Radio Design, the award-winning market leader in the provision of wireless infrastructure sharing solutions and RF filter systems, hosted a webinar last week focused on the deployment of the 700 MHz frequency band. This new 700 MHz spectrum is in great demand across the world, mainly due to its long anticipated use as low band 5G spectrum. The webinar explores the potential of this band, as well as how to prepare for potential challenges when deploying.
For people who are familiar with our trainings, we divide the spectrum into three layers, the coverage layer, the capacity layer and the high-throughput layer. 700 MHz is the most popular coverage layer spectrum worldwide.
The slide above from the webinar talks of the recent Austrian 5G Spectrum auction that we blogged about. See tweet below for details
In the webinar, slides and video embedded below, Radio Design’s founder – Eric Hawthorn – kicks things off by analysing the benefits of deploying the 700 MHz band in the real world, before passing over to Global Engineering Director – Steve Shaw – who explores some of the technical problems which can arise, as well as some of the solutions. Last but not least, COO and co-owner of Keima – Iris Barcia – provides her insight into the benefits of deploying the 700 MHz band.
3GPP Release 16 describes business role models for network slicing and in TR 21.916 I found the figures below that I have pimped a little bit to illustrate an asset tracking use case for goods transported with a truck from Factory A to Factory B.
Factory B is equipped with a 5G Non-Public Network (NPN) that broadcasts an NPN-ID or - if the network infrastructure is deployed by an operator - a Cell Access Group ID (CAG ID).
I would like to assume that in case of the scenario shown in 3GPP Figure 2-2 the asset tracking CIoT devices are able to access any necessary PLMN, Network Slice and NPN. This can be achieved e.g. by using an eSIM.
So while the truck is at the location of Factory A the asset tracking "things" will connect to the private slice of Factory A provided by the operator of PLMN 1. Factory A is a tenant of this operator. This means: Factory A rented a virtual part of PLMN1 for private use and technically this rented virtual network part is realized by a NW slice.
When the truck leaves Factory A and drives on the road (maybe a long distance) to Factory B the asset tracking data must be transmitted over public mobile network infrastructure. Depending on rural coverage this service can be offered by PLMN 2 (as in case of 3GPP figure 2-2) or by PLMN 1 (as in case of 3GPP figure 2-3).
In case of 3GPP figure 2-4 the operator of PLMN 1 is even able to provide the private slice along the road, which allows Factory A to stretch the coverage of their virtual private network (slice) over a very long distance.
Looking further into the Cellular IoT enhancements defined by 3GPP in Release 16 it turns out that actually there is no need for a nation-wide 5G coverage to realize at least the role models shown in the 3GPP figures 2-2 and 2-3.
Because Release 16 also defines co-existence and inter-RAT mobility between 5G CIoT traffic and 4G NB-IoT the operators of PLMN 1 and PLMN 2 may offer NB-IoT coverage along the road while the factories are covered with 5G NR frequency cells - as shown in my second figure below.
It illustrates the great improved flexibility that Release 16 standards are offering for customized business solutions and monitoring the service quality is not a trivial task under these circumstances.
Earlier this year, MediaTek had announced that its MT2625 NB-IoT chip has been validated for LwM2M over NIDD on SoftBank Corp.’s cellular network across Japan. This achievement marks the first global commercial readiness of LwM2M over NIDD; a secure, ultra-efficient IoT communications technique that is being adopted by operators worldwide. The benefits of LwM2M over NIDD include security improvements, cost-efficient scalability and reduced power consumption.
LwM2M over NIDD is a combination of the communication technology "NIDD (Non-IP Data Delivery)" that does not use an IP address in LTE communication NB-IoT for IoT and the device management protocol "LwM2M (Lightweight M2M)" advocated by the Open Mobile Alliance. It's been a while since I wrote about Open Mobile Alliance on this blog. OMA SpecWorks is the successor brand to the Open Mobile Alliance. You can read all about it here.
OMA SpecWorks’ LightweightM2M is a device management protocol designed for sensor networks and the demands of a machine-to-machine (M2M) environment. With LwM2M, OMA SpecWorks has responded to demand in the market for a common standard for managing lightweight and low power devices on a variety of networks necessary to realize the potential of IoT. The LwM2M protocol, designed for remote management of M2M devices and related service enablement, features a modern architectural design based on REST, defines an extensible resource and data model and builds on an efficient secure data transfer standard called the Constrained Application Protocol (CoAP). LwM2M has been specified by a group of industry experts at the OMA SpecWorks Device Management Working Group and is based on protocol and security standards from the IETF.
You can get all the LwM2M resources here and the basic specs of 'Lightweight M2M 1.1: Managing Non-IP Devices in Cellular IoT Networks' here.
The 5G Americas whitepaper 'Wireless Technology Evolution Towards 5G: 3GPP Release 13 to Release 15 and Beyond' details how Current Architecture for 3GPP Systems for IOT Service Provision and Connectivity to External Application Servers. It also talks about Rel-13 Cellular IoT EPS Optimizations which provide improved support of small data transfer over control plane and user plane. Control Plane CIoT EPS Optimization transports user data (measurements, ID, status, etc.) via MME by encapsulating user data in NAS PDUs and reduces the total number of control plane messages when handling a short data transaction. Control Plane CIoT EPS optimization, designed for small infrequent data packets, can also be used for larger data bursts depending in UE Radio capability.
User data transported using the Control Plane CIoT EPS Optimization, has special characteristics, as different mobility anchor and termination nodes.
Therefore, the Preferred Network Behavior signaling must include information on:
Whether Control Plane CIoT EPS optimization is supported
Whether User Plane CIoT EPS optimization is supported
Whether Control Plane CIoT EPS optimization is preferred or whether User Plane CIoT EPS optimization is preferred
These optimizations have enabled:
Non-IP Data Delivery (NIDD) for both: mobile originated and mobile terminated communications, by using SCEF (Service Capability Exposure Function) or SGi tunneling. However, it has to be taken into account that Non-IP PDUs may be lost and its sequence is not guaranteed
For IP data, the UE and MME may perform header compression based on Robust Header Compression (ROHC) framework
NB-IoT UE can attach but not activate any PDN connection
High latency communication handled by the buffering of downlink data (in the Serving GW or the MME)
SMS transfer
EPS Attach, TA Update and EPS Detach procedures for NB-IoT only UEs, with SMS service request
Procedures for connection suspend and resume are added
Support for transfer of user plane data without the need for using the Service Request procedure to establish Access Stratum context in the serving eNodeB and UE
When selecting an MME for a UE that is using the NB-IoT RAT, and/or for a UE that signals support for CIoT EPS Optimizations in RRC signaling, the eNodeB’s MME selection algorithm shall select an MME taking into account its Release 13 NAS signaling protocol.
Mpirical has a nice short video explaining 5G Non IP Data Delivery. It is embedded below.
IoT has not taken off as expected and prophesised for years. While the OMASpecWorks is doing some fantastic work by defining simplified approach for IoT deployment, its current member list doesn't have enough operators to drive the uptake required for its spec adoption. They would argue that it doesn't matter how many members there are as the NIDD approach is completely optional and over-the-top. Let's wait and see how it progresses.
I have received quite a few requests to do a 5G Network Slicing tutorial but have still not got around to doing it. Luckily there are so many public resources available that I can get away with not doing one on this topic.
This Award Solutions webinar by Paul Shepherd (embedded below) provides good insights into network slicing, what it is, how it efficiently enables different services in 5G networks, and the architectural changes in 5G required to support it.
Then there is also this myth about 3 slices in the network. The GSMA slice template is a good starting point for an operator looking to do network slicing in their 5G networks. The latest version is 3.0, available here.
As this picture (courtesy of Phil Kendall) shows, it's not a straightforward task.
That is 37 attributes each of which can take multiple values. The permutations are massive.
Alistair URIE from Nokia Bell Labs points out some common misconceptions people have with Network Slicing:
Multiple slices may share the same cell and the same RU in each slice
Single UE may have up to 8 active slices but must have a single CU-CP instance to terminate the common RRC
Slicing supports more than 3 slices
Back in March, China Mobile, Huawei, Tencent, China Electric Power Research Institute, and Digital Domain have jointly released the Categories and Service Levels of Network Slice White Paper to introduce the industry’s first classification of network slice levels. The new white paper dives into the definitions, solutions, typical scenarios, and evolution that make up the five levels of network slices. It serves as an excellent reference to provide guidance in promoting and commercializing network slicing, and lays a theoretical foundation for the industry-wide application of network slicing.
Phase 1 (ready): As mentioned above, the 5G transport network and 5G core network support different software-based and hardware-based isolation solutions. On the 5G NR side, 5QIs (QoS scheduling mechanism) are mainly used to achieve software-based isolation in WAN scenarios. Alternatively, campus-specific 5G NR (including micro base stations and indoor distributed base stations) is used to implement hardware-based isolation in LAN scenarios. In terms of service experience assurance, 5QIs are used to implement differentiated SLA assurance between slices. In terms of slice OAM capabilities, E2E KPIs can be managed in a visualized manner. This means that from 2020 on, Huawei is ready to deliver commercial use of E2E slicing for common customers and VIP customers of the public network and common customer of general industries (such as UHD live broadcast and AR advertisement).
Phase 2 (to be ready in 2021): In terms of isolation, the 5G NR side supports the wireless RB resource reservation technology (including the static reservation and dynamic reservation modes) to implement E2E network resource isolation and slicing in WAN scenarios. In terms of service experience assurance, features such as 5G LAN and 5G TSN are enhanced to implement differentiated and deterministic SLA assurance between different slices. In terms of slice OAM, on the basis of tenant-level KPI visualization, the limited self-service of the industry for rented slices can be further supported. In this phase, operators can serve VIP customers in common industries (such as AR/VR cloud games and drone inspection), dedicated industry customers (such as electric power management information region, medical hospital campus, and industrial campus), and dedicated industry customers (such as electric power production control region and public security).
Phase 3 (to be ready after 2022): In this phase, 5G network slicing supports real dynamic closed-loop SLAs based on AI and negative feedback mechanism, implementing network self-optimization and better serving industries (such as 5G V2X) with high requirements on mobility, roaming, and service continuity. In addition, industry-oriented comprehensive service capabilities will be further enhanced and evolved.
A more technical presentation from Nokia is available here. The video below shows how innovations in IP routing and SDN work together to implement network slicing in the transport domain.
If you know some other good resources and tutorials worth sharing, add them in the comments below.
Mats Näslund is a cryptologist at the National Defence Radio Establishment outside Stockholm, an agency under the Swedish dept. of defence. As part of his work, he represents Sweden in technical LI standardization in 3GPP. Mats also has a part time appointment as adjunct professor at KTH. Her recently delivered a HAIC Talk on Lawful Intercept in 5G Networks. HAIC Talks is a series of public outreach events on contemporary topics in information security, organized by the Helsinki-Aalto Institute for Cybersecurity (HAIC).
The following is the description from HAIC website:
Our societies have been prospering, much due to huge technological advances over the last 100 years. Unfortunately, criminal activity has in many cases also been able to draw benefits from these advances. Communication technology, such as the Internet and mobile phones, are today “tools-of-the-trade” that are used to plan, execute, and even hide crimes such as fraud, espionage, terrorism, child abuse, to mention just a few. Almost all countries have regulated how law enforcement, in order to prevent or investigate serious crime, can sometimes get access to meta data and communication content of service providers, data which normally is protected as personal/private information. The commonly used term for this is Lawful Interception (LI). For mobile networks LI is, from a technical standpoint, carried out according to ETSI and 3GPP standards. In this talk, the focus will lie on the technical LI architecture for 5G networks. We will also give some background, describing the general, high-level legal aspects of LI, as well as some current and future technical challenges.
TCO or 'Total Cost of Ownership' is an important topic for the mobile networks. The service providers use it to ascertain how much the network will cost and based on that they decide what they should charge and how much money could make.
In this basic tutorial, we looks at the basic costs in the mobile network, eventually looking at the CapEx and OpEx of RAN and look at how some operators try to reduce the these costs. Slides and video embedded below.
I realised that I have not looked at Positioning techniques a lot in our blogs so this one should be a good summary of the latest positioning techniques in 5G.
Qualcomm has a nice short summary here: Release 16 supports multi-/single-cell and device-based positioning, defining a new positioning reference signal (PRS) used by various 5G positioning techniques such as roundtrip time (RTT), angle of arrival/departure (AoA/AoD), and time difference of arrival (TDOA). Roundtrip time (RTT) based positioning removes the requirement of tight network timing synchronization across nodes (as needed in legacy techniques such as TDOA) and offers additional flexibility in network deployment and maintenance. These techniques are designed to meet initial 5G requirements of 3 and 10 meters for indoor and outdoor use cases, respectively. In Release 17, precise indoor positioning functionality will bring sub-meter accuracy for industrial IoT use cases.
I wrote about the 5G Americas white paper titled, "The 5G Evolution: 3GPP Releases 16-17" highlighting new features in 5G that will define the next phase of 5G network deployments across the globe. The following is from that whitepaper:
Release-15 NR provides support for RAT-independent positioning techniques and Observed Time Difference Of Arrival (OTDOA) on LTE carriers. Release 16 extends NR to provide native positioning support by introducing RAT-dependent positioning schemes. These support regulatory and commercial use cases with more stringent requirements on latency and accuracy of positioning.25 NR enhanced capabilities provide valuable, enhanced location capabilities. Location accuracy and latency of positioning schemes improve by using wide signal bandwidth in FR1 and FR2. Furthermore, new schemes based on angular/spatial domain are developed to mitigate synchronization errors by exploiting massive antenna systems.
The positioning requirements for regulatory (e.g. E911) and commercial applications are described in 3GPP TR 38.855. For regulatory use cases, the following are the minimum performance requirements:
Horizontal positioning accuracy better than 50 meters for 80% of the UEs.
Vertical positioning accuracy better than 5 meters for 80% of the UEs.
End-to-end latency less than 30 seconds.
For commercial use cases, for which the positioning requirements are more stringent, the following are the starting-point performance targets
Horizontal positioning accuracy better than 3 meters (indoors) and 10 meters (outdoors) for 80% of the UEs.
Vertical positioning accuracy better than 3 meters (indoors and outdoors) for 80% of the UEs.
End-to-end latency less than 1 second.
Figure 3.11 above shows the RAT-dependent NR positioning schemes being considered for standardization in Release 16:
Downlink time difference of arrival (DL-TDOA): A new reference signal known as the positioning reference signal (PRS) is introduced in Release 16 for the UE to perform downlink reference signal time difference (DL RSTD) measurements for each base station’s PRSs. These measurements are reported to the location server.
Uplink time difference of arrival (UL-TDOA): The Release-16 sounding reference signal (SRS) is enhanced to allow each base station to measure the uplink relative time of arrival (UL-RTOA) and report the measurements to the location server.
Downlink angle-of-departure (DL-AoD): The UE measures the downlink reference signal receive power (DL RSRP) per beam/gNB. Measurement reports are used to determine the AoD based on UE beam location for each gNB. The location server then uses the AoDs to estimate the UE position.
Uplink angle-of-arrival (UL-AOA): The gNB measures the angle-of-arrival based on the beam the UE is located in. Measurement reports are sent to the location server.
Multi-cell round trip time (RTT): The gNB and UE perform Rx-Tx time difference measurement for the signal of each cell. The measurement reports from the UE and gNBs are sent to the location server to determine the round trip time of each cell and derive the UE position.
Enhanced cell ID (E-CID). This is based on RRM measurements (e.g. DL RSRP) of each gNB at the UE. The measurement reports are sent to the location server.
UE-based measurement reports for positioning:
Downlink reference signal reference power (DL RSRP) per beam/gNB
Downlink reference signal time difference (DL RSTD)
UE RX-TX time difference
gNB-based measurement reports for positioning:
Uplink angle-of-arrival (UL-AoA)
Uplink reference-signal receive power (UL-RSRP)
UL relative time of arrival (UL-RTOA)
gNB RX-TX time difference
NR adopts a solution similar to that of LTE LPPa for Broadcast Assistance Data Delivery, which provides support for A-GNSS, RTK and OTDOA positioning methods. PPP-PTK positioning will extend LPP A-GNSS assistance data message based on compact “SSR messages” from QZSS interface specifications. UE-based RAT-dependent DL-only positioning techniques are supported, where the positioning estimation will be done at the UE-based on assistance data provided by the location server.
Rohde&Schwarz have a 5G overview presentation here. This picture from that presentation is a good summary of the 3GPP Release-16 5G NR positioning techniques. This nice short video on "Release 16 Location Based Services Requirements" complements it very well.
The premises of virtualization is to move physical network functions (PNF in hardware) into software and to design them in a way so that they can be deployed on a NFVI (Network Functions Virtualization Infrastructure, a.k.a. the cloud).
MANagement and Orchestration (MANO) is a key element of the ETSI network functions virtualization (NFV) architecture. MANO is an architectural framework that coordinates network resources for cloud-based applications and the lifecycle management of virtual network functions (VNFs) and network services. As such, it is crucial for ensuring rapid, reliable NFV deployments at scale. MANO includes the following components: the NFV orchestrator (NFVO), the VNF manager (VNFM), and the virtual infrastructure manager (VIM).
NFV Orchestrator: Responsible for onboarding of new network services (NS) and virtual network function (VNF) packages; NS lifecycle management; global resource management; validation and authorization of network functions virtualization infrastructure (NFVI) resource requests.
VNF Manager: Oversees lifecycle management of VNF instances; fills the coordination and adaptation role for configuration and event reporting between NFV infrastructure (NFVI) and Element/Network Management Systems.
Virtualized Infrastructure Manager (VIM): Controls and manages the NFVI compute, storage, and network resources.
For the NFV MANO architecture to work properly and effectively, it must be integrated with open application program interfaces (APIs) in the existing systems. The MANO layer works with templates for standard VNFs and gives users the power to pick and choose from existing NFVI resources to deploy their platform or element.
Couple of good old tutorials, good as gold, explaining the ETSI NFV MANO concept. The videos are embedded below. The slides from the video are probably not available but there are other slides from ETSI here. If you are new to this, this is a good presentation to start with.
NFV MANO Part 1: Overview and VNF Lifecycle Management: Uwe Rauschenbach | Rapporteur | ETSI NFV ISG covers:
ETSI NFV MANO Concepts
VNF Lifecycle Management
NFV MANO Part 2: Network Service Lifecycle Management: Jeremy Fuller | Chair, IFA WG | ETSI NFV ISG covers:
Network Service Lifecycle Management
If you have any better suggestions for the slides / video, please feel free to add in the comments.
Cloud native is talked about so often that it is assumed everyone knows what is means. Before going any further, here is a short introductory tutorial here and video by my Parallel Wireless colleague, Amit Ghadge.
If instead you prefer a more detailed cloud native tutorial, here is another one from Award Solutions.
Back in June, Johanna Newman, Principal Cloud Transformation Manager, Group Technology Strategy & Architecture at Vodafone spoke at the Cloud Native World with regards to Vodafone's Cloud Native Journey
Roz Roseboro, a former Heavy Reading analyst who covered the telecom market for nearly 20 years and currently a Consulting Analyst at Light Reading wrote a fantastic summary of that talk here. The talk is embedded below and selective extracts from the Light Reading article as follows:
While vendors were able to deliver some cloud-native applications, there were still problems ensuring interoperability at the application level. This means new integrations were required, and that sent opex skyrocketing.
I was heartened to see that Newman acknowledged that there is a difference between "cloud-ready" and "cloud-native." In the early days, many assumed that if a function was virtualized and could be managed using OpenStack, that the journey was over.
However, it soon became clear that disaggregating those functions into containerized microservices would be critical for CSPs to deploy functions rapidly and automate management and achieve the scalability, flexibility and, most importantly, agility that the cloud promised. Newman said as much, remarking that the jump from virtualized to cloud-native was too big a jump for hardware and software vendors to make.
The process of re-architecting VNFs to containerize them and make them cloud-native is non-trivial, and traditional VNF suppliers have not done so at the pace CSPs would like to see. I reference here my standard chicken and egg analogy: Suppliers will not go through the cost and effort to re-architect their software if there are no networks upon which to deploy them. Likewise, CSPs will not go through the cost and effort to deploy new cloud networks if there is no software ready to run on them. Of course, some newer entrants like Rakuten have been able to be cloud-native out of the gate, demonstrating that the promise can be realized, in the right circumstances.
Newman also discussed the integration challenges – which are not unique to telecom, of course, but loom even larger in their complex, multivendor environments. During my time as a cloud infrastructure analyst, in survey after survey, when asked what the most significant barrier to faster adoption of cloud-native architectures, CSPs consistently ranked integration as the most significant.
Newman spent a little time discussing the work of the Common NFVi Telco Taskforce (CNTT), which is charged with developing a handful of reference architectures that suppliers can then design to which will presumably help mitigate many of these integration challenges, not to mention VNF/CNF life cycle management (LCM) and ongoing operations.
Vodafone requires that all new software be cloud-native – calling it the "Cloud Native Golden Rule." This does not come as a surprise, as many CSPs have similar strategies. What did come as a bit of a surprise, was the notion that software-as-a-service (SaaS) is seen as a viable alternative for consuming telco functions. While the vendor with the SaaS offering may not itself be cloud-native (for example, it could still have hardware dependencies), from Vodafone's point of view, it ends up performing as such, given the lower operational and maintenance costs and flexibility of a SaaS consumption model.
If you have some other fantastic links, videos, resources on this topic, feel free to add in the comments.
