Real-time backhaul assurance to enhance QoE - The evolution in backhaul monitoring in LTE networks

Backhaul assurance’s role expands in response to higher traffic complexity and use of carrier Ethernet backhaul LTE brings the much needed performance and capacity improvement over 3G that enables operators to provide better service and QoE to their subscribers. But to leverage the new network capabilities, operators need to manage traffic more actively – indeed, proactively – to prevent service issues from manifesting. They need to be able to monitor, troubleshoot and optimize each element in their network, while at the same time keeping track of QoE and end-to-end network performance in real time. Legacy networks, less complex and more homogeneous than LTE networks, do not require – or allow – this intense level of management of network resources. They are easier for mobile operators to monitor and operate.

Today, mobile operators are modifying their backhaul to support these complex heterogeneous networks with latency-sensitive applications, which require real-time, QoE-based optimization if operators are to make more efficient and profitable use of their network resources. The introduction of LTE and the overall network evolution affect backhaul and, specifically, backhaul assurance primarily along two dimensions: the overall changes in traffic dynamics and traffic management, and specific changes in backhaul technology and provisioning.

Not only are we seeing a staggering increase in traffic volumes; the complexity of traffic is increasing, and mobile operators have to manage traffic flows tied to different applications that have different requirements, are extremely variable in spatial and temporal distribution, and are subject to complex, real-time policy enforcement. And they have to achieve this management in networks with multiple layers and multiple RATs. Operators want to use their network resources as efficiently as they can, and to keep their subscribers happy even under the most demanding application requirements: to do so, they have to explicitly monitor and optimize QoE. Backhaul still has to provide the required capacity, as it has in legacy networks, but it also has to address the traffic complexity and latency sensitivity appropriately to avoid becoming the performance bottleneck in mobile networks.

Management of mobile backhaul is made even more complex by the expanding adoption of true IP-based Ethernet technologies, and by the fact that backhaul provisioning is increasingly shared and managed by third-party service providers. Operators have less direct control over the backhaul, and find it more difficult to gain visibility into it, at a time when the relevance of control and visibility have grown along with the need to manage traffic more actively. Backhaul assurance is essential to giving mobile operators the tools they need to monitor and troubleshoot their networks end-to-end and address appropriately any performance issue that may arise within the backhaul portion of their networks.

1. Traffic growth and focus on QoE require a new approach to traffic management

     Video and voice lead to the dominance of real-time data

Mobile traffic continues to grow relentlessly – from 3.7 to 30.6 TB/month over the 2015–2020 period, with a 53% CAGR, according to Cisco VNI. The traditional response to increased demand has been to add cell sites or sectors to increase capacity. This is no longer sufficient – and it is a financially challenging proposition for mobile operators when used alone: it requires large investments that are not backed by a corresponding increase in revenue, because ARPUs are stable or even declining in most markets.

Mobile operators are discovering that they need to manage traffic more actively to drive resource utilization up, because this allows them to extract more value from the deployed infrastructure, and contain or postpone the need for expensive network expansion. With a more proactive traffic management approach, mobile operators can purposely allocate network resources to maximize QoE – giving their subscribers the best experience their networks can support.

Most of the attention in the wireless industry today focuses on the increase in data traffic, but equally important is the change in traffic characteristics, especially distribution and complexity. Initially all traffic was voice. Texting added some amount of data, but the volumes were always limited and the requirements easy to meet.

Today most mobile traffic (more than 90% in developed markets) is data, and with VoLTE, voice too becomes an instance of data traffic. Mobile video will increase from 2 to 23 TB/month, an 11-fold increase, between 2015 and 2020, and will account for 75% of total mobile data traffic by 2020. The requirements operators must meet to provide a good subscriber experience become more stringent with the increasing prominence of real-time traffic such as voice and video. Conversational video traffic, such as Apple’s FaceTime and Microsoft’s Skype and Lync services, requires voice and video clarity with no perceptible delay or packet loss, and is more sensitive to latency issues than streaming services.

2. Traffic complexity and uneven distribution grow in LTE networks

    QoE becomes the target of network traffic optimization

The shift to IP data does not make it easier to manage traffic priorities. Furthermore, the way we use data and the requirements for different data flows have added complexity in managing traffic end-to-end in mobile networks. The table on the right lists different drivers responsible for the increase in data complexity that affect the way operators manage their overall networks and, specifically, their backhaul. The increased use of video and the introduction of VoLTE are the changes that have had the largest impact to date. We expect the other drivers, such as IoT, to take on a large role in shaping traffic management in the future.

Voice and video provide a good illustration of the impact of traffic complexity on network management. Real-time traffic types such as video and voice have similar requirements in terms of latency, jitter and packet loss that sets them apart from other data streams. Yet operators typically treat video and voice differently. Because of the importance of voice quality for subscriber retention, operators may want to give VoLTE priority over all other data services, including streaming video. Because of the high bandwidth requirements of video, they may want to limit the bandwidth allocated to video traffic in networks that are at capacity or congested. In addition, because of the special requirements of VoLTE, operators have to treat VoLTE traffic differently from OTT voice services. Similarly, they may set higher performance targets for conversational video than for streaming video, because subscribers are likely to be more sensitive to the quality of conversational video.

As a result, mobile operators need to manage traffic more carefully to drive resource utilization. This translates into the need to manage and monitor traffic not as a homogeneous flow of packets, but as a concurrent set of flows.

As traffic flows through the network end-to-end, operators need to know what the performance level is, both at different locations within the network and from the subscriber perspective in terms of QoE. They need to know this from multiple  dimensions – by application, type of traffic, and location – and they need to know it in real time. For both monitoring and troubleshooting the network, operators also need a precise understanding of what is required to ensure good QoE, and to prevent or solve performance issues. For that, they need visibility into the network at different levels of granularity to see how, for instance, application, traffic and location interact with each other, without succumbing to unmanageable complexity.

Traditionally, operators have relied on historical network KPIs that provide an averaged view of the performance of network elements. Although this data is still valuable, and undoubtedly operators will continue to use them to assess network performance, historical averaged KPIs do not have the granularity needed to assess network performance in real time, how it relates to QoE, and what the bottlenecks in the network are.

For instance, an operator may decide to give priority to voice and selected video services, and ensure that the latency is low for this type of service. However, this may drive up latency for applications like web access, messaging or downloads, and this is acceptable because increased latency there is likely to go unnoticed by subscribers. As a result, the averaged network latency may be higher than if all traffic were treated equally, but the latency for the selected voice and video services may be low, and hence in line with the operator’s performance targets.

How should operators leverage the increase in traffic complexity to their advantage? What targets should operators pursue to get the best QoE? In the voice-dominated networks of the past, the answer was straightforward: operators’ main goal was to maximize voice capacity, measured in erlangs. In 3G networks, increasing data capacity and lowering latency became essential targets. In 4G networks, with the emphasis shifting toward QoE, the targets of optimization have become more complex to define.

Metrics like capacity and latency are still crucial, but they have to be optimized for specific traffic flows or, as they are increasingly called, specific network slices, rather than for the overall traffic to and from the RAN. Network slices are logically separated traffic streams that may be defined by traffic type, application, target device, service, or other parameters.

The goal for operators is no longer to have the lowest latency and highest capacity at the network level, but to have the lowest latency, highest capacity, or both for the network slices that matter most to the operator, or that need it most. This approach may require – as a side effect – that network slices deemed to have a lower priority or less stringent requirements end up having a degraded performance in terms of KPIs, but still retain a good QoE.

While this approach increases the complexity of traffic management, it opens new opportunities for mobile operators to allocate network resources in a more efficient way, which if implemented properly should raise the QoE within the existing network – thus removing or postponing the need for capex for capacity expansion. It also enables mobile operators to define a traffic management strategy as a differentiator from other operators, and use it as a competitive tool.

Traffic characteristics that affect network management

- Traffic type: Requirements for different types of traffic (e.g., voice, video, or best-effort data) vary greatly in terms of bandwidth, latency, jitter, packet loss, and mobility. Voice remains a special case, with subscribers strongly sensitive to degraded quality.
- Application or service type: The same traffic type may be transmitted as a different service or within a different application. For instance, subscribers can get streaming video within OTT applications such as Netflix, or as a conversational video for an OTT application such as WebEx or Zoom, or an operator-managed ViLTE service. Video traffic may also be encrypted or not, and optimized by the content provider or the operator.
- Spatial distribution: Usage is extremely concentrated geographically in a small part of the network – specific venues, central metropolitan areas – leading to congestion in specific areas.
- Temporal distribution: The network traffic load changes throughout the day and week as subscribers travel to and from work, and go out at night and on weekends.
- Microbursts: Data traffic is inherently spiky at the millisecond level and below. This may cause congestion in the network even though, when looking at transported traffic averaged over time, the traffic load on the network appears to be operating within capacity.
- Policy, traffic prioritization: The mobile operator may use policy to prioritize traffic or allocate it to specific RATs, channels or infrastructure elements (e.g., macro or small cells).

3. Backhaul has to support application-based, real-time traffic management

    QoE metrics take center stage in backhaul assurance

As operators learn to deal with more complex and uneven traffic distribution in real time, mobile backhaul has to work within this new framework for performance assurance and traffic management, and avoid becoming the bottleneck that degrades QoE. To do so, backhaul has to be more than a high- capacity pipe. It has to accommodate different sources of traffic and meet the different requirements set by factors such as application type, location, RAN conditions and policy. This has to happen in real time to be effective.

While QoE metrics gain prominence in assessing backhaul performance, they do not directly drive the assessment of backhaul performance. Operators have to relate QoE measurements to KPIs and to the performance of different elements in the network. QoE metrics, though, are difficult to quantify because they are inherently more subjective than KPIs, and there is no industry-wide definition of QoE measurements for data traffic. Even more challenging is the need to relate QoE to network performance – including backhaul performance. Low QoE for video, for instance, may be due to problems with the handset, RAN congestion, backhaul limitations, policy enforcement, or a bottleneck in the interface with the internet if the video is not cached.

Backhaul assurance is crucial to ensuring that backhaul supports the new mobile operator requirements. Along with other types of performance and service assurance, it has to move beyond averaged historical KPIs in order to identify and resolve performance issues in real time, at the granularity level that is required. To succeed in this task, backhaul assurance has to work within the wider context of end-to-end network assurance. When the operator spots an issue that degrades network performance or QoE at the end-to-end level, it has to identify the source within the network. Backhaul assurance is one of the tools operators can use to go deeper in their assessment of network performance, and either exonerate backhaul or establish its role in the problem.

RAN evolution expands backhaul requirements

- Multiple RAT interfaces. LTE networks coexist side by side with 2G and 3G networks, with Wi-Fi for both residential and workplace offload, and with carrier Wi-Fi. LTE unlicensed is the latest addition to the mix, and although it is a version of LTE that works in the 5 GHz unlicensed band, it introduces significant differences from LTE in licensed bands, partially due to the support of LAA for listen-before- talk, or LBT, to manage interference with Wi-Fi.
- More spectrum bands. Operators need and use more spectrum to meet the increase in data traffic. Carrier aggregation enables operators to use licensed spectrum they own, or can acquire, to transmit efficiently within multiple bands.
- Operators are more eager to use unlicensed spectrum with carrier Wi-Fi, LWA or LTE unlicensed on an opportunistic basis, because unlicensed spectrum provides a valuable increase in capacity where those bands are not congested.
Regulators are trying to allocate additional spectrum for mobile traffic – e.g., the 3.5 GHz band in the USA. With 5G, mobile operators hope to use spectrum above 6 GHz, which can support very high capacity in dense environments.
- Small cells and other sublayer elements. Densification is necessary to increase network capacity to meet increasing traffic demand. In addition to outdoor small- cell deployments, it will include indoor femto-cell and small-cell deployments, DAS, and carrier Wi-Fi networks.
- SON. To manage the coexistence of multiple elements with overlapping coverage areas, automation is necessary to fine-tune the RAN in near-real time. SON treats the network elements and capacity as dynamically changing, and modifies RAN settings to optimize the use of network resources.

4. Multiple RATs, bands and layers coexist in HetNets

    Backhaul assurance to operate across RAN elements and backhaul solutions

As traffic and traffic management solutions evolve, so do the RAN infrastructure and its operations. In the RAN, the transition is toward less homogeneous networks in which multiple elements coexist and are increasingly integrated.

Deeper integration across networks – e.g., LTE and Wi-Fi – allows mobile operators to allocate traffic to specific RAN resources, depending on the capabilities of RAN elements, real-time RAN conditions, subscriber location within the footprint, demand, and policy. The flexibility in managing traffic flows within the RAN makes the effective RAN capacity dynamic and affects backhaul requirements, which change correspondingly in time.

Operators have to ensure the backhaul meets the RAN requirements during network deployment, but as RAN elements change, they have to check that RAN requirements continue to be met. This is especially true in small-cell deployments with multi-hop backhaul, in which cells can be added to a local topology (e.g., hub-and-spoke or mesh topologies) more frequently than in a macro-only scenario.

The heterogeneous mix of RAN elements creates a more complex environment for backhaul assurance, because backhaul requirements vary for each element. Monitoring and troubleshooting HetNets, especially when they include a small-cell layer, have to take into account factors such as load sharing, aggregation, visibility and infrastructure sharing, which are less relevant or do not apply in a macro-only environment.

Small cells’ impact on backhaul requirements

The higher number of RAN endpoints increases the need for scalable, low-complexity, cost- effective solutions, which nevertheless provide full functionality, resiliency and high capacity.

Infrastructure installed on non-telecom assets, closer to the ground but close to an aggregation point, imposes limits on the choice of backhaul solutions. At many locations, fiber is not available or cost effective, and LOS or NLOS wireless backhaul has to be used instead. Multiple backhaul solutions with varying performance characteristics are often deployed within the same footprint, increasing the complexity of monitoring and troubleshooting backhaul.

Multi-hop backhaul in hub-and-spoke or mesh topologies further increases the complexity of backhaul requirements and management. Requirements vary, and visibility may be lost or limited at different locations within the local network.

Small-cell networks are designed to grow organically as demand grows, with the addition of small cells to the existing footprint as the need arises. In a hub-and-spoke or mesh topology, such additions often change the backhaul requirements of multiple links within the network.

The introduction of the X2 interface in LTE networks to coordinate transmission among overlapping or adjacent network elements allows mobile operators to improve RAN resource utilization, but generates higher levels of signaling and imposes additional requirements – especially for latency – in the backhaul. X2-based signaling remains in the RAN – it is not sent to the core – making it difficult for mobile operators to monitor it and troubleshoot any problems that may originate from it.

Neutral-host models are emerging to make small-cell deployments cost effective, scalable, and easier to deploy and manage. They typically require a shared backhaul link managed by a third-party service provider, which may or may not be the neutral-host provider. While this arrangement gives operators flexibility and cost reduction, it limits their visibility into the backhaul up to the aggregation point, and possibly further if transport from the aggregation point to their core network is shared.

5. Ethernet backhaul is cost effective, but OAM can be challenging

    New backhaul assurance solutions are needed to meet new requirements

Operators no longer use TDM-based private circuits for backhaul. Ethernet MPLS- based backhaul can now deliver scalable, resilient, carrier-grade performance in a cost-effective way and support legacy technologies such as TDM, making it possible to support 2G, 3G and 4G concurrently over the same link.

While the standards include the functionality mobile operators require, they may not provide the network-fault and performance monitoring data that operators need, especially in multivendor environments, or where backhaul is shared or provided by third parties (see next two sections).

In some cases, operators resort to using NIDs that give them more visibility into backhaul performance and better troubleshooting capabilities, but NIDs also introduce additional cost and complexity in the management of backhaul. NIDs’ limited scalability and cost can be an issue in macro-only networks, but become a more severe liability in multilayer HetNets, in which the number of endpoints -- small cells or other sublayer RAN elements – and the variety of backhaul solutions sharply increase. Mobile operators have started to deploy smart SFP transceivers as an alternative. They are more cost effective, have a smaller footprint requirement, and allow operators to achieve the monitoring accuracy and resolution required to manage complex backhaul networks.

When deploying small cells, operators face a bigger challenge, because they have to keep costs lower than in the macro network, but their OAM requirements are unchanged. Backhaul assurance becomes all the more important, to ensure that operators benefit from the cost savings of carrier Ethernet backhaul. The increased complexity in traffic composition and distribution, and the need to monitor and troubleshoot performance on the basis of real-time QoE and RAN- condition data, expand the relevance and required functionality of backhaul assurance.

Drivers for carrier Ethernet and IP/MPLS backhaul

- Lower costs

Shared IP backhaul is less expensive than TDM private lines, and provides more flexibility for bandwidth pricing

- Legacy support

MPLS-enabled backhaul supports multiple technologies, including legacy ones such as TDM.

- Support for guaranteed SLAs

SLAs may include committed information rates, committed burst rates, excess information rates, and random early discards.

- Improved support for QoS

Class-of-service options are supported.

- Ethernet OAM standards

These have introduced OAM capabilities to Ethernet to support network-fault and performance management. Key Ethernet OAM standards are:

IEEE 802.3ah for the access link (Ethernet first mile)

IEEE 802.1ag for the connectivity layer (connectivity fault management)

IEEE 802.1aj for managing customer demarcation devices

 ITU-T-Y.1731 (network and service layer OAM)

 RFC-2544 and ITU-T-Y.1564 (service level validation)

 RFC-5357 (Two-Way Active Measurement Protocol, or TWAMP)

 MEF E-LMI to manage the UNI and to auto-configure the CE

6. Backhaul provided by third-party service providers reduces operators’ control

    Visibility into third-party backhaul is crucial for OAM

Over recent years, mobile operators have faced strong pressure to lower per-bit costs, because they have to carry a much heavier traffic load but do not see a corresponding increase in service revenues. As a result, they have started to accept infrastructure-sharing and neutral-host arrangements that provide cost savings, but also limit the control and visibility they have into their networks.

Backhaul is an example of this. One of the cost advantages of carrier Ethernet comes from the fact that backhaul can be provisioned and managed by a third party, and that it can be shared with other mobile operators or service providers. This cost advantage has been a major driver for the adoption of carrier Ethernet and, as a result, operators are increasingly sharing backhaul and leasing it from third parties.

To preserve performance of their networks, however, it is imperative that they deploy solutions that give them the necessary visibility into the backhaul – initially during the activation testing phase, and subsequently for monitoring and troubleshooting. Frequently, mobile operators want to conduct the testing, monitoring and troubleshooting of backhaul links independently from the service providers, both to confirm the performance data they receive from them, and to collect data that the backhaul provider may not collect.

The data that operators collect from these solutions may enable them to relate backhaul performance to RAN performance and QoE more accurately. In turn, this enables them to manage the RAN more effectively as well, including identifying microbursts. When backhaul assurance is part of an end-to-end network assurance solution, having more-granular information on the backhaul may enable them to identify the source of QoE issues more precisely.

Assessing leased or shared backhaul networks

- Ensure that SLA terms are met, during initial deployment and subsequent network upgrades and expansion (e.g., addition of small cells, carriers, or sectors), as well as during regular operations (i.e., monitoring and troubleshooting)
- Monitor performance at the application and service levels and in real time, to ensure that backhaul does not become a bottleneck in RAN performance or have an adverse impact on QoE
- In shared deployments, ensure that the operator gets access to a fair share of the backhaul resources

7. Implications

With LTE and carrier Ethernet, visibility into backhaul becomes more crucial to  preserving end-to-end network performance and QoE

With LTE, backhaul requirements have not just expanded, they have changed qualitatively. Operators need to monitor and troubleshoot their networks in real time, taking into account QoE. They need to do this for the end-to-end network and for the backhaul as well.

Greater traffic complexity and extreme variability through time and space compel operators to monitor and troubleshoot backhaul performance more actively, increasingly in real time or near real time to address performance issues as they arise, or to prevent them.

Operators need to assess backhaul performance with a view of its impact on QoE. Performance metrics averaged over time and across the network are still useful, but operators are transitioning to network monitoring and assurance platforms that can operate at the traffic flow or network slice level, based on factors such as traffic type, service and application.

The RAN has become more complex, dynamic and dense because of the introduction of HetNets; densification with small cells, DAS and other sublayer RAN elements; and LTE Advanced functionality such as CA. These changes affect backhaul requirements and increase the complexity of monitoring and troubleshooting backhaul performance.

Carrier Ethernet delivers cost savings, but also bring challenges for managing backhaul performance. Operators need to actively control OAM to ensure that backhaul links do not become the bottleneck and, when that does happen, operators must reliably identify the causes.

Backhaul has become a service that operators often lease from third parties and share with other service providers. Operators need to make certain they have the backhaul assurance tools to verify that the backhaul’s performance meets the agreed SLAs, and that they get their fair share of backhaul resources.

Nowadays, the world leading measure equipment suppliers are aimed at making surveillance solutions for 4G LTE backhaul networks, which must mention VIAVI. Specifically, Viavi provides the EtherASSURE solution, supporting operators in monitoring and quality management in the 4G LTE network backhaul. At the Vietnam market, COMIT is strategic partner of Viavi in ​​providing this solution. With years of experience in providing services and solutions to the telecommunications, COMIT is providing service and solution consultancy, design, testing and optimization for 2G, 3G, and 4G LTE . COMIT has been implementing a lot of service and telecommunication solutions for major mobile operators in Vietnam such as Viettel, MobiFone, Vinaphone and in regional markets such as Laos, Cambodia, Cambodia, East Timor, Myanmar and the Philippines.



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