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5G Wireless Networks — Architecture and Services

17 May

Wireless network providers are rolling out deployments of the next generation of network technology. This new generation of wireless networks known as 5G promises to significantly improve the usability and performance of networked mobile applications. In this article, we review the architecture and functions that enable the delivery of feature-rich, dynamic, location aware applications on 5G wireless networks.

We’ll begin with an overview of previous wireless network technologies such as 3G and 4G, we’ll then review the current documentation to get a clear picture of the 5G standard and protocols. By analyzing network architectures, service specifications, and protocols, we will have a better understanding of the current state of 5G wireless technology. We’ll focus specifically on wireless and mobility challenges that 5G attempts to address.

At the end of this article, we hope to understand the ways in which 5G wireless has improved upon previous generations of wireless networking architectures such as 4G LTE. We will also see how a unified data network and service-oriented architecture allows us to move compute resources closer to the “edge” of the network on 5G wireless networks.

History

Over the past 20 years, the number of wireless users has increased significantly. There are now more cellular phone subscriptions than there are people on the planet. During this time, wireless technology has also evolved considerably. Today, the 5G wireless architecture and protocols offer a service oriented and highly scalable infrastructure that can support dynamic mobile applications and services.

Early wireless companies relied on 2G networks to provide voice connectivity to the Public Switched Telephone Network (PSTN) for their users. 2G had limited bandwidth but was adequate enough to support voice communication for wireless and mobile users. Its architecture relied on mobile users connecting to a Mobile Switching Center using a Base Station Controller (BSC). A special MSC known as a Gateway MSC connected mobile users to the voice telephone network.

The next generation of wireless network architecture was introduced around the year 2000 with the 3G wireless standard. In addition to support for voice communication, 3G added data capabilities to the existing wireless network. 3G introduced a new cellular data network that operated in parallel with the existing cellular voice network. The two networks were connected at the edge by the Radio Network Controller (RNC). Although 3G provided data connectivity, it did not have enough features to support modern dynamic networked applications.

Around 2009, we saw the next evolution in cellular networks known as the 4G Long Term Evolution standard (LTE). It introduced two important innovations over 3G systems — an all-IP Core network and an enhanced radio network. The LTE radio access network uses Orthogonal Frequency Division Multiplexing (OFDM) to give active mobile nodes access to shared channels. It also allows user priorities and contracted levels of service to be used when scheduling downstream packet transmission. 4G provides support for dynamic networked applications ranging from location-aware mapping to real-time social networking applications. 4G offers bandwidths up to 200 mbps.

The next evolution in wireless communication following 4G is 5G. The 5G architecture and protocols provide increased bandwidth up to 1Gbps. A new Radio Access Network (RAN) allows much higher device density and less interference than 4G. 5G is also service oriented, allowing providers to tailor the mobile user experience to match application requirements.

5G Features

The 5G network architecture and associated services allow network providers to offer many new services and features to their customers. It also enhances some of the current features of wireless networks (Intel. n.d). Some of the new features and improvements include:

· Increased bandwidth: 5G can achieve download speads of 1–3 gigabits per second (Gbps) within the High-band frequencies of 25–39 GHz, near the bottom of the millimeter wave band. This is comparable to broadband cable internet.

· Low latency: Improvements in both the Core Network (Core) and Radio Access Network (RAN) promise to deliver low latency in the single digit milliseconds compared to an average of 50 ms for 4G LTE networks

· Higher availability, coverage, and density: With the use of Multiple Input and Multiple Output antennas (MIMO), each antenna can be individually controlled, resulting in increased sector throughput and capacity density. (Larsson et al, 2017)

The 5G Spectrum and Frequencies

There are two ranges of frequencies allocated to the 5G wireless networks:

· Frequency Range 1: Also known as the sub-6 GHz range, it goes From 450 MHz to 6 GHz

· Frequency Range 2: Known as millimeter wave, it ranges from 24.25 GHz to 52.6 GHz

Like its predecessor, 5G uses Orthogonal Frequency Division Multiplexing (OFDM) to share spectrum between active users. OFDM relies on a combination of Time Division Multiplexing (TDM) and Frequency Division Multiplexing (FDM) to increase channel utilization and minimize interferences.

In addition to licensed bands, 5G networks can also operate in unlicensed 5 GHz and 6 GHz spectrum bands (Wikipedia. 2020, April 6). (Poulos et al, 2019)

The 5G Network

The 5G architecture evolved from 4G LTE by introducing many features such as separation of Control and User Planes (CUPS) of the 4G Evolved packet Core (EPC), and reorganization of CUPS functions into services.

In contrast with previous generations of wireless cellular technology, the 5G architecture does not separate the core and edge networks. 5G presents us with a unified network. Network slicing uses virtualization and multiplexing to create independent logical networks on top of the existing network infrastructure (IEEE, n.d).

5G separates the Packet Data Network Gateway (P-GW) and Serving Gateway (S-GW) into user and control gateways. P-GW was split into PGW-C and PGW-U, and S-GW was split into SGW-C and SGW-U. This separation provides additional flexibility in network deployment and operations. It also allows for independent scaling of control plane and user plane functions (Flynn, n. d). In addition to separating control and user planes, 5G also organized 4G EPC components into services such as Authentication, Policy Control Function (PCF), Access and Mobility, and Session Management.

Service-Oriented Architecture

5G relies on a robust set of interconnected services. Services are exposed with a REST interface using HTTP/2. A Network Function Repository provides service discovery of Network Function Instances.

(Grandmetric, 2020)

The following services are defined by the 5G Service-Based architecture:

· Authentication Server Function (AUSF)

· Core Access and Mobility Management Function (AMF)

· Data network (DN), e.g. operator services, Internet access or 3rd party services

· Structured Data Storage network function (SDSF)

· Unstructured Data Storage network function (UDSF)

· Network Exposure Function (NEF)

· NF Repository Function (NRF)

· Policy Control function (PCF)

· Session Management Function (SMF)

· Unified Data Management (UDM)

· User plane Function (UPF)

· Application Function (AF)

· User Equipment (UE)

· (Radio) Access Network ((R)AN)

· Network Slice Selection Function (NSSF) — Used to select network slice instance.

Mobility Management

5G networks provide a set of reliable mobility management services. The Access and Mobility Management Function (AMF) is responsible for interfacing with User Equipment (UE). AMF interfaces with Session Management Functions (SMF) to track user sessions. This ensures a separation between authentication services and session management services. AMF also uses the Network Slice Selection Function (NSSF) to select network slice instances for user equipment.

(Dredge, n. d.)

When a User Equipment is leaving the coverage area of a gNB and entering the coverage area of another, the AMF is also responsible for coordinating handoff between gNBs. It also coordinates handoffs within the same Radio Access Network (RAN).

5G supports two types of handover: the inter gNB handover, and an intra RAN handover

· The following steps are included in the Inter gNB handover:

o Source gNB initiates handover

o Target gNB performs admission control and provide Radio Resource Config (RRC)

o Source gnB forwards RRC to UE

o UE moves RRC connection to target gNB

o UE replies handover is complete

· During an intra RAN handover, gNBs directly exchange messages. The target gNB will trigger handover completion phase, resulting in a release of resources from source gNB (RF Wireless World, n.d.).

Compute at the Edge: 5G + AWS wavelength

One of the most promising features of 5G wireless networks is Compute at the Edge. Today, networked applications use computing resources located in data centers that are far from the user. This introduces latency and other network related issues. Wireless network providers are working with datacenter vendors to bring compute closer to the edge of the network. One example of such implementation is AWS wavelength. A collaboration between Amazon Web Services and several wireless network providers to bring compute resources closer to the edge of the network.

Source: https://medium.com/@oumarwillane/5g-wireless-networks-architecture-and-services-8d643e000da7 17 05 20

5G in Release 17 – strong radio evolution

15 Dec

5G NR radio evolution is carried out with a drive from a multitude of key stakeholders from the traditional commercial cellular industry, a wide variety of industry verticals and the non-terrestrial access ecosystem. The Release-17 work program is a testament that 3GPP is committed to serving all of these key stakeholders.

A major achievement of the RAN plenary meeting was the approval of the content for Release-17 – both in terms of the list of features included and the detailed functionality within each feature. This decision addresses the work in RAN1, RAN2, and RAN3: physical layer, radio protocol and radio architecture enhancements. Further decisions will be made at RAN#88, in June next year, on the RAN4 work for Release-17.

For Release-17 the physical layer work in RAN1 will start at the beginning of next year, whilst radio protocol and architecture work in RAN2 and RAN3, respectively, will start in the 2nd quarter.

RAN R17 schedule

(Click above to enlarge the image)

Physical layer enhancements (RAN1)

From January, RAN1 will start working on several features that continue to be important for overall efficiency and performance of 5G NR: MIMO, Spectrum Sharing enhancements, UE Power Saving and Coverage Enhancements. RAN1 will also undertake the necessary study and specification work to enhance the physical layer to support frequency bands beyond 52.6GHz, all the way up until 71 GHz. The summary figure below shows the Release-17 content for RAN1 with the planned RAN1 time allocations (TU) in each quarter.

R1 TUs rel17

In addition, several features have been approved to address different needs of vertical industries: Sidelink enhancements to address automotive industry and critical communication needs, Positioning enhancements to address stringent accuracy and latency requirements for indoor industrial cases. Further functionalities will be added to the rich set of capabilities to better support low latency and industrial IoT requirements, and also to terrestrial Low Power Wide Area systems (NB-IoT).
Specification support will be added to support lower capable NR devices, realizing the needs of certain commercial and industry segments for such features.

The combination to support lower capable NR devices, and enhancements done for NR coverage constitute key elements to enhance support for the Low Mobility Large Cell (LMLC) scenarios – an important scenario for the global success of 5G NR, in particular in developing countries.

3GPP RAN will now start normative work on 5G NR enhancements to support non-terrestrial access (NTN): satellites and High-Altitude Platforms (HAPs). Initial studies will be performed for IoT as well, paving the way to introduce both NB-IoT and eMTC support for satellites.

Radio protocol enhancements (RAN2)

In RAN2, the work starts in the second quarter of 2020. The necessary protocol enhancements for the newly added physical layer driven features will be added. The summary figure below shows the Release-17 content for RAN2 with the planned RAN2 time allocations (TU) in each quarter – note that these allocations may be revised at RAN#87 in March.

R2 TUs rel17

From April, RAN2 will also start working on features that continue to be important for overall efficiency and performance of 5G NR: Multiradio DC/CA enhancements, IAB enhancements, enhancements for small data transfer, UE Power Saving enhancements, SON/MDT enhancements.

As a new RAN2-led feature 3GPP will add support for Multicast transmissions, focusing on single-cell multicast functionality with clear evolution path towards multicell. It is important to note that multicast will entirely re-use the unicast NR physical layer to enhance the opportunity for an accelerated commercial uptake of multicast.

Multi-SIM devices have been extremely popular for LTE in many regions, these have been based on proprietary solutions. In order to have a more efficient and predictable Multi-SIM operation in NR RAN2 will work on specification enhancements, especially in the area of paging coordination.

Radio architecture enhancements (RAN3)

In RAN3, Release 17 will also start in the 2nd quarter of 2020. Architecture support will be added to all necessary RAN1- and RAN2-led features. The summary figure below shows the Release-17 content for RAN3 with the planned RAN3 time allocations (TU) in each quarter.

R3 TUs rel17

RAN3 will also address the QoE needs of 5G NR, initially starting with a study to understand how different the QoE function would need to be compared to what was specified for LTE.

The radio architecture of 5G NR is substantially more versatile than LTE through the split of gNB: Control- and Userplane split, as well as the split of Centralized Unit and Distributed Unit. RAN3 will now add support for CP-UP split to LTE to so that LTE networks can also take advantage of some of the advanced radio architecture functions of 5G.

Summary

Release 17 is perhaps the most versatile release in 3GPP history in terms of content. Still, the scope of each feature was carefully crafted so that the planned timelines can be met despite the large number of new features.

Source: https://www.3gpp.org/news-events/2098-5g-in-release-17-%E2%80%93-strong-radio-evolution
15 12 19

Today’s 4G LTE puts you on the pathway to tomorrow’s 5G

20 Oct

Phrases like 3G, 4G, and 5G draw definitive traces within the sand between one era and the following. In truth, the transition is way more sluggish. And since what we name 5G accommodates many functions, it’s turning into clearer that the era will impact our lives in numerous tactics, ramping up in magnitude through the years.

In the long run, 5G’s gigabit-class throughput, ultra-low latency, ultra-high reliability, and data-centric infrastructure will make it imaginable to use synthetic intelligence at an unparalleled scale. It’ll enhance the versatility of cloud computing, whilst developing new alternatives on the edge. And it’ll pave the way in which for a bigger collection of broadband IoT units, which is able to account for just about 35% of mobile IoT connections through 2024. Simply within the media business by myself, new products and services and programs enabled through 5G are anticipated to generate a cumulative $765 billion bucks between now and 2028.

5-year outlook

Whilst the adoption of 5G gained’t be so simple as flipping a transfer, we do have some sense of the transition’s tempo. If the merger between T-Cell and Dash is going via, 97% of the U.S. inhabitants is promised some type of 5G carrier from the New T-Cell inside 3 years of that deal final, together with 85% of people in rural spaces. The union of T-Cell and Dash additionally units forth a plan to determine Dish Networks as a fourth primary wi-fi provider along AT&T and Verizon, serving a minimum of 70% of the U.S. inhabitants with 5G through June 2023.

Between from time to time, 5G entry will proceed rolling out within the densest spaces and municipalities pleasant to the era’s infrastructure necessities, in step with a record printed through cloud-delivered wi-fi edge answer supplier Cradlepoint. Ericsson’s June 2019 Mobility Record forecasts 10 million 5G subscriptions international through the top of 2019. A quicker uptake in comparison to LTE would possibly lead to as many as 1.nine billion 5G subscriptions for enhanced cellular broadband through the top of 2024.

So does that imply you will have to dangle off on upgrading community infrastructure till 5G protection is in style? Now not essentially. In the similar record, Ericsson tasks the ongoing enlargement of LTE, culminating in a height of five.three billion subscriptions in 2022. There’s no doubt that LTE and 5G networks will perform in live performance for years yet to come.

Very best of all, there’s a pathway to 5G that guarantees a lot of the era’s price on current 4G LTE networks. As you run up towards programs begging for gigabit-class records charges and single-digit-millisecond latencies, a handful of knowledgeable upgrades could also be all you want to bridge the distance between what’s to be had now and whole 5G protection throughout your WAN.

ericsson june 2019 mobility report

Above: A 5G subscription is counted as such when related to a tool that helps New Radio (NR), as laid out in 3GPP Unlock 15, and is hooked up to a 5G-enabled community

How is 5G taking place lately?

Prior to we discover what you’ll be able to do now, let’s communicate a bit extra about how the era is rolling out lately. 5G is getting used to explain many various functions, frequency spectrums, or even use circumstances. They gained’t all be imaginable, and even fascinating, throughout 5G-capable units or on 5G networks. That is through design, regardless that.

Present 5G deployments are being pushed through mounted wi-fi entry and enhanced cellular broadband (eMBB), construction upon 4G LTE with extra to be had spectrum and wider bands to push considerably upper bandwidth. However every provider’s technique is moderately other.

Verizon, for instance, is specializing in the 28 GHz and 39 GHz frequencies, often known as millimeter wave, to reach large throughput and coffee latency. Alternatively, the restricted vary of the ones alerts may also be problematic, even within the dense city spaces the place Verizon already gives 5G carrier.

“You want to have 4 antennas, every on a special airplane, to give you the optimum line of sight connectivity to a 5G millimeter wave tower,” defined Todd Krautkremer, CMO at Cradlepoint. “Then you want some type of set up help, in all probability an software, that is helping consumers optimally place that instrument. Additionally it is most probably that you want an outside modem that mounts on a pole or aspect of a construction to verify you’ll be able to get connectivity since millimeter-wave alerts steadily combat to penetrate low-emissivity-glass, for instance.

Dash is the usage of extra 2.five GHz spectrum with huge MIMO antenna programs in the past deployed to improve its LTE carrier. That’s going to make it more uncomplicated for the corporate to succeed in extra consumers, albeit at decrease records charges. In reality, Verizon suggests a reliance on mid-band spectrum goes to make a large number of 5G approximate “excellent 4G carrier.”

Very similar to Verizon, T-Cell is approved for millimeter wave spectrum within the 28 GHz and 39 GHz bands. It’s additionally running to enlarge protection with 600 MHz low-band 5G. A merger with Dash would give each corporations entry to sources around the vary of frequencies utilized by 5G programs.

5G’s different use circumstances will take time to bake

Past the improved cellular broadband and stuck wi-fi entry stoning up in city markets, the advantages of 5G can even make it imaginable to ensure ultra-reliable low-latency communications (URLLC) for robotics, protection programs, self sustaining cars, and healthcare.

cradlepoint 5g use cases

Above: 5G use circumstances

This 2nd carrier class explained through the Global Telecommunication Union gifts a novel set of demanding situations since low latency and excessive reliability are steadily at odds with every different. However URLLC products and services are designed to take precedence a few of the different 5G use circumstances. They loosen up the emphasis on uncooked throughput with shorter messages, extra clever scheduling, and grant-free uplink entry, getting rid of latency that in the past went into combating interference from units transmitting on the identical time.

A 3rd use case, huge machine-type communique (mMTC), guarantees connectivity to dense swathes of sensors that aren’t essentially bandwidth-sensitive. They do, alternatively, require low continual intake, low charge, and dependable operation in a sea of heterogenous units working at the identical community.

5G’s eMBB carrier class appears so much like an evolution of 4G, paving the way in which for upper throughput and extra environment friendly use of to be had spectrum. The URLLC and mMTC categories are all in regards to the Web of Issues (IoT), the place machines, sensors, cameras, drones, and surgical gear interoperate in new and thrilling tactics. For a few of these units, the 99.99 reliability of 4G LTE programs]  is inadequate. Others stand to have the benefit of 5G’s non-orthogonal more than one entry (NOMA) era, supporting extra units in a given space than current low-power extensive space networks.

The eMBB-oriented model of 5G to be had lately, known as the non-standalone structure, permits carriers to make use of current community belongings to introduce 5G spectrums and spice up capability. It’s no longer the model that’ll sooner or later continual our sensible factories and attached automobiles, nevertheless it does lend a hand bridge lately’s truth and the following day’s alternatives, that are going to require a whole lot of infrastructure paintings.

Standalone 5G, with its cloud-native 5G Core and community reducing capability, is foundational to enabling the era’s 3 use circumstances. This subsequent section of 5G is an eventuality—without a doubt about that. However it’s nonetheless in a trying out section and gained’t even start rolling out till 2020. Getting ready now will make the transition more uncomplicated and assist you to get extra ROI out of your current WAN.

Getting the advantages of 5G in an LTE global

Figuring out the total 5G revel in isn’t going to contain flipping a transfer that makes all 3 use circumstances viable concurrently. In reality, a large number of the options integral to 5G are already elements of the most recent LTE requirements. It can be the case that appearing an improve lately will lend a hand with a transfer to 5G the following day.

“…gigabit-class LTE products and services in reality constitute, I might say, nearly 5G model zero.five, as a result of they begin to incorporate most of the identical foundational applied sciences as 5G,” mentioned Cradlepoint’s Krautkremer. “For instance, functions like 256-QAM—a modulation era, which is, ‘how the provider can stuff extra bits down a unmarried piece of spectrum.’ And four×four MIMO, which is, as we all know from the Wi-Fi global, ‘how can I am getting extra bits within the air from the brink instrument to the tower.’ Then now we have provider aggregation or CA, which takes us again to the inverse multiplexing days of, ‘how do I take a number of items of spectrum and mix them in combination to behave like one greater piece of spectrum?’ By way of leveraging those applied sciences inside gigabit LTE, carriers at the moment are ready to ship 150, 200, even 400 megabits in line with 2nd of mounted wi-fi and cellular connectivity on LTE networks.”

5g integration with 4g emf explained

Above: When a 5G connection is established, the Person Apparatus (or instrument) will hook up with each the 4G community to give you the keep watch over signaling and to the 5G community to lend a hand give you the speedy records connection through including to the prevailing 4G capability.

It’s going to take a little time for carriers to reach significant densification of millimeter wave radios, to get their backhaul able for 10 gigabits of wi-fi visitors, to refarm 3G and 4G spectrum, and to roll out multi-access edge computing for decrease latency. Companies looking forward to all that want extra connectivity, to strengthen video, backup, or extra endpoints. Fairly than looking forward to 5G to hide their complete footprint, present 4G answers are offering an intermediate step.

Krautkremer persisted, “The wonderful thing about it’s, now that 4G is being upgraded to have extra 5G-like efficiency functions with gigabit LTE, and 5G is beginning to deploy, corporations like Cradlepoint are telling consumers, ‘glance, we’ll put you at the pathway to 5G so you’ll be able to get 80% of the worth of 5G lately on a 4G gigabit LTE community for current programs that want quicker mounted wi-fi and cellular speeds.’ After which, as 5G turns into to be had to your community footprint and you need to benefit from it, we’re creating and participating on answers—whether or not it’s millimeter wave, mid-wave, or low-band—that may maintain your funding to your current router infrastructure and offers you entry to 5G when and the place you want it.”

The preservation Krautkremer is speaking about comes from community purposes virtualization (NFV) and a software-defined structure. Those ideas are integral to the deployment and control of 5G networks. They supplement every different, enabling variable 4G LTE or 5G workloads the usage of commonplace . That implies taking an off-the-shelf Xeon-based server and nearly spinning-up community products and services that will have in the past required single-purpose units and plenty of months of labor to deploy.

Making an investment in sensible foundations

In step with a white paper printed through A10 Networks, probably the most smartest investments you’ll be able to make into an current 4G community contain utility applied sciences that still lay the root for a 5G improve. Advanced community control gear are indexed because the single-most logical and cost-effective position to begin. A control and orchestration (MANO) framework, for instance,  offers you the versatility to deploy products and services as they transition from bodily home equipment to digital machines. Compute, garage, and networking sources turn into a lot more uncomplicated to transport and arrange.

The honour steadily made between 4G and 5G means that there’s an drawing close Giant Bang tournament poised to unfold next-gen protection all over the place. In truth, the transition goes to occur slowly, group through group, town through town. Within the interim, LTE and 5G will coexist. A few of lately’s most well liked modem-RF programs make that a lot transparent. In lately’s non-standalone model of 5G, which makes use of the keep watch over airplane of current LTE networks, they have got a connection to the 4G and 5G networks on the identical time, permitting you to dip out and in of 5G protection with out interrupting carrier.

“It in reality makes the purpose that 4G and 5G infrastructures are going to be round for a very long time, concluded Cradlepoint’s Krautkremer. “And that’s why carriers are upgrading their 4G infrastructure, to scale back the differential of functions between 4G and 5G in order that they may be able to be extra harmonious in combination than we’ve observed in any earlier evolution of wi-fi era.”

Innovation at the Telco Edge

31 Aug

Imagine watching the biggest football game of the year being streamed to your Virtual Reality headset, and just as your team is about to score, your VR headset freezes due to latency in the network, and you miss the moment!

While this may be a trivial inconvenience, there are other scenarios that can have serious consequential events such as a self-driving car not stopping at a stop sign because of high latency networks.

The rapid growth of applications and services such as Internet of Things, Vehicle to Everything communications and Virtual Reality is driving the massive growth of data in the network that will demand real-time processing at the edge of the network closer to the user that will deliver faster speeds and reduced latency when compared to 4G LTE networks.

Edge computing will be critical in ensuring that low-latency and high reliability applications can be successfully deployed in 4G and 5G networks.

For CSPs, deploying a distributed cloud architecture where compute power is pushed to the network edge, closer to the user or device, offers improved performance in terms of latency, jitter, and bandwidth and ultimately a higher Quality of Experience.

Delivering services at the edge will enable CSPs to realize significant benefits, including:

  • Reduced backhaul traffic by keeping required traffic processing and content at the edge instead of sending it back to the core data center
  • New revenue streams by offering their edge cloud premises to 3rd party application developers allowing them to develop new innovative services
  • Reduced costs with the optimization of infrastructure being deployed at the edge and core data centers
  • Improved network reliability and application availability

Edge Computing Use Cases

According to a recent report by TBR, CSP spend on Edge compute infrastructure will grow at a 76.5% CAGR from 2018 to 2023 and exceed $67B in 2023.  While AR/VR/Autonomous Vehicle applications are the headlining edge use cases, many of the initial use cases CSPs will be deploying at the edge will focus on network cost optimization, including infrastructure virtualization, real estate footprint consolidation and bandwidth optimization. These edge use cases include:

Mobile User Plane at the Edge

A Control Plane and User Plane Separation (CUPS) architecture delivers the ability to scale the user plane and control plane independent of each other.  Within a CUPS architecture, CSPs can place user plane functionality closer to the user thereby providing optimized processing and ultra-low latency at the edge, while continuing to manage control plane functionality in a centralized data center.  An additional benefit for CSPs is the reduction of backhaul traffic between the end device and central data center, as that traffic can be processed right at the edge and offloaded to the internet when necessary.

Virtual CDN

Content Delivery Network was one of the original edge use cases, with content cached at the edge to provide an improved subscriber user experience.  However, with the exponential growth of video content being streamed to devices, the scaling of dedicated CDN hardware can become increasingly difficult and expensive to maintain.  With a Virtualized CDN (vCDN), CSPs can deploy capacity at the edge on-demand to meet the needs of peak events while maximizing infrastructure efficiency while minimizing costs.

Private LTE

Enterprise applications such as industrial manufacturing, transportation, and smart city applications have traditionally relied on Wi-Fi and fixed-line services for connectivity and communications.  These applications require a level of resiliency, low-latency and high-speed networks that cannot be met with existing network infrastructure. To deliver a network that can provide the flexibility, security and reliability, CSPs can deploy dedicated mobile networks (Private LTE) at the enterprise to meet the requirements of the enterprise.  Private LTE deployments includes all the data plane and control plane components needed to manage a scaled-out network where mobile sessions do not leave the enterprise premises unless necessary.

VMware Telco Edge Reference Architecture

Fundamentally, VMware Telco Edge is based on the following design principles:

  • Common Platform

VMware provides a flexible deployment architecture based on a common infrastructure platform that is optimized for deployments across the Edge data centers and Core data centers.  With centralized management and a single pane of glass for monitoring network infrastructure across the multiple clouds, CSPs will have consistent networking, operations and management across their cloud infrastructure.

  • Centralized Management

VMware Telco Edge is designed to have a centralized VMware Integrated OpenStack VIM at the core data center while the edge sites do not need to have any OpenStack instances.  With zero OpenStack components present at the Edge sites, CSPs will gain massive improvements in network manageability, upgrades, scale, and operational overhead. This centralized management at the Core data center gives CSPs access to all the Edge sites without having to connect to individual Edge sites to manage their resources.

  • Multi-tenancy and Advanced Networking

Leveraging the existing vCloud NFV design, the Telco Edge can be deployed in a multi-tenant environment with resource guarantees and resource isolation with each tenant having an independent view of their network and capacity and management of their underlying infrastructure and overlay networking. The Edge sites support overlay networking which makes them easier to configure and offers zero trust through NSX multi-segmentation.

  • Superior Performance

VMware NSX managed Virtual Distributed Switch in Enhanced Data Path mode (N-VDS (E)) leverages hardware-based acceleration (SR-IOV/Direct-PT) and DPDK techniques to provide the fastest virtual switching fabric on vSphere. Telco User Plane Functions (UPFs) that require lower latency and higher throughput at the Edge sites can run on hosts configured with N-VDS (E) for enhanced performance.

  • Real-time Integrated Operational Intelligence

The ability to locate, isolate and provide remediation capabilities is critical given the various applications and services that are being deployed at the edge. In a distributed cloud environment, isolating an issue is further complicated given the nature of the deployments.   The Telco Edge framework uses the same operational model as is deployed in the core network and provides the capability to correlate, analyze and enable day 2 operations.  This includes providing continuous visibility over service provisioning, workload migrations, auto-scaling, elastic networking, and network-sliced multitenancy that spans across VNFs, clusters and sites.

  • Efficient VNF onboarding and placement

Once a VNF is onboarded, the tenant admin deploys the VNF to either the core data center or the edge data center depending on the defined policies and workload requirements. VMware Telco Edge offers dynamic workload placement ensuring the VNF has the right number of resources to function efficiently.

  • Validated Hardware platform

VMware and Dell Technologies have partnered to deliver validated solutions that will help CSPs deploy a distributed cloud architecture and accelerate time to innovation.  Learn more about how VMware and Dell Technologies have engineered and created a scalable and agile platform for CSPs.

Learn More

Edge computing will transform how network infrastructure and operations are deployed and provide greater value to customers.  VMware has published a Telco Edge Reference Architecture that will enable CSPs to deploy an edge-cloud service that can support a variety of edge use cases along with flexible business models.

Source: https://blogs.vmware.com/telco/

An overview of the 3GPP 5G security standard

21 Aug

Building the inherently secure 5G system required a holistic effort, rather than focusing on individual parts in isolation. This is why several organizations such as the 3GPP, ETSI, and IETF have worked together to jointly develop the 5G system, each focusing on specific parts. Below, we present the main enhancements in the 3GPP 5G security standard.

Crowd crossing street

These enhancements come in terms of a flexible authentication framework in 5G, allowing the use of different types of credentials besides the SIM cards; enhanced subscriber privacy features putting an end to the IMSI catcher threat; additional higher protocol layer security mechanisms to protect the new service-based interfaces; and integrity protection of user data over the air interface.

Overview: Security architecture in 5G and LTE/4G systems

As shown in the figure below, there are many similarities between LTE/4G and 5G in terms of the network nodes (called functions in 5G) involved in the security features, the communication links to protect, etc. In both systems, the security mechanisms can be grouped into two sets.

  • The first set contains all the so-called network access security mechanisms. These are the security features that provide users with secure access to services through the device (typically a phone) and protect against attacks on the air interface between the device and the radio node (eNB in LTE and gNB in 5G)
  • The second set contains the so-called network domain security mechanisms. This includes the features that enable nodes to securely exchange signaling data and user data for example between radio nodes and core network nodes
Figure 1_Simplified security architectures of LTE and 5G

Figure 1: Simplified security architectures of LTE and 5G showing the grouping of network entities that needs to be secured in the Home Network and Visited Network and all the communication links that must be protected.

New authentication framework

A central security procedure in all generations of 3GPP networks is the access authentication, known as primary authentication in 3GPP 5G security standards. This procedure is typically performed during initial registration (known as initial attach in previous generations), for example when a device is turned on for the first time.

A successful run of the authentication procedure leads to the establishment of sessions keys, which are used to protect the communication between the device and the network. The authentication procedure in 3GPP 5G security has been designed as a framework to support the extensible authentication protocol (EAP) – a security protocol specified by the Internet Engineering Task Force (IETF) organization. This protocol is well established and widely used in IT environments.

The advantage of this protocol is that it allows the use of different types of credentials besides the ones commonly used in mobile networks and typically stored in the SIM card, such as certificates, pre-shared keys, and username/password. This authentication method flexibility is a key enabler of 5G for both factory use-cases and other applications outside the telecom industry.

The support of EAP does not stop at the primary authentication procedure, but also applies to another procedure called secondary authentication. This is executed for authorization purposes during the set-up of user plane connections, for example to surf the web or to establish a call. It allows the operator to delegate the authorization to a third party. The typical use case is the so-called sponsored connection, for example towards your favorite streaming or social network site and where other existing credentials (e.g. username/password) can be used to authenticate the user and authorize the connection. The use of EAP allows to cater to the wide variety of credentials types and authentication methods deployed and used by common application and service providers.

Enhanced subscriber privacy

Security in the 3GPP 5G standard significantly enhances protection of subscriber privacy against false base stations, popularly known as IMSI catchers or Stingrays. In summary, it has been made very impractical for false base stations to identify and trace subscribers by using conventional attacks like passive eavesdropping or active probing of permanent and temporary identifiers (SUPI and GUTI in 5G). This is detailed in our earlier blog post about 5G cellular paging security, as well as our earlier post published in June 2017.

In addition, 5G is proactively designed to make it harder for attackers to correlate protocol messages and identify a single subscriber. The design is such that only a limited set of information is sent as cleartext even in initial protocol messages, while the rest is always concealed. Another development is a general framework for detecting false base stations, a major cause for privacy concerns. The detection, which is based on the radio condition information reported by devices on the field, makes it considerably more difficult for false base stations to remain stealthy.

Service based architecture and interconnect security

5G has brought about a paradigm shift in the architecture of mobile networks, from the classical model with point-to-point interfaces between network function to service-based interfaces (SBI). In a service-based architecture (SBA), the different functionalities of a network entity are refactored into services exposed and offered on-demand to other network entities.

The use of SBA has also pushed for protection at higher protocol layers (i.e. transport and application), in addition to protection of the communication between core network entities at the internet protocol (IP) layer (typically by IPsec). Therefore, the 5G core network functions support state-of-the-art security protocols like TLS 1.2 and 1.3 to protect the communication at the transport layer and the OAuth 2.0 framework at the application layer to ensure that only authorized network functions are granted access to a service offered by another function.

The improvement provided by 3GPP SA3 to the interconnect security (i.e. security between different operator networks) consists of three building blocks:

  • Firstly, a new network function called security edge protection proxy (SEPP) was introduced in the 5G architecture (as shown in figure 2). All signaling traffic across operator networks is expected to transit through these security proxies
  • Secondly, authentication between SEPPs is required. This enables effective filtering of traffic coming from the interconnect
  • Thirdly, a new application layer security solution on the N32 interface between the SEPPs was designed to provide protection of sensitive data attributes while still allowing mediation services throughout the interconnect

The main components of SBA security are authentication and transport protection between network functions using TLS, authorization framework using OAuth2, and improved interconnect security using a new security protocol designed by 3GPP.

Figure 2: Simplified service-based architecture for the 5G system in the roaming case

Figure 2: Simplified service-based architecture for the 5G system in the roaming case

Integrity protection of the user plane

In 5G, integrity protection of the user plane (UP) between the device and the gNB, was introduced as a new feature. Like the encryption feature, the support of the integrity protection feature is mandatory on both the devices and the gNB while the use is optional and under the control of the operator.

It is well understood that integrity protection is resource demanding and that not all devices will be able to support it at the full data rate. Therefore, the 5G System allows the negotiation of which rates are suitable for the feature. For example, if the device indicates 64 kbps as its maximum data rate for integrity protected traffic, then the network only turns on integrity protection for UP connections where the data rates are not expected to exceed the 64-kbps limit.

Learn more about security standardization

The security aspects are under the remits of one of the different working groups of 3GPP called SA3. For the 5G system, the security mechanisms are specified by SA3 in TS 33.501. Ericsson has been a key contributor to the specification work and has driven several security enhancements such as flexible authentication, subscriber privacy and integrity protection of user data.

Learn more about our work across network standardization.

Explore the latest trending security content on our telecom security page.

Source: https://www.ericsson.com/en/blog/2019/7/3gpp-5g-security-overview

Private 5G Mobile Networks for Industrial IoT

31 Jul

Afbeeldingsresultaat voor 5g netwerk

Dedicated 5G campus networks, designed to meet the coverage, performance and security requirements of industrial users, are one of the most exciting — and tangible — advanced 5G use-cases under development.

Part of the reason for this is that the private mobile network market in general is taking-off. These networks enable enterprises to optimize and redefine business processes in ways that are not possible, or are impractical, within the limitations of wired and WiFi networks, and also cannot be reliably served by wide-area cellular. Right now, this means using LTE technology. Backed by a robust ecosystem of suppliers and integrators, private LTE is a growth market, with deployment activity across diverse industry sectors in all global regions.

Looking one step farther out, however, to scenarios where users have more demanding performance requirements — for example, the cyber-physical systems that characterize Industry 4.0. — and 5G technology comes into the picture, offering an investment path that can support these new-wave applications at scale. Building on the existing LTE ecosystem, private 5G campus networks are emerging to address the performance requirements of production-critical processes in sectors such as smart factories, logistics/warehouses, container ports, oil & gas production, chemical plants, energy generation and distribution and more.

In my new white paper, “Private 5G Networks for Industrial IoT,” I discuss how 5G technology meets the performance requirements of industrial users and why it will integrate with the next generation of Operational Technologies (OT) used in these markets. The paper discusses how private 5G can be deployed across licensed, shared-licensed and unlicensed spectrum bands, and investigates key 5G radio innovations. Specifically, it addresses the use of time synchronization in shared spectrum to ensure predictable performance.

Among the key findings in the paper — available for download here — are:

  • The strategic importance of private networks is reflected in 5G R&D. Whereas in previous generations, private networking was an add-on capability to public cellular; in 5G these requirements are addressed directly in the initial specification phase.
  • The first 5G standards release (3GPP Release 15) contains many of the critical features that will underpin the performance needed in the industrial IoT segment. In addition, to support the advanced capabilities needed for cyber-physical industrial communication networks, an enormous amount of work is underway in Release 16, scheduled for functional freeze in March 2020 and ASN.1 freeze (i.e. protocols stable) in June 2020.
  • 5G offers the opportunity to consolidate industrial networking complexity onto a common network platform. An example is the cross-industry effort to transition diverse fieldbuses to the Time Sensitive Networking (TSN) Ethernet standard, and the mapping of TSN requirements to the 5G system specifications, such that a 5G campus network can transport TSN within the required latency, jitter and timing bounds.
  • There are a range of spectrum options that will accelerate private network adoption. In some markets, regulators are investigating, or already allocating, dedicated spectrum to enterprises to run private networks; these allocations are often targeted at industrial verticals.
  • Unlicensed spectrum is also attractive, with new radio techniques emerging to increase reliability in shared bands. Time synchronized sharing in unlicensed spectrum, in combination with other advanced 5G radio capabilities, can deliver highly predictable performance.
  • Heavy Reading believes spectrum will, in many cases, be de-coupled from the decision about which party designs, operates and maintains private networks. There is evidence that operators themselves see opportunities in dedicated enterprise spectrum and are preparing to offer manged private networks in these bands. Other active parties include systems integrators and specialist OT companies.
  • In the radio domain, multiple techniques are under development to will enable 5G to meet extreme industrial IoT performance requirements. These include flexible numerology, ultra-reliable low-latency communications (URLLC), spatial diversity, Coordinated MultiPoint (CoMP), cm-accurate positioning, QoS, spectrum flexibility (including NR-Unlicensed), etc.
  • At the system level, capabilities such as network slicing, improved security, new authentication methods, edge-cloud deployment, TSN support (with synchronization) and API exposure make 5G suitable for the private industrial IoT market

The investment the global 3GPP community — which includes leading technology vendors, research organizations and network operators — is making in industrial IoT is very significant. This multi-year commitment draws deeply on R&D capabilities at these organizations and creates confidence in the technology and roadmap.

Source: https://www.lightreading.com/mobile/5g/private-5g-mobile-networks-for-industrial-iot/a/d-id/753123

International Telecommunications Union Releases Draft Report on the 5G Network

1 Mar

2017 is another year in the process of standardising IMT-2020, aka 5G network communications. The International Telecommunications Union (ITU) has released a draft report setting out the technical requirements it wants to see next in the spectrum of  communications.

5G network needs to consolidate existing technical prowess

The draft specifications call for at least 20Gbp/s down and 10Gbp/s up at each base station. This won’t be the speed you get, unless you’re on a dedicated point-to-point connection, instead all the users on the station will split the 20 gigabits.

Each area has to cover 500km sq, with the ITU also calling for a minimum connection density of 1 million devices per square kilometer. While there are a lot of laptops, mobile phones and tablets in the world this is capacity is for the expansion of networked, Internet of Things, devices. The everyday human user can expect speeds of 100mbps download and 50mbps upload. These speeds are similar to what is available on some existing LTE networks some of the time. 5G is to be a consolidation of this speed and capacity.

5G communications framework
Timeline for the development and deployment of 5G

Energy efficiency is another topic of debate within the draft. Devices should be able to switch between full-speed loads and battery-efficient states within 10ms. Latency should decrease to within the 1-4ms range. Which is a quarter of the current LTE cell speed. Ultra-reliable low latency communications (URLLC) will make our communications more resilient and effective.

When we think about natural commons the places and resources are usually rather ecological. Forests, oceans, our natural wealth is very tangible in the mind of the public. Less acknowledged is the commonality of the electromagnetic spectrum. The allocation of this resource brings into question more than just faster speeds but how much utility we can achieve. William Gibson said that the future is here but it isn’t evenly distributed yet. 5G has the theoretical potential to boost speeds, but its real utility is the consolidate the gains of its predecessors and make them more widepsread.

Source: http://www.futureofeverything.io/2017/02/28/international-telecommunications-union-releases-draft-report-5g-network/

5G specs announced: 20Gbps download, 1ms latency, 1M devices per square km

26 Feb

The total download capacity for a single 5G cell must be at least 20Gbps, the International Telcommunication Union (ITU) has decided. In contrast, the peak data rate for current LTE cells is about 1Gbps. The incoming 5G standard must also support up to 1 million connected devices per square kilometre, and the standard will require carriers to have at least 100MHz of free spectrum, scaling up to 1GHz where feasible.

These requirements come from the ITU’s draft report on the technical requirements for IMT-2020 (aka 5G) radio interfaces, which was published Thursday. The document is technically just a draft at this point, but that’s underselling its significance: it will likely be approved and finalised in November this year, at which point work begins in earnest on building 5G tech.

I’ll pick out a few of the more interesting tidbits from the draft spec, but if you want to read the document yourself, don’t be scared: it’s surprisingly human-readable.

5G peak data rate

The specification calls for at least 20Gbps downlink and 10Gbps uplink per mobile base station. This is the total amount of traffic that can be handled by a single cell. In theory, fixed wireless broadband users might get speeds close to this with 5G, if they have a dedicated point-to-point connection. In reality, those 20 gigabits will be split between all of the users on the cell.

5G connection density

Speaking of users… 5G must support at least 1 million connected devices per square kilometre (0.38 square miles). This might sound like a lot (and it is), but it sounds like this is mostly for the Internet of Things

, rather than super-dense cities. When every traffic light, parking space, and vehicle is 5G-enabled, you’ll start to hit that kind of connection density.

5G mobility

Similar to LTE and LTE-Advanced, the 5G spec calls for base stations that can support everything from 0km/h all the way up to “500km/h high speed vehicular” access (i.e. trains). The spec talks a bit about how different physical locations will need different cell setups: indoor and dense urban areas don’t need to worry about high-speed vehicular access, but rural areas need to support pedestrians, vehicular, and high-speed vehicular users.

5G energy efficiency

The 5G spec calls for radio interfaces that are energy efficient when under load, but also drop into a low energy mode quickly when not in use. To enable this, the control plane latency should ideally be as low as 10ms—as in, a 5G radio should switch from full-speed to battery-efficient states within 10ms.

5G latency

Under ideal circumstances, 5G networks should offer users a maximum latency of just 4ms, down from about 20ms on LTE cells. The 5G spec also calls for a latency of just 1ms for ultra-reliable low latency communications (URLLC).

5G spectral density

It sounds like 5G’s peak spectral density—that is, how many bits can be carried through the air per hertz of spectrum—is very close to LTE-Advanced, at 30bits/Hz downlink and 15 bits/Hz uplink. These figures are assuming 8×4 MIMO (8 spatial layers down, 4 spatial layers up).

5G real-world data rate

Finally, despite the peak capacity of each 5G cell, the spec “only” calls for a per-user download speed of 100Mbps and upload speed of 50Mbps. These are pretty close to the speeds you might achieve on EE’s LTE-Advanced network, though with 5G it sounds like you will always get at least 100Mbps down, rather than on a good day, down hill, with the wind behind you.

The draft 5G spec also calls for increased reliability (i.e. packets should almost always get to the base station within 1ms), and the interruption time when moving between 5G cells should be 0ms—it must be instantaneous with no drop-outs.

Enlarge / The order of play for IMT-2020, aka the 5G spec.

The next step, as shown in the image above, is to turn the fluffy 5G draft spec into real technology. How will peak data rates of 20Gbps be achieved? What blocks of spectrum will 5G actually use? 100MHz of clear spectrum is quite hard to come by below 2.5GHz, but relatively easy above 6GHz. Will the connection density requirement force some compromises elsewhere in the spec? Who knows—we’ll find out in the next year or two, as telecoms and chip makers

Source: http://126kr.com/article/15gllhjg4y

A total of 192 telcos are deploying advanced LTE technologies

15 Aug

A total of 521 operators have commercially launched LTE, LTE-Advanced or LTE-Advanced Pro networks in 170 countries, according to a recent report focused on the state of LTE network reach released by the Global mobile Suppliers Association.

In 2015, 74 mobile operators globally launched 4G LTE networks, GSA said. Bermuda, Gibraltar, Jamaica, Liberia, Myanmar, Samoa and Sudan are amongst the latest countries to launch 4G LTE technology.

The report also reveals that 738 operators are currently investing in LTE networks across 194 countries. This figure comprises 708 firm network deployment commitments in 188 countries – of which 521 networks have launched – and 30 precommitment trials in another 6 countries.

According to the GSA, active LTE network deployments will reach 560 by the end of this year.

A total of 192 telcos, which currently offer standard LTE services, are deploying LTE-A or LTE-A Pro technologies in 84 countries, of which 147 operators have commercially launched superfast LTE-A or LTE-A Pro wireless broadband services in 69 countries.

“LTE-Advanced is mainstream. Over 100 LTE-Advanced networks today are compatible with Category 6 (151-300 Mbps downlink) smartphones and other user devices. The number of Category 9 capable networks (301-450 Mbps) is significant and expanding. Category 11 systems (up to 600 Mbps) are commercially launched, leading the way to Gigabit service being introduced by year-end,” GSA Research VP Alan Hadden said.

The GSA study also showed that the 1800 MHz band continues to be the most widely used spectrum for LTE deployments. This frequency is used in 246 commercial LTE deployments in 110 countries, representing 47% of total LTE deployments. The next most popular band for LTE systems is 2.6 GHz, which is used in 121 networks. Also, the 800 MHz band is being used by 119 LTE operators.

A total of 146 operators are currently investing in Voice over LTE deployments, trials or studies in 68 countries, according to the study. GSA forecasts there will be over 100 LTE network operators offering VoLTE service by the end of this year.

Unlicensed spectrum technologies boost global indoor small cell market

In related news, a recent study by ABI Research forecasts that the global indoor small cell market will reach revenue of $1.8 billion in 2021, manly fueled by increasing support for unlicensed spectrum technologies, including LTE-License Assisted Access and Wi-Fi.

The research firm predicts support for LTE-based and Wi-Fi technologies using unlicensed spectrum within small cell equipment will expand to comprise 51% of total annual shipments by 2021 at a compound annual growth rate of 47%

“Unlicensed LTE (LTE-U) had a rough start, meeting negative and skeptic reactions to its possible conflict with Wi-Fi operations in the 5 GHz bands. But the ongoing standardization and coexistence efforts increased the support in the technology ecosystem,” said Ahmed Ali, senior analyst at ABI Research.

“The dynamic and diverse nature of indoor venues calls for an all-inclusive small cell network that intelligently adapts to different user requirements,” the analyst added. “Support for multioperation features like 3G/4G and Wi-Fi/LAA access is necessary for the enterprise market.”

Source: http://www.rcrwireless.com/20160815/asia-pacific/gsa-reports-521-lte-deployments-170-countries-tag23
LTE network

A Pre-Scheduling Mechanism in LTE Handover for Streaming Video

21 Mar

This paper focuses on downlink packet scheduling for streaming video in Long Term Evolution (LTE). As a hard handover is adopted in LTE and has the period of breaking connection, it may cause a low user-perceived video quality. Therefore, we propose a handover prediction mechanism and a pre-scheduling mechanism to dynamically adjust the data rates of transmissions for providing a high quality of service (QoS) for streaming video before new connection establishment. Advantages of our method in comparison to the exponential/proportional fair (EXP/PF) scheme are shown through simulation experiments.

1. Introduction

For improving a low transmission rate of the 3G technologies, LTE (Long Term Evolution) was designed as a next-generation wireless system by the 3rd Generation Partnership Project (3GPP) to enhance the transmission efficiency in mobile networks [1,2]. LTE is a packet-based network, and information coming from many users is multiplexed in time and frequency domains. Many different downlink packet schedulers are proposed and utilized to optimize the network throughput [3,4]. There are three typical strategies: (1) round robin (RR), (2) maximum rate (MR) and (3) proportional fair (PF). The RR scheme is a fair scheduler, in which every user has the same priority for transmissions, but the RR scheme may lead to low throughput. MR aims to maximize the system throughput by selecting the user with the best channel condition (the largest bandwidth) such as by comparing the signal to noise ratio (SNR) values. Moreover, the PF mechanism utilizes link adaptation (LA) technology. It compares the current channel rate with the average throughput for each user and selects the one with the largest value. However, these methods only consider non-real-time data transmissions. Therefore, some packet schedulers are proposed based on PF algorithm for real-time data transmissions [5,6]. In one study [5], a Maximum-Largest Weighted Delay First (M-LWDF) algorithm is proposed. In addition to data rate, M-LWDF takes weights of the head-of-line (HOL) packet delay (between current time and the arrival time of a packet) into consideration. It also combines HOL packet delay with the PF algorithm to achieve a good throughput and fairness. In another study [6], an exponential/proportional fair (EXP/PF) is proposed. EXP/PF is designed for both real-time and non-real time traffic. Compared to M-LWDF, the average HOL packet delay is also taken into account. Because of the consideration of packet delay time, M-LWDF and EXP/PF can achieve higher performance than the other mechanisms in real-time transmissions [7]. Other schedulers for real-time data transmissions are as follows. In one study [8], two semi-persistent scheduling (SPS) algorithms are proposed to achieve a high reception ratio in real-time transmission. It also utilizes wide-band time-average signal-to-interference-plus-noise ratios (SINR) information for physical resource blocks (PRBs) allocation to improve the performance of large packet transmissions. In another study [9], the mechanism provides fairness-aware downlink scheduling for different types of packets. Three queues are utilized for data transmission arrangement according to the different priority needs. If a user is located near cell′s edge, his services may not be accepted. This may still cause starvation and fairness problems. In yet another study [10], a two-level downlink scheduling is proposed. The mechanism utilizes a discrete control theory and a proportional fair scheduler in upper-level and lower level, respectively. Results show that the strategy is suitable for real-time video flows. However, most schedulers do not improve low transmission rates during the LTE handover procedure and meet the needs of video quality for users.
The scalable video coding (SVC) is a key technology for spreading streaming video over the internet. SVC can dynamically adapt the video quality to the network state. It divides a video frame into one base layer (BL) and number of enhancement layers (ELs). The BL includes the most important information of the original frame and must be used by a user for playing a video frame. Although ELs can be added to the base layer to further enhance the quality of coded video, it may not be essential. Therefore, in this paper, we propose a pre-scheduling mechanism to determine the transmission rates of BL and EL, especially focusing on the BL transmissions, before a new connection handover for providing high quality of service (QoS) for streaming video.

2. Pre-Scheduling Mechanism

Our proposed mechanism is divided into two phases: (1) handover prediction and (2) pre-scheduling mechanism.

2.1. Handover Prediction

Handover determination generally depends on the degradation of the Reference Signal Receiving Power (RSRP) from the base station (eNodeB). When the threshold value is reached, a handover procedure is triggered. Many works have focused on handover decisions [11,12,13,14,15,16]. In this paper, user measures RSRP periodically with neighbor eNodeBs. In addition, we use exponential smoothing (ES) to remove high-frequency random noise (Figure 1), where α is a smoothing constant. Then, we incorporate a linear regression model with RSRP values to predict time-to-trigger (TTT) for handover.

Figure 1. Exponential smoothing (α = 0.2).
The linear regression equation can be simply expressed as follows:

Pˆi=a+bti, i=1, 2, , n
(1)

where Pˆi is the predictive value of RSRP at time ti, and a and b are coefficients of the linear regression equation. Then, we use the least squares (LS) method to deduce a and b. The method of LS is a standard solution to estimate the coefficient in linear regression analysis.

Let the sum of the residual squares be S, that is

S=ni=1[Pi(a+bti)]2
(2)

where Pi is the measured value of RSRP at time ti. The least squares method is to try to find the minimum of S, and then the minimum of S is determined by calculating the partial derivatives.

Let⎧⎩⎨⎪⎪⎪⎪pa=ni=12[Pi(a+bti)](1)=0pb=ni=12[Pi(a+bti)](ti)=0
(3)
Finally we can get

⎧⎩⎨⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪a =P¯¯¯bt¯b = ni=1tiPinTP¯¯¯¯¯ni=1ti2nT¯¯¯2
(4)

where T¯¯¯= ni=1tin and P¯¯¯= ni=1Pin. If there are several neighbor eNodes, we select the eNodeB with the maximum variation of RSRP (maximum slope) as target eNodeB. In Figure 2a, we can see that while RSRPSeNB=RSRPTeNB, the handover procedure is triggered. We have trigger time tt=a1a2b2b1.

Figure 2. Prediction for (a) time-to-trigger (TTT) of handover and (b) amount of data transmitted before handover.

2.2. Pre-Scheduling Mechanism

The BL is necessary for the video stream to be decoded. ELs are utilized to improve stream quality. Therefore, for high QoS for video streaming, we calculate the total number of BL that is required in a handover period for maintaining high QoS for video streaming.

NBL=(tr+tho+tn)×Ks×m
(5)

where tr is the time interval from scheduling to starting handover (pre-scheduling time for handover). The starting time of scheduling is adjustable, and we will evaluate it in our simulation later. tho is the time during handover procedure. tn is the delay time before new transmission (preparation time of scheduling with new eNodeB). Ks is the required number of video frames per second and m is the number of BL that is needed in each video frame. In Figure 2b, according to transmission data rate of the serving eNodeB, we construct a linear regression line dx(t). Then, the amount of BL’s data (transmitted from serving eNodeB and stored in the buffer of users) before handover has to be no less than NBL.

thandovertnowdx(t)dtNBL
(6)

where thandover is the TTT for handover. In the above inequality, the left part is the amount of data that the serving eNodeB can transmit before handover. According to the serving eNodeB capacity of transmission, we can dynamically adjust the transmission rate between BL and ELs. In Equation (6), while the inequality does not hold, it means the serving eNodeB cannot provide enough data for BL for maintaining high QoS for video streaming. Accordingly, the serving eNodeB merely transmits data for BL. On the contrary, while the inequality holds, the serving eNodeB can provide the data of BL and ELs simultaneously for desired quality of video service. In the following, we describe our mechanism of data rate adjustment between BL and ELs. The transmission rates of the BL and ELs are decreasing because the RSRP is degrading between the previous serving eNodeB and user. Hence, by the regression line dx(t), we can define the total descent rate s(slope) of transmissions as

s=ΔyΔx
(7)
In Figure 3, because of the decreasing RSRP, the transmission rates of BL and EL are also decreasing with time unit respectively. Then, we let per time unit be tunit, that is,

t0= t1=t2=t3==ti=tunit
(8)
Figure 3. The data rate of (a) BL and (b) EL under degrading RSRP.
Because of the limitative transmission rate of the serving eNodeB during a certain time interval, we have

tunit(dBL,i+dEL,i)0+tunit(i+1)0+tunitidx(t)dt 
(9)

where dBL,i and dEL,i are the transmitted number of BL and ELs during time interval ti, respectively. In Equation (9), the total transmitted number for streaming video (left part) is necessarily less than or equal to the total number of data the serving eNodeB can provide (right part). Thus, the total descent rate of transmission per tunit can be calculated as stunit. In this paper, for high QoS for video streaming, BL data has high priority for transmission. Furthermore, to achieve dynamically adjusting the transmission rate between BL and EL, we define the descent rate as

Ki=dEL,0dBL,0
(10)
Ki is the proportion of the transmission rate between EL and BL during the time interval. That is, the transmission rate of BL is written as

stunit1Ki+1
(11)
Then, we calculate the transmission rate of BL in each time unit

dBL,0dBL,1=dBL,0+stunit1Ki+1dBL,2=dBL,1+stunit1Ki+1=dBL,0+2s tunit1Ki+1dBL,3=dBL,2+stunit1Ki+1=dBL,0+3s tunit1Ki+1dBL,i=dBL,0+is tunit1Ki+1=dBL,0+i s tunitKi+1
(12)
Finally, we can calculate the total transmitted BL data from time t0 to tr (pre-scheduling time before handover)

tunit[dBL,0+dBL,1+dBL,2++dBL,i]=tunit[dBL,0+dBL,1+dBL,2++dBL,(trtunit1)]=tunit[dBL,0+dBL,0+s tunitKi+1+dBL,0+2s tunitKi+1+]=tunit⎡⎣⎢trtunitdBL,0+(trtunit1+1)(trtunit1)2s tunitKi+1⎤⎦⎥=tunit⎡⎣⎢trtunitdBL,0+trs(trtunit1)2(Ki+1)⎤⎦⎥=trdBL,0+trs(trtunit)2(Ki+1)
(13)
The total transmission number of BL is required to be no less than the number of BL for maintaining high QoS for video streaming, that is,

trdBL,0+trs(trtunit)2(Ki+1)(tr+tho+tn)×Ks×m
(14)
Finally, we have

dBL,0s(trtunit)2(Ki+1)+(1+tho+tntr)×Ks×m
(15)
In Equation (15), because s, tunit,tho, tn, Ks, and m are pre-defined values, we only consider Ki, tr and dBL,0 in the following simulations. In this paper, for maintaining high QoS for video streaming, the BL data transmission must be given precedence over the EL data. Therefore, dBL,0 value can be determined in advance. Due to the limitation of the total number of data the serving eNodeB can provide, dEL,0 also can be determined. Eventually, Ki is decided for BL and EL transmissions. A sufficient tr represents that more pre-scheduling time can be utilized for transmitting EL data to enhance video quality. On the contrary, BL transmissions are increased to achieve high QoS for video streaming.
Research manuscripts reporting large datasets that are deposited in a publicly available database should specify where the data have been deposited and provide the relevant accession numbers. If the accession numbers have not yet been obtained at the time of submission, please state that they will be provided during review. They must be provided prior to publication.

3. Performance Evaluation

3.1. The Effect of the Prediction Mechanism

We evaluate our scheme through simulations implemented in the LTE-Sim [17] simulator. LTE-Sim can provide a thorough performance verification of LTE networks. We also utilize Video Trace Library [18] with LTE-Sim to present real-time streaming video for network performance evaluations. The simulation parameters are summarized as Table 1.

Table 1. Parameters of simulation.
The accuracy of handover prediction affects the pre-scheduling time (tr) for BL and EL transmission rate. In Figure 4, as user equipments (UEs) velocity is 30 km/h and the actual TTT of handover is 79.924 s, we can have an error rate smaller than 0.8% while the prediction is made after 59 s. On the other hand, as UE velocity is 120 km/h, the actual TTT of handover is 25.981 s and the error rate can be contained smaller than 0.5% as the prediction is made after 15 s. Faster UE results in shorter pre-scheduling time for transmissions accordingly. On the contrary, more pre-scheduling time can be used for transmissions. Therefore, we can adaptively trigger the pre-scheduling procedure and adjust the transmission rates between BL and ELs with limited resource.

Figure 4. The prediction of time-to-trigger (TTT) of handover. (a) User equipments (UEs) velocity = 30 km/h and (b) UE velocity = 120 km/h.

3.2. Base Layer Adjustment

Our goal is to provide high QoS for video streaming before new connection establishment. Since BL includes the most basic data for playing the video, for this reason, BL is needed to transmit in advance. In the following, we discuss the simulation result of BL adjustment.
As shown in Figure 5 and Figure 6, let Ki be a constant. When the starting time is approaching the actual TTT, the shortertr can be used for transmissions and the value of dBL,0 decreases accordingly. While the starting time is after 71 (Figure 4) or after 21 (Figure 5), dBL,0 increases slightly and approaches a constant. This is because there is a shorter pre-scheduling time for transmissions after 71 (Figure 5) or after 21 (Figure 6), we need to assign a higher dBL,0 for maintaining high QoS for streaming video. Furthermore, because of limitative pre-scheduling time, a greater number of users leads to higher dBL,0compared to a smaller number of users. On the other hand, high velocity causes a severe decrease of dBL,0 because of a shorter pre-scheduling time.

Figure 5. Starting time for pre-scheduling vs. dBL,0 (UE velocity = 30 km/h, actual TTT = 79.924 s).
Figure 6. Starting time for pre-scheduling vs. dBL,0 (UE velocity = 120 km/h, actual TTT = 25.981 s).
Because BL has higher priority for high QoS for video streaming, while the starting time is after 75 s (Figure 7) and 21 s (Figure 8), we can see K i has a severe decent rate, especially at higher velocity. This indicates our mechanism can provide more BL to meet high QoS for streaming video.

Figure 7. The decent rate Ki  vs. starting time (UE velocity = 30 km/h).
Figure 8. The decent rate Ki  vs. starting time (UE velocity = 120 km/h).
In the following, we set the length of pre-scheduling time tr to evaluate the relationship between K i and dBL,0. Here, Kiis a variable. In Figure 9 and Figure 10, a UE can dynamically adjust Ki for desirable video quality according to SNR values. A higher Ki indicates that dBL,0 has a lower proportion of transmission frames. While the UE requires better video quality with more data of enhanced layers transmitted, Ki can be set to a higher value. On the contrary, for a low SNR situation, Kican be set to a lower value to maintain high QoS for video streaming.

Figure 9. The decent rate Ki vs . dBL,0 (UE velocity = 30 km/h, tr = 20.924 s).
Figure 10. The decent rate Ki  vs. dBL,0 (UE velocity = 120 km/h, tr  = 8.981 s).
As shown in Figure 11 and Figure 12, our proposed mechanism achieves a higher throughput compared to the EXP/PF scheme. This is because BL has higher priority for transmission in our proposed mechanism. Furthermore, we combined the pre-scheduling mechanism with a prediction of TTT for packet transmissions. Note that BL is essential to video decoding, but the EXP/PF only fairly schedules BL and ELs transmissions.

Figure 11. Average user throughput (UE velocity = 30 km/h).
Figure 12. Average user throughput (UE velocity = 120 km/h).

4. Conclusions

In this paper, a pre-scheduling mechanism is proposed for real-time video delivery over LTE. We can adjust the data transmission rate before handover between BL and EL for high QoS for video streaming under the disconnection period by utilizing the handover prediction. The practical results show higher throughputs compared to the EXP/PF scheme.

Author Contributions

All authors contributed equally to this work. Wei-Kuang Lai and Chih-Kun Tai prepared and wrote the manuscript; Chih-Kun Tai and Wei-Ming Su performed and designed the experiments; Wei-Kuang Lai, Chih-Kun Tai and Wei-Ming Su performed error analysis. Wei-Kuang Lai gave technical support and conceptual advice.

Conflicts of Interest

We declare that we have no financial and personal relationships with other people or organizations that can suitably influence our work. There is no professional or other personal interest of any nature or type in any product, service, and/or company that could be said to influence the position presented in, or the review of, the manuscript entitled “A Pre-Scheduling Mechanism in LTE Handover for Streaming Video.

Abbreviations

The following abbreviations are used in this manuscript:

LTE
Long Term Evolution
EXP/PF
exponential/proportional fair
3GPP
3rd Generation Partnership Project
RR
round robin
MR
maximum rate
PF
proportional fair
LA
link adaptation
M-LWDF
Maximum-Largest Weighted Delay First
HOL
head-of-line
SVC
scalable video coding
BL
base layer
ELs
enhancement layers
RSRP
Reference Signal Receiving Power
ES
exponential smoothing
TTT
time-to-trigger
LS
least squares
QoE
quality-of experience
SPS
semi-persistent scheduling
PRBs
physical resource blocks
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Source: http://www.mdpi.com/2076-3417/6/3/88

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