geolocation webinar from Actility

Video

5G New Radio Standards and other Presentations

A recent Cambridge Wireless event 'Radio technology for 5G – making it work' was an excellent event where all speakers delivered an interesting and insightful presentation. These presentations are all available to view and download for everyone for a limited time here.

I blogged about the base station antennas last week but there are other couple of presentations that stood out for me.

The first was an excellent presentation from Sylvia Lu from u-Blox, also my fellow CW Board Member. Her talk covered variety of topics including IoT, IIoT, LTE-V2X and Cellular positioning, including 5G NR Positioning Trend. The presentation is embedded below and available to download from Slideshare

Overview of standardisation status and 3GPP technology evolution trend from 3G4G

The other presentation on 5G NR was one from Yinan Qi of Samsung R&D. His presentation looked at variety of topics, mainly Layer 1 including Massive MIMO, Beamforming, Beam Management, Bandwidth Part, Reference Signals, Phase noise, etc. His presentation is embedded below and can be downloaded from SlideShare.

5G NR: Key features and enhancements from 3G4G

Related Posts:

• Base Station Antenna Considerations for 5G
• Introduction to Fixed Wireless Access (FWA)
• 5G Network Architecture Options (Updated)
• Automated 4G / 5G HetNet Design

Base Station Antenna Considerations for 5G

I first mentioned Quintel in this blog three years back for their innovations in 4T8R/8T8R antennas. Since then they have been going strength to strength.

I heard David Barker, CTO of Quintel at Cambridge Wireless event titled "Radio technology for 5G – making it work" talking about the antennas consideration for 5G. There are quite a few important areas in this presentation for consideration. The presentation is embedded below:

Base Station Antenna needs for the 5G RAN from 3G4G

Related Posts:

• Using 8T8R Antennas for TD-LTE
• Antenna evolution: From 4G to 5G
• The Art of Disguising Cellular Antennas
• AT&T Blog: "Providing Connectivity from Inside a Cactus"
• Automated 4G / 5G HetNet Design

End-to-end Network Slicing in 5G

I recently realised that I have never written a post just on Network slicing. So here is one on the topic. So the first question asked is, why do we even need Network Slicing? Alan Carlton from Interdigital wrote a good article on this topic. Below is what I think is interesting:

Network slicing is a specific form of virtualization that allows multiple logical networks to run on top of a shared physical network infrastructure. The key benefit of the network slicing concept is that it provides an end-to-end virtual network encompassing not just networking but compute and storage functions too. The objective is to allow a physical mobile network operator to partition its network resources to allow for very different users, so-called tenants, to multiplex over a single physical infrastructure. The most commonly cited example in 5G discussions is sharing of a given physical network to simultaneously run Internet of Things (IoT), Mobile Broadband (MBB), and very low-latency (e.g. vehicular communications) applications. These applications obviously have very different transmission characteristics. For example, IoT will typically have a very large number of devices, but each device may have very low throughput. MBB has nearly the opposite properties since it will have a much smaller number of devices, but each one will be transmitting or receiving very high bandwidth content. The intent of network slicing is to be able to partition the physical network at an end-to-end level to allow optimum grouping of traffic, isolation from other tenants, and configuring of resources at a macro level.

Source: ITU presentation, see below

The key differentiator of the network slicing approach is that it provides a holistic end-to-end virtual network for a given tenant. No existing QoS-based solution can offer anything like this. For example, DiffServ, which is the most widely deployed QoS solution, can discriminate VoIP traffic from other types of traffic such as HD video and web browsing. However, DiffServ cannot discriminate and differentially treat the same type of traffic (e.g. VoIP traffic) coming from different tenants.

Also, DiffServ does not have the ability to perform traffic isolation at all. For example, IoT traffic from a health monitoring network (e.g. connecting hospitals and outpatients) typically have strict privacy and security requirements including where the data can be stored and who can access it. This cannot be accomplished by DiffServ as it does not have any features dealing with the compute and storage aspects of the network. All these identified shortfalls of DiffServ will be handled by the features being developed for network slicing.

I came across this presentation by Peter Ashwood-Smith from Huawei Technologies who presented '5G End to-end network slicing Demo' at ITU-T Focus Group IMT-2020 Workshop and Demo Day on 7 December 2016. Its a great presentation, I wish a video of this was available as well. Anyway, the presentation is embedded below and the PPT can be downloaded from here.

5G End to-end network slicing Demo from ITU

The European Telecommunications Standards Institute (ETSI) has established a new Industry Specification Group (ISG) on Zero touch network and Service Management (ZSM) that is working to produce a set of technical specifications on fully automated network and service management with, ideally, zero human intervention. ZSM is targeted for 5G, particularly in network slice deployment. NTT Technical review article on this is available here.

Finally, here is a presentation by Sridhar Bhaskaran of Cellular Insights blog on this topic. Unfortunately, not available for download.


Related Posts:

• 5G and IoT Security Update from ETSI Security Week 2018
• 5G – Beyond the Hype
• 5G Network Architecture Options (Updated)
• Automated 4G / 5G HetNet Design

Introduction to Fixed Wireless Access (FWA)

We have just produced a new tutorial on Fixed Wireless Access (FWA). The high level introductory tutorial looks at what is meant by Fixed Wireless Access, which is being touted as one of the initial 5G use cases. This presentation introduces FWA and looks at a practical deployment example.

According to GSA report, "Global Progress to 5G – Trials, Deployments and Launches", July 2018:

One use-case that has gained prominence is the use of 5G to deliver fixed wireless broadband services. We have identified 20 tests so far that have specifically focused on the fixed wireless access (FWA) use-case, which is five more than three months ago.

Embedded below is the video and presentation of the FWA tutorial.

Beginners: Fixed Wireless Access (FWA) from 3G4G

If you found this useful, you would be interested in other tutorials on the 3G4G website here.

Related Posts:

• Keima: Automated 4G / 5G HetNet Design
• 5G Network Architecture Options (Updated)

LiFi can be a valuable tool for densification

LiFi has been popping up in the news recently. I blogged about it (as LED-Fi) 10 years back. While the concept has remained the same, many of the limitations associated with the technology has been overcome. One of the companies driving LiFi is Scottish startup called pureLiFi.

I heard Professor Harald Haas at IEEE Glasgow Summit speak about how many of the limitations of LiFi have been overcome in the last few years (see videos below). This is a welcome news as there is a tremendous amount of Visible Light Spectrum that is available for exploitation.

While many discussions on LiFi revolve round its use as access technology, I think the real potential lies in its use as backhaul for densification.

For 5G, when we are looking at small cells, every few hundred meters, probably on streetlights and lamp posts, there is a requirement for alternative backhaul to fiber. Its difficult to run fiber to each and every lamp post. Traditionally, this was solved by microwave solutions but another option available in 5G is Integrated Access and Backhauling (IAB) or Self-backhauling.

A better alternative could be to use LiFi for this backhauling between lamp posts or streetlights. This can help avoid complications with IAB when multiple nodes are close by and also any complications with the technology until it matures. This approach is of course being trialed but as the picture above shows, rural backhaul is just one option.

LiFi is being studied as part of IEEE 802.11bb group as well as its potential is being considered for 5G.

Here is a vieo playlist explaining LiFi technology in detail.




Further reading:

• O2 uses light to transmit data in latest network trial
• IEEE Task Force Works on Standard for Light Communications
• Learn How Li-Fi Works from Its Inventor, Harald Haas
• Light Communications for Wireless Local Area Networking
• LiFi can bring enhanced connectivity to your workspace, while also enhancing data security

Telefonica: Big Data, Machine Learning (ML) and Artificial Intelligence (AI) to Connect the Unconnected

Earlier, I wrote a detailed post on how Telefonica was on a mission to connect 100 Million Unconnected with their 'Internet para todos' initiative. This video below is a good advert of what Telefinica is trying to achieve in Latin America


I recently came across a LinkedIn post on how Telefónica uses AI / ML to connect the unconnected by Patrick Lopez, VP Networks Innovation @ Telefonica. It was no brainer that this needs to be shared.

Big data for social good from Patrick Lopez

In his post, Patrick mentions the following:

To deliver internet in these environments in a sustainable manner, it is necessary to increase efficiency through systematic cost reduction, investment optimization and targeted deployments.

Systematic optimization necessitates continuous measurement of the financial, operational, technological and organizational data sets.

1. Finding the unconnected

The first challenge the team had to tackle was to understand how many unconnected there are and where. The data set was scarce and incomplete, census was old and population had much mobility. In this case, the team used high definition satellite imagery at the scale of the country and used neural network models, coupled with census data as training. Implementing visual machine learning algorithms, the model literally counted each house and each settlement at the scale of the country. The model was then enriched with crossed reference coverage data from regulatory source, as well as Telefonica proprietary data set consisting of geolocalized data sessions and deployment maps. The result is a model with a visual representation, providing a map of the population dispersion, with superimposed coverage polygons, allowing to count and localize the unconnected populations with good accuracy (95% of the population with less than 3% false positive and less than 240 meters deviation in the location of antennas).


2. Optimizing transport

Transport networks are the most expensive part of deploying connectivity to remote areas. Optimizing transport route has a huge impact on the sustainability of a network. This is why the team selected this task as the next challenge to tackle.

The team started with adding road and infrastructure data to the model form public sources, and used graph generation to cluster population settlements. Graph analysis (shortest path, Steiner tree) yielded population density-optimized transport routes.


3. AI to optimize network operations

To connect very remote zones, optimizing operations and minimizing maintenance and upgrade is key to a sustainable operational model. This line of work is probably the most ambitious for the team. When it can take 3 hours by plane and 4 days by boat to reach some locations, being able to make sure you can detect, or better, predict if / when you need to perform maintenance on your infrastructure. Equally important is how your devise your routes so that you are as efficient as possible. In this case, the team built a neural network trained with historical failure analysis and fed with network metrics to provide a model capable of supervising the network health in an automated manner, with prediction of possible failure and optimized maintenance route.

I think that the type of data driven approach to complex problem solving demonstrated in this project is the key to network operators' sustainability in the future. It is not only a rural problem, it is necessary to increase efficiency and optimize deployment and operations to keep decreasing the costs.


Finally, its worth mentioning again that I am helping CW (Cambridge Wireless) organise their annual CW TEC conference on the topic 'The inevitable automation of Next Generation Networks'. There are some good speakers and we will have similar topics covered from different angles, using some other interesting approaches. The fees are very reasonable so please join if you can.

Related posts:

• Internet para todos: Telefonica and Parallel Wireless on a mission to connect 100 Million Unconnected
• Automating the 5G Core using Machine Learning and Data Analytics
• ITU 'Network 2030': Initiative to support Emerging Technologies and Innovation looking beyond 5G advances
• Artificial Intelligence - Beyond SON for Autonomous Networks
• Twitter et al. for Small Cell Planning

Changes in LTE pricing strategies

Its been a while since I blogged about pricing strategies (see old posts here, here and here). I recently enjoyed listening to Soichi Nakajima, Director of "Digital Telco and OTT" at IDATE DigiWorld when he presented a talk on LTE pricing strategy. The slides are embedded below

Supply-side strategies: from LTE to 5G - IDATE from techUK

I think the slides are self-explanatory but here is the summary worth highlighting:

How LTE plans have changed: shift in focus from data allowance to quality of service 

• Mobile data services are still largely structured by on data allowance, but high volume and unlimited plans are increasingly common. 
• Unlimited does not necessarily mean high-end: some target users with a small budget, providing a very slow connection. 
• Quality of service becoming central in structuring product lines – especially speed which my or may not be combined with data caps – as is content quality. 
• Certain applications being favoured through zero rating (traffic not deducted from the customer’s allowance). This can be a way to market unlimited plans and avoid fixed-mobile substitution. 
• Growing number of partnerships with OTT video services, rather than selling premium content plans, which are tending to wane.

The slides are available to download from techUK page here. There is also a bonus presentation on "How to address the challenges of providing connectivity on trains".

ITU 'Network 2030': Initiative to support Emerging Technologies and Innovation looking beyond 5G advances

Source: ITU

As per this recent ITU Press Release:

The International Telecommunication Union, the United Nations specialized agency for information and communication technology (ICT), has launched a new research initiative to identify emerging and future ICT sector network demands, beyond 2030 and the advances expected of IMT-2020 (5G) systems. This work will be carried out by the newly established ITU Focus Group on Technologies for Network 2030, which is open to all interested parties.

The ITU focus group aims to guide the global ICT community in developing a "Network 2030" vision for future ICTs. This will include new concepts, new architecture, new protocols – and new solutions – that are fully backward compatible, so as to support both existing and new applications.

"The work of the ITU Focus Group on Technologies for 'Network 2030' will provide network system experts around the globe with a very valuable international reference point from which to guide the innovation required to support ICT use cases through 2030 and beyond," said ITU Secretary-General Houlin Zhao.

These ICT use cases will span new media such as hologrammes, a new generation of augmented and virtual reality applications, and high-precision communications for 'tactile' and 'haptic' applications in need of processing a very high volume of data in near real-time – extremely high throughput and low latency.   

Emphasizing this need, the focus group's chairman, Huawei's Richard Li, said, "This Focus Group will look at new media, new services and new architectures. Holographic type communications will have a big part to play in industry, agriculture, education, entertainment – and in many other fields. Supporting such capabilities will call for very high throughput in the range of hundreds of gigabits per second or even higher."

The ITU Focus Group on Technologies for 'Network 2030' is co-chaired by Verizon's Mehmet Toy, Rostelecom's Alexey Borodin, China Telecom's Yuan Zhang, Yutaka Miyake from KDDI Research, and is coordinated through ITU's Telecommunication Standardization Sector – which works with ITU's 193 Member States and more than 800 industry and academic members to establish international standards for emerging ICT innovations.

The ITU focus group reports to and will inform a new phase of work of the ITU standardization expert group for 'Future Networks' – Study Group 13. It will also strengthen and leverage collaborative relationships with and among other standards development organizations including: The European Telecommunications Standards Institute (ETSI), the Association for Computing Machinery's Special Interest Group on Data Communications (ACM SIGCOMM), and the Institute of Electrical and Electronics Engineers' Communications Society (IEEE ComSoc).

Source: ITU

According to the Focus Group page:

The FG NET-2030, as a platform to study and advance international networking technologies, will investigate the future network architecture, requirements, use cases, and capabilities of the networks for the year 2030 and beyond. 

The objectives include: 

• To study, review and survey existing technologies, platforms, and standards for identifying the gaps and challenges towards Network 2030, which are not supported by the existing and near future networks like 5G/IMT-2020.
• To formulate all aspects of Network 2030, including vision, requirements, architecture, novel use cases, evaluation methodology, and so forth.
• To provide guidelines for standardization roadmap.
• To establish liaisons and relationships with other SDOs.

An ITU interview with Dr. Richard Li, Huawei, Chairman of the ITU-T FG on Network 2030 is available on YouTube here.

A recent presentation by Dr. Richard Li on this topic is embedded below:

Towards a New Internet for the Year 2030 and Beyond from 3G4G

First Workshop on Network 2030 will be held in New York City, United States on 2 October 2018. Details here.

Related News:

• ITU News: ITU launches new study on networks & technologies for 2030 and beyond

Automating the 5G Core using Machine Learning and Data Analytics

One of the new entities introduced by 3GPP in the 5G Core SBA (see tutorial here) is Network Data Analytics Function, NWDAF.

3GPP TR 23.791: Study of Enablers for Network Automation for 5G (Release 16) describes the following 5G Network Architecture Assumptions:

1 The NWDAF (Network Data Analytics Function) as defined in TS 23.503 is used for data collection and data analytics in centralized manner. An NWDAF may be used for analytics for one or more Network Slice.
2 For instances where certain analytics can be performed by a 5GS NF independently, a NWDAF instance specific to that analytic maybe collocated with the 5GS NF. The data utilized by the 5GS NF as input to analytics in this case should also be made available to allow for the centralized NWDAF deployment option.
3 5GS Network Functions and OAM decide how to use the data analytics provided by NWDAF to improve the network performance.
4 NWDAF utilizes the existing service based interfaces to communicate with other 5GC Network Functions and OAM.
5 A 5GC NF may expose the result of the data analytics to any consumer NF utilizing a service based interface.
6 The interactions between NF(s) and the NWDAF take place in the local PLMN (the reporting NF and the NWDAF belong to the same PLMN).
7 Solutions shall neither assume NWDAF knowledge about NF application logic. The NWDAF may use subscription data but only for statistical purpose.

Picture Source: Application of Data Mining in the 5G Network Architecture by Alexandros Kaloxylos

Continuing from 3GPP TR 23.791:

The NWDAF may serve use cases belonging to one or several domains, e.g. QoS, traffic steering, dimensioning, security.
The input data of the NWDAF may come from multiple sources, and the resulting actions undertaken by the consuming NF or AF may concern several domains (e.g. Mobility management, Session Management, QoS management, Application layer, Security management, NF life cycle management).
Use case descriptions should include the following aspects:
1. General characteristics (domain: performance, QoS, resilience, security; time scale).
2. Nature of input data (e.g. logs, KPI, events).
3. Types of NF consuming the NWDAF output data, how data is conveyed and nature of consumed analytics.
4. Output data.
5. Possible examples of actions undertaken by the consuming NF or AF, resulting from these analytics.
6. Benefits, e.g. revenue, resource saving, QoE, service assurance, reputation.

Picture Source: Application of Data Mining in the 5G Network Architecture by Alexandros Kaloxylos

3GPP TS 23.501 V15.2.0 (2018-06) Section 6.2.18 says:

NWDAF represents operator managed network analytics logical function. NWDAF provides slice specific network data analytics to a NF. NWDAF provides network analytics information (i.e., load level information) to a NF on a network slice instance level and the NWDAF is not required to be aware of the current subscribers using the slice. NWDAF notifies slice specific network status analytic information to the NFs that are subscribed to it. NF may collect directly slice specific network status analytic information from NWDAF. This information is not subscriber specific.

In this Release of the specification, both PCF and NSSF are consumers of network analytics. The PCF may use that data in its policy decisions. NSSF may use the load level information provided by NWDAF for slice selection.

NOTE 1: NWDAF functionality beyond its support for Nnwdaf is out of scope of 3GPP.
NOTE 2: NWDAF functionality for non-slice-specific analytics information is not supported in this Release of the specification.

3GPP Release-16 is focusing on 5G Expansion and 5G Efficiency, SON and Big Data are part of 5G Efficiency.

3GPP Release-16 is going to focus on 5G expansion & efficiency. Listen to the @3GPPLive Webinar here: https://t.co/tKzXJ3cUFj pic.twitter.com/1xCZfpT9lt

— 3G4G (@3g4gUK) July 14, 2018

Light Reading Artificial Intelligence and Machine Learning section has a news item on this topic from Layer123's Zero Touch & Carrier Automation Congress:

The 3GPP standards group is developing a machine learning function that could allow 5G operators to monitor the status of a network slice or third-party application performance.

The network data analytics function (NWDAF) forms a part of the 3GPP's 5G standardization efforts and could become a central point for analytics in the 5G core network, said Serge Manning, a senior technology strategist at Sprint Corp.

Speaking here in Madrid, Manning said the NWDAF was still in the "early stages" of standardization but could become "an interesting place for innovation."

The 3rd Generation Partnership Project (3GPP) froze the specifications for a 5G new radio standard at the end of 2017 and is due to freeze another set of 5G specifications, covering some of the core network and non-radio features, in June this year as part of its "Release 15" update.

Manning says that Release 15 considers the network slice selection function (NSSF) and the policy control function (PCF) as potential "consumers" of the NWDAF. "Anything else is open to being a consumer," he says. "We have things like monitoring the status of the load of a network slice, or looking at the behavior of mobile devices if you wanted to make adjustments. You could also look at application performance."

In principle, the NWDAF would be able to make use of any data in the core network. The 3GPP does not plan on standardizing the algorithms that will be used but rather the types of raw information the NWDAF will examine. The format of the analytics information that it produces might also be standardized, says Manning.

Such technical developments might help operators to provide network slices more dynamically on their future 5G networks.

Generally seen as one of the most game-changing aspects of 5G, the technique of network slicing would essentially allow an operator to provide a number of virtual network services over the same physical infrastructure.

For example, an operator could provide very high-speed connectivity for mobile gaming over one slice and a low-latency service for factory automation on another -- both reliant on the same underlying hardware.

However, there is concern that without greater automation operators will have less freedom to innovate through network slicing. "If operators don't automate they will be providing capacity-based slices that are relatively large and static and undifferentiated and certainly not on a per-customer basis," says Caroline Chappell, an analyst with Analysys Mason .

In a Madrid presentation, Chappell said that more granular slicing would require "highly agile end-to-end automation" that takes advantage of progress on software-defined networking and network functions virtualization.

"Slices could be very dynamic and perhaps last for only five minutes," she says. "In the very long term, applications could create their own slices."

Despite the talk of standardization, and signs of good progress within the 3GPP, concern emerged this week in Madrid that standards bodies are not moving quickly enough to address operators' needs.

Caroline Chappell's talk is available here whereas Serge Manning's talk is embedded below:



I am helping CW organise the annual CW TEC conference on the topic The inevitable automation of Next Generation Networks

#CWTEC 2018 planning committee working hard to bring an exciting conference - explores the role of #AI in delivering Next Gen. Network performance; & bridges the gap between #AI/#ML & Telecos communities! @zahidtg @Bob_CWCEO @swunger Paul Ceely @bt_uk , John Haine @BristolCSN pic.twitter.com/4uGprC1usg

— Sylvia Lu (@SylviaLuUk) July 23, 2018

Communications networks are perhaps the most complex machines on the planet. They use vast amounts of hardware, rely on complex software, and are physically distributed over land, underwater, and in orbit. They increasingly provide essential services that underpin almost every aspect of life. Managing networks and optimising their performance is a vast challenge, and will become many times harder with the advent of 5G. The 4th Annual CW Technology Conference will explore this challenge and how Machine Learning and AI may be applied to build more reliable, secure and better performing networks.

Is the AI community aware of the challenges facing network providers? Are the network operators and providers aware of how the very latest developments in AI may provide solutions? The conference will aim to bridge the gap between AI/ML and communications network communities, making each more aware of the nature and scale of the problems and the potential solutions.

I am hoping to see some of this blog readers at the conference. Looking forward to learning more on this topic amongst others for network automation.

Related Post:

• Artificial Intelligence - Beyond SON for Autonomous Networks