Tag: 5G

Product update: “Radio Testing as a Service” – successful cloud-based INOS installation in Intel Lab

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Digis Squared’s team complete INOS migration from local on-premises deployment to first cloud-based installation enabling “Radio Testing as a Service”, with Intel® Xeon® Gold 6338N Processor, in the Intel Lab.

Thanks to membership of Intel Network Builders, work undertaken in the Intel Lab has enabled the Digis Squared team to run INOS over the Intel® Xeon® Gold 6338N processor, in the first cloud-based installation of INOS. This work is the first step in our assessment of INOS as a cloud-based solution with Intel processors. Further work is planned with the Intel Lab team assessing other enhanced processors and benchmarking performance enhancement.

Yasser Elsabrouty, Digis Squared Chief Business Officer and Co-Founder said, “Thanks to Intel Network Builders and membership of Intel Winners Circle, INOS is now providing Radio Testing automation over the cloud, enabling “Radio Testing as a Service” over private or public cloud.  The cognitive testing tool can seamlessly manage large amounts of data in a multi-tenant environment, providing full automation and real-time reporting.”

“Delivering INOS Testing as a Service over the cloud will increase efficiency, convenience and scalability, delivering the instant capability to run thousands of radio network tests from anywhere, anytime, in combination with smart automation, real-time reports and KPI deviation alerts. Digis Squared’s cognitive INOS tool just became a whole lot smarter!”

Intel® Xeon® Gold 6338N processor

  • 3rd Generation Intel® Xeon® Scalable Processors (formerly “Ice Lake”)
  • 10nm technology, 32 cores, 64 threads, 3.6GHx max turbo frequency, full specification.

Benefits & observations

Running 25 INOS Radio Field Tests in the Intel Lab, the following enhancements were measured, and benefits observed,

1. Increased cores & threads

  • The Intel® Xeon® Gold 6338N processor enabled Digis Squared to setup 2 or more parallel INOS containers serving two (o more) different customer accounts. In the field, this extra capability enabled by the Intel® Xeon® Gold 6338N processor would mean that,
    • More copies of INOS modules can run together in parallel, providing higher processing capability
    • Lower response time and faster handling for APIs and web requests
    • Duplicating INOS running modules presents high availability
  • When assessing response time across all 25 tests, the results show that the Intel® Xeon® Gold 6338N easily handles the volume of data as data payload increases x2.5 over the 25 tests.

2. Max Turbo Frequency: the INOS platform receives high traffic bursts periodically, due to the nature of telecoms. The increased max turbo frequency of the Intel Xeon processor empowers INOS to handle these bursts without any probability of outage.

3. Intel® Turbo Boost Technology 2.0 Frequency: Increases the capability of INOS to receive big sudden bursts of requests, keeping stable progress and high performance (i.e. no delay on data retrieval, no delay on rendering data to maps and tables, and reduced time to prepare reports.)

4. Number of UPI links: INOS consumes a huge volume of processor capability and RAM. To optimise INOS performance, we are looking not just for capacity of the processor, but also how this processor chip interconnects with the rest of the system components. The Intel® Xeon® Gold 6338N presents better integration with various I/O devices reflecting in INOS performance, especially when handling large bursts of input data files.

5. Max memory size: For INOS, more memory means more concurrent users, more software threads running in parallel, and an increase in the number of docker containers running simultaneously. The increased max memory size indicated in this table will deliver at least three or more times the number of INOS containers when using the Intel® Xeon® Gold 6338N.

6. Intel® AES-NI & Intel® Trusted Execution Technology: INOS SW runs on sensitive client data, and this capability will save data from any corruption and violation trials.

Conclusions & next steps

Having successfully completed this first assessment with the Intel Lab, the Digis Squared team are confident in the deployment of INOS as a cloud-based solution utilising Intel® Xeon® Gold processors, delivering optimised performance and enhanced speeds.

Yasser concluded, “Further work is planned with the Intel Lab team assessing other enhanced processors and measuring performance enhancement, and then, mutual testing with Open RAN market leaders!”

If you or your team would like to discover more about our capabilities, please get in touch: use this link or email sales@DigisSquared.com .

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Digis Squared, independent telecoms expertise.

AI enhancement of capacity management in mobile networks

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The optimisation of capacity management in mobile networks is vital: too little capacity constraints revenue opportunities and impacts customer experience, but idle capacity risks high opex and under-performing investment in assets. Capacity management has always used mathematical modelling techniques to attempt to find the sweet spot, and optimise opportunities and costs. In the past, such predictions were based on historical data, but now AI enhancement of capacity management changes that. The deployment of network virtualization, 5G and network slicing requires the use of cognitive planning; it is vital that capacity planning models are able to assess a step-change in the volume of data points in real-time or near-real-time.

RAN Automation Architect and Data Scientist at Digis Squared, Obeid Allah Ali, describes how AI, automation and advanced analytics are being deployed to gain even greater network capacity planning efficiencies.

What exactly is machine learning, and why is it important?

Machine Learning (ML) is an application of artificial intelligence (AI) that enables computer programs to learn and improve over time because of their interactions with data.

It automates analytics by making predictions using algorithms that learn repeatedly.

Its easy self-learning technique, rather than rule-based programming, has found widespread use in a variety of contexts.

So, whether it’s making life easier with navigation advice based on predicted traffic behaviour, assessing large amounts of medical data to identify new patterns and links, or warning you about market volatility so you can adjust financial decisions, AI and ML technology has permeated many aspects of our daily lives.

The power of prediction machines

In simplified terms, prediction is the process of filling in the missing information. It takes the information you have, often called ‘data,’ and uses it to generate information you don’t have. Most machine learning algorithms are mathematical models that predict outcomes.

How will machine learning impact businesses?

There are two major ways that forecasts will alter the way businesses operate.

  1. At low levels, a prediction machine can relieve humans of predictive activities, resulting in cost savings, and for example removing emotional bias.
  2. A prediction machine could become so accurate and dependable that it alters how a company operates.

How big is the growth in mobile connectivity?

Above: from GSMA “The State of Mobile Internet Connectivity Report 2021” [3], their most recent report

Some further statistics on the growth in mobile data, from the same GSMA report [3],

  • global data per user reaching more than 6 GB per month – double the data usage for 2018
  • 94% of the world’s population covered by mobile broadband network
  • By the end of 2020, 51% of the world’s population – just over 4 billion people – were using mobile internet, an increase of 225 million since the end of 2019

And from [4] GSMA Mobile Economy 2021 report,

  • By the end of 2025, 5G will account for just over a fifth of total mobile connections.

Capacity and performance of mobile networks

The rapid growth of mobile traffic places enormous strain on mobile networks’ ability to provide the necessary capacity and performance.

To meet demand, communications services providers (CSPs), mobile network operators and their suppliers need a range of options, including more spectrum, new technology, small cells, and traffic offloading to alternate access networks.

To meet commercial business objectives, mobile network operators are under pressure to maximize the utilization of existing resources while avoiding capacity bottlenecks that reduce revenues and negatively influence end-user experience.

Additionally, network operators have to assess risk, contractual SLAs (especially in the context of MVNOS who utilise their network, and corporate contracts), the total cost of ownership, and the impact on customer experience, perception and brand.

Radio Access Network costs are estimated to be 20% of the opex cost of running a network [1]. And the impact of opex on network quality correlates strongly with increased ARPU and reduced churn; when network quality is highest, service providers benefit from a higher average ARPU (+31 %) and lower average churn (-27%) [2].

Finding the perfect balance of capacity, quality, efficiency and cost – not too much, not too little – is complex and dynamic.

Capacity forecasting for mobile networks

The Digis Squared team have developed machine learning algorithms and decoders that can, based on network activity, decode how User Traffic Profiles are changing. With the deployment of 5G and network slicing techniques, modelling network usage patterns and customer behaviour and predicting future demand becomes immediately far more complex – the only way to successfully model this will be with AI.

Detecting a problem

We detect anomalies in cells in the existing network, plus highly utilized cells, using machine learning and a design approach algorithm based on several reported KPIs. We use this information to distinguish what requires immediate attention from what should be monitored for proactive action. Using multivariable modeling techniques, that is, assessing multiple KPIs across each cell, enables us to have a highly nuanced model, optimising all available capacity.

Forecasting

Operators must be able to estimate the required traffic capacity for their mobile networks in this competitive climate to invest in extensions when they are truly needed, and deploy the most cost-effective solution, while maximizing investment and maintaining good network quality.
In this phase of the development of the model, we will discover future troublesome cells to guide our approach and actions using predictive models.

AI enhancement of capacity management: what’s next?

Today, we use an open-loop control system to apply our AI methods. However, as predictive model accuracy improves, we anticipate transitioning to a fully automated Self-Organized Network (SON) – enabling closed-loop network management with self-planning, self-configuration, self-optimization, and self-healing – system in the near future.

In conversation with Obeid Allah Ali, RAN Automation Architect and Data Scientist at Digis Squared.

If you or your team would like to discover more about our capabilities, please get in touch: use this link or email sales@DigisSquared.com .

Discover more

Digis Squared, independent telecoms expertise.

References

  1. Open RAN might not save you much after all
  2. Why network quality is more important than ever
  3. GSMA “The State of Mobile Internet Connectivity Report 2021”
  4. GSMA “Mobile Economy 2021” report

AI-native network slicing for 5G networks

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AI-native network slicing for 5G networks. Successful 5G deployments rely on the use and integration of many other new technologies. In this blog post, Tameem Sheble RAN data scientist at Digis Squared, and AI for 5G researcher, takes us on a deep dive through the close integration of 5G with AI, and how network slicing is vital to deliver the 5G vision.

The view from 2015: the 5G vision

New telecom technologies take years to be discussed, agreed and defined in standards. Previous wireless technologies have been designed and architected for one major use case: enabling mobile broadband.

During the development phase of 5G standards, by means of reaching consensus and aligning expectations, the International Telecoms Union (ITU) defined their framework and overall objectives of the future out to 2020 and beyond, in a vision document. As part of this workaround 5G architecture, they considered three distinctive, cutting-edge service verticals – enhanced mobile broadband, massive machine-type communications and ultra-reliable and low-latency communications – and their usage scenarios and opportunities for communications service providers (CSPs).

Above: The original vision for 5G. Diagram from “IMT Vision for 2020 and beyond”, published 2015 [1]

Network Slicing (NS) is one of the 5G key enablers. It’s a technique that CSPs can use to satisfy the different needs and demands of the 5G heterogeneous verticals, as illustrated below, using the same physical network infrastructure.

AI-native network slicing for 5G networks

Network slicing enables the virtual and independent logical separation of physical networks. It’s a technique used to unlock the value of 5G networks, by opening the possibilities for customer-centric services based on the demand on the network while managing cost and complexity. Consequently, vendors and standardization communities consider 5G NS a key paradigm for 5G and beyond mobile network generations.

Although the 5G NS process brings flexibility, it also increases the complexity of network management. The introduction of AI into the 5G architecture, AI-native, is motivated by the vast amount of unexploited data and the inherent complexity and diversity that requires AI to be deployed as an integral part of the overall system design. Although the rising temptation is to rely on AI as a pillar for managing 5G network complexity, in practical terms, AI and 5G are indivisible. They tend to converge from an application perspective, and they become two halves of a whole. AI’s value relies on 5G; for example; critical data-driven decisions need to be communicated with ultra-low latency and high reliability.

AI as a potential solution to network slicing

Let’s turn now to addressing AI in a nutshell for the management of the complex sliced 5G network, a complexity that relates to decision-making towards efficient, dynamic management of resources in real-time. CSPs need to leverage the use of the vast volume of data flowing through the network in a proactive way, by forecasting and exploiting the future system behaviour.

The management lifecycle of a network slice consists of four main phases,

  1. Preparation
  2. Instantiation
  3. Operation
  4. Decommissioning.

Many researchers have proposed AI solutions that underline the first 3 phases, as the decommissioning phase doesn’t involve management decisions. Admission control and network resources orchestration are some of the key slice management functions that need to make slice-level decisions to meet their requirements, while simultaneously maximizing the overall system performance.

Looking at this in more detail, this is achieved by controlling a massive number of parameters as a result of uncovering complex multivariate relationships that are related to each other in time, geolocation, etc. Proposing an AI solution must be done case by case depending on problem formulation and framing, algorithmic requirements, the scarcity and type of data and the operational time dynamics.

AI for network slices admission control (Phase 1)

Admission control – during the slice preparation phase – is a very critical decision-making control mechanism, it ensures that the requirements of the admitted slices are satisfied. During this control mechanism, a trade-off between resources sharing and KPIs fulfilment needs to be tackled. The decision on how many network slices run simultaneously, and how to share the network infrastructure between those slices, has an impact on the revenues of the CSPs.

The trade-off is further complicated by variables that alter over time, which makes the optimization of revenue based on admitted slices a difficult task. This is where Deep Reinforcement Learning (DRL) approach comes into the picture.

In a nutshell, the DRL algorithm has to learn the arrival pattern of network slices and make, for example, revenue-maximizing decisions based on the current system utilization and the anticipated long-term revenue evolution. Once a network slice is requested, and based on the system current utilization, two separate neural networks are in charge of scoring the two actions (i.e., accepting or rejecting the request), where each score represents the revenue associated with each action. Based on the difference in scores, the action corresponding to the higher revenue is selected; the algorithm interacts with the system and evaluates the accuracy of the forecasted revenue through a loss function. This value is then feedback to the corresponding neural network to perform weight update, so that the algorithm starts converging to a global maximum and performs better in the subsequent request iterations.

AI for network resources orchestration and re-orchestration (Phase 2 and 3)

After the successful admission, slices must be allocated sufficient resources in such a way that the available capacity is used in the most efficient way that minimizes the operational expenses (OPEX). The trade-off here is between under-provisioning that leads to Service Level Agreement
(SLA) violation, and over-dimensioning thus wasting resources.

CSPs need to be proactive by forecasting, at a slice level, the future capacity needed, based on previous traffic demand, and consequently timely reallocate resources when and where needed. This is where the Convolutional Neural Network (CNN) architecture comes into the picture for time-series forecasting.

Legacy state-of-the-art traffic time-series forecasting models focus on forecasting the future demand that minimizes some symmetric loss (e.g., mean absolute error), that treats both under- and over-prediction equally. But this type of legacy approach doesn’t consider the risk of under-provisioning and SLA violation – it is useless for 5G deployment!

Researchers argue that a practical AI-native resource orchestration solution has to forecast the minimum provisioned capacity that prevents SLA violation. The balance between over-dimensioning and under-provisioning is therefore controlled by the CSPs, by introducing a customized loss function that overcomes the drawbacks of the “vanilla symmetric losses”.

The AI literature proposes the use of 3-dimensional CNN architecture over the recurrent neural network (RNN) architecture – which is considered the state-of-the-art algorithm for forecasting time-series data –  in order to exploit and uncover spatial and temporal traffic relationships.

The future for AI in 5G and beyond

Whilst general AI limitations are now well known – trustworthiness, generalization and interpretability – exploiting AI to assess and manage complex decisions is vital for the smooth operation of 5G networks. And as network technologies continue to grow in complexity and capability, AI will clearly be necessary as a pillar technology for future-generation zero-touch mobile networks

In conversation with Tameem Sheble RAN data scientist at Digis Squared, and AI for 5G researcher.

If you or your team would like to discover more about our capabilities, please get in touch: use this link or email sales@DigisSquared.com .

Discover more

Digis Squared, independent telecoms expertise.

References

  1. IMT Vision – Framework and overall objectives of the future development of IMT for 2020 and beyond (2015) – Figure 2, page 12, Usage scenarios of IMT for 2020 and beyond

Africell selects Digis Squared to support new network in Angola

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Managed Services from Digis Squared will maximise mobile network efficiency and give Africell’s customers in Angola an outstanding user experience.

November 2021: Africell Angola has awarded Digis Squared a multi-year contract to provide end to end Managed Services to support the launch of Africell’s new network in Angola. In this article, Africell Angola CEO Christopher Lundh and CTIO Faissal Abdallah discuss the partnership with Digis Squared’s CCO, Mohamed Hamdy, and explain why it will contribute to the success of Africell’s launch in Angola.

Optimising digital connectivity

The multi-year contract will see Africell Angola benefiting from Digis Squared’s end to end Managed Services capabilities, covering Radio, Core, BSS, VAS and Field.

“Digis Squared’s tools will help our systems work smartly and efficiently”, says Christopher Lundh, CEO of Africell Angola. “We have been impressed by Digis Squared’s commitment to transferring skills to local staff, a goal which aligns with our own, and we are confident in their experience of multi-vendor systems. It is exciting to have Digis Squared join our new network team.”

“We thank Africell Angola for the trust they have invested in us with this significant commitment”, said Mohamed Hamdy, CCO of Digis Squared. “The contract for Managed Services will enable the new Africell Angola network to launch smoothly and undertake a successful rollout of solutions to customers. Digis Squared’s resources, AI assisted tools, and processes will ensure Africell Angola’s end-to-end services perform at their peak. With our support, Africell’s customers in Angola will be able to experience a revolution in network excellence and performance.”

Supporting Africell’s mission in Angola

Africell Angola’s mission is simple: to help Angola grow by providing innovative, affordable and reliable mobile services.

“The telecoms sector is key to the future success of Angola,” explains Christopher Lundh, “and we will play a big part in this success. Our team of staff and suppliers is tasked with building a network that excites customers, keeps pace with new technologies, and fulfils our vision of leading a digital transformation in Angola.”

Africell Angola’s CTIO Faissal Abdallah added, “The technical solutions we deploy now will form the backbone of the systems we use for decades ahead. Making sure that the complex web of systems deployed can work together seamlessly and resiliently is vital if Africell Angola is to be a network which delivers innovation, affordability and reliability over the long term – working in this new partnership with Digis Squared will enable us to achieve that.”

Africell Angola selects Digis Squared for in-building coverage optimisation

Digis Squared have also been entrusted with an additional contract for Africell in Angola, handling in-building coverage optimisation. In this workstream, Digis Squared will utilise their AI assisted tools including Digis One, INOS, and iPM solutions. Developed in-house by Digis Squared, these tools deliver intelligent, automated testing, benchmarking and analysis platform for network operators and service providers, delivering drive testing (DT), in-building solution (IBS) capability, end to end IoT system testing, as well as Unified Performance and Fault Management and much more, whilst decreasing both the time taken to complete the work and OpEx cost. These AI-led tools are ideally suited to analysing and optimising multi-vendor, multi-technology network implementations, including 5G.

“The contract for in-building coverage optimisation is significant to Digis Squared. When considered alongside our Managed Services contract, it shows that there is real momentum in our southern Africa business operations,” said Mohamed Hamdy. “It’s an exciting time for Digis Squared, and we are grateful to all our clients for the faith they have shown in selecting us. The team are excited to apply their skills, tools and experience to benefit Africell Angola and their clients.”

In partnership with Africell, Digis Squared aims to develop and enhance the capability of local engineers and other technical professionals, increasing their skills and experience. The target is to create a significant number of skilled jobs in the local Angola telecoms market. Says Mohamed Hamdy: “This is a key part of  how we work. Digis Squared is committed to developing local employees who can benefit from our international multi-technology and multi-vendor experience and form a vibrant and capable cohort of local engineers in Luanda”.

About Africell: a fast-growing mobile operator with a pan-African footprint
Africell provides mobile network coverage and related technology services to more than 12 million subscribers in sub-Saharan Africa. In January 2021 Africell won a competitive international tender process for a telecommunications license in Angola. Africell will launch mobile network services in Angola 2022.

These two new contracts between Africell Angola and Digis Squared follow the recent Digis Squared announcement of new offices in Luanda. With business continuing to expand across central and southern Africa, the new Digis Squared office space in Luanda will serve as a regional hub and give the growing Digis Squared team a Covid-19 secure space to meet clients and collaborate with colleagues.

Members of the Digis Squared team, Key Account Manager Ahmed Ma’moon, CCO Mohamed Hamdy, and Co-Founder and Chief Business Development Officer Yasser Elsabrouty outside the new offices in Luanda, Angola.

If you or your team would like to discover more about our capabilities, please get in touch or email sales@DigisSquared.com .

Keep up to speed with company updates, product launches and our quarterly newsletter, sign up here.

Digis Squared, independent telecoms expertise.

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Digis Squared awarded Intel Winner’s Circle Membership 2021

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Digis Squared awarded Intel Winner’s Circle Membership

Yasser ElSabrouty shares the latest news from the team: Digis Squared awarded Intel Winner’s Circle Membership.

“We’re very excited to confirm that Intel Corporation have selected Digis Squared to join their Winners Circle,” Yasser ElSabrouty, Digis Squared Co-Founder and System Integration Business Unit Director announced.

The Intel Winners’ Circle program rewards the most innovative solutions in the ecosystem, in alignment with Intel’s technologies and strategic objectives. Intel is committed to driving advancement in the networking landscape, and the Intel® Network Builders Winners’ Circle seeks to further align the industry in order to accelerate network innovation. The program drives greater technical enablement in the form of testing and benchmarking of solutions, and it helps strengthen the industry’s relationship with end users.

Ongoing collaboration

This announcement demonstrates the growing collaboration and partnership between Digis Squared and Intel. In February this year, Digis Squared joined the Intel Network Builders ecosystem program, and brought with it the deep experience and expertise of the Digis Squared team in ultra-reliable network configuration and optimisation.

A joint case study with Intel published in May, utilising Intel® Xeon® Scalable processors, described substantial enhancements to Video and TCP optimisation achieved utilising Digis Squared’s System Integration capabilities to deliver 30% down link throughput enhancement, thanks to the data traffic optimisation capabilities of INOS.

“The optimisation described in that Intel case study was tested, and customer experience verified, using INOS, Digis Squared’s radio testing and network optimisation solution. INOS works over all data network technologies, including 5G and Open RAN,” Yasser explained. “All our ongoing commercial deployments of INOS utilise Intel technology, as their processing capabilities meet our demanding performance requirements.”

“As part of our partnership with Intel, we’ve also been working within the Intel Lab to characterise the behaviour of INOS with the latest generation of Intel processors, and plan to undertake further work in this facility focussed on Open RAN.”

Thank you

Yasser added, “Thank you to the team at Intel Network Builders and the Intel Lab for their ongoing support and collaboration as we work together to deliver optimised world-class telecom network solutions, and enter the next phase together as a Member of the Winner’s Circle.”

Link to the official announcement on the Intel website.

In conversation with Yasser ElSabrouty, Digis Squared Co-Founder and System Integration Business Unit Director.

If you or your team would like to discover more about our System Integration capability, video and TCP optimisation, or other elements of mobile network optimisation, please get in touch: use this link or email sales@DigisSquared.com .

Keep up to speed with company updates, product launches and our quarterly newsletter, sign up here.

Digis Squared, independent telecoms expertise.

About Intel® Network Builders

The Intel® Network Builders ecosystem program accelerates network transformation by connecting all of the players that are driving new solutions to the market, including service providers, end users, infrastructure, software and technology vendor.

The ecosystem offers members technical support technology training, technology matchmaking, co-marketing opportunities and more. These programs help companies to optimally utilize Intel technologies in their solutions, and facilitate joint collaboration.

There are now over 400 Ecosystem Partners.

Find out more: https://networkbuilders.intel.com/

Image credits

  • Digis Squared social media and blog banner image: Intel / background Kenny Luo
  • The Intel® and Intel® Network Builders logo and graphics are copyright and trademark Intel.
  • The “digis2” logo is copyright and trademark Digis Squared Limited.

New office in Angola supports business expansion across southern Africa

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In conversation with CEO and Founder Ziad Khalil, we discuss how Digis Squared’s new office in Angola supports business expansion across southern Africa.

Digis Squared Ltd, the UK-based managed services, system integration and telecoms consulting specialists, continues the expansion of its global footprint with the opening of new offices in Luanda, Angola this month. This latest announcement builds on solid business growth at Digis Squared, and enhances support to clients in the southern region of Africa.

Digis Squared’s London HQ, and Technology & Customer Support Centre in Cairo now have over 180 staff, an increasing team in the Dubai office opened in December, plus additional staff in-country embedded in clients’ offices in Europe, the Middle East and Africa. The announcement today builds on the celebrations of Digis Squared’s fifth year in business, and their #WeAre5 campaign.

Ziad Khalil, CEO and Founder at Digis Squared, shared his insights into why the business is investing here in Angola, now,

“Our clients and partners have demonstrated their trust in the Digis Squared team and our capabilities, and as our commitment in the region continues to expand, this is reflected in our new investment in Angola. With increasing numbers of significant engagements locally, and across Africa, now is the time for Digis Squared to invest and open a new office in Luanda.”

With business continuing to expand across central and southern Africa, the new office space in Luanda will provide a regional hub, and ensure that the growing Digis Squared team has a Covid-19 secure space to meet clients, and collaborate in-person safely.

“2021 continues to be another year of significant success and growth for the Digis Squared team. The work we undertook for clients in 2020 addressed massive changes in mobile network demand caused by the pandemic, re-dimensioning and optimising network performance,” commented Ziad.

“This significant investment in new offices in Luanda, strengthens our commitment to clients in Angola and across the southern Africa region. The facilities will enable our local team to provide enhanced support to new and extended contracts, as our business continues to expand.”

“As 2022 approaches, and new technology deployments continue at pace, this location is ideally situated to deliver further business expansion and enhanced presence in the region for Digis Squared,” Ziad added. “This investment strengthens the local support and capabilities we can deliver to our clients and staff, and demonstrates our commitment to them.”

In conversation with Ziad Khalil, Digis Squared CEO and Founder.

If you or your team would like to discover more about our capabilities, please get in touch: use this link or email sales@DigisSquared.com .

Keep up to speed with company updates, product launches and our quarterly newsletter, sign up here.

Digis Squared, independent telecoms expertise.

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  • Digis Squared social media and blog banner image: Mohamed Hamdy

Digis Squared Open RAN projects and capabilities

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Digis Squared Open RAN projects and capabilities  |  Mohamed Hamdy shares details of Digis Squared’s Open RAN capabilities and describes the types of projects the team are currently working on.

This is the second in a series of blogs focussing on Open RAN, where Mohamed Hamdy, Chief Commercial Officer at Digis Squared, and AbdelRahman Fady, CTO, share their insights.

“The Digis Squared team believe that 100% of mobile operators and CSPs will move to Open RAN models sooner or later. Each MNO will deploy Open RAN according to their strategy, either in rural areas or in urban areas, and that’s why we’re giving strategic and operational focus to this.”

Mohamed Hamdy, CCO at Digis Squared

Digis Squared’s Open RAN expertise, solutions & capabilities

Mohamed, what insights can you share with us on the Open RAN work being undertaken at Digis Squared?

“The Digis Squared team believe that 100% of mobile operators and CSPs will move to Open RAN models sooner or later. Each MNO will deploy Open RAN according to their strategy, either in rural areas or in urban areas, and that’s why we’re giving strategic and operational focus to this.

The Digis Squared team started very early to build their competencies, expertise, tools and portfolio for Open RAN, as well as building a dedicated service portfolio to help MNOs to adapt their network architecture to the Open RAN model. Today, we provide insight-led multi-system and multi-vendor expertise across the entire network lifecycle.”


Digis Squared OpenRAN expertise, solutions and capabilities

“Our work tries to address five key challenges we frequently see when working with clients,

  • Lack of confidence in OpenRAN solutions
  • Sub-optimal performance with a limited vendor feature set
  • Delayed operator & vendor deployment
  • Duplicated operator & vendor interoperability testing for HW & SW
  • Lack of SI expertise for successful deployment

To address these issues we,

  • Provide independent, interoperability and performance benchmarking, for example, by working with EANTC
  • Undertake advanced E2E troubleshooting
  • Deliver extensive system release validation
  • Provide direct access to Open RAN expertise and experience in design, integration and deployment

And thereby deliver,

  • Minimised deployment costs
  • Accelerated time to value
  • Richer vendor feature set through roadmap alignment
  • High performing Open RAN solutions
  • And, successful Open RAN deployments.”

In conversation with Mohamed Hamdy, Digis Squared Chief Commercial Officer.

How can Digis Squared help you with Open RAN?

The Digis Squared team are here to help, and can provide their experience, AI-led tools, and capabilities to help operators and CSPs with all aspects of Open RAN strategy, testing and deployment optimisation.

  • We provide the industry with a range of OpenRAN related services including integration, performance benchmarking and systemisation.
  • Collaborate with operators, vendors, system integrators and research institutes to promote and accelerate OpenRAN ecosystem development, focused on,
    • System Integration
    • Interoperability between vendor components
    • Release validation
    • End to end performance benchmarking
    • Trials and PoCs.
  • Showcase and promote OpenRAN within the industry (TIP, O-RAN, GSMA)
    • Capacity solutions, cost-effective rural coverage, 5G solutions.

This Digis Squared Open RAN blog reveals some of the capabilities we have, and if you or your team would like to discover more about our OpenRAN capability, or other elements of the work we do, please get in touch: use this link or email sales@DigisSquared.com .

Read AbdelRahman Fady’s blog, CTO insights into Open RAN features and vendor flexibility.

Keep up to speed with company updates, product launches and our quarterly newsletter, sign up here.

Digis Squared, independent telecoms expertise.

Abbreviations

  • CSP Communications Service Provider (ComSP)
  • SI System Integration

Image credit, Digis Squared social media and blog banner image: Charlotte Harrison

CTO insights into Open RAN features and vendor flexibility

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Open RAN  features and vendor flexibility | Digis Squared CTO AbdelRahman Fady shares his insights.

In this series of blogs focussing on Open RAN, AbdelRahman Fady, Digis Squared CTO, and Mohamed Hamdy, Chief Commercial Officer, share their insights.

In this first blog, AbdelRahman considers traditional, legacy RAN implementations, why Open RAN is needed, and the benefits and options it brings. He looks at technical features and vendor selection considerations, and how to balance features, flexibility and efficiency.

Open RAN features and vendor flexibility: a technical overview

AbdelRahman talks us through traditional legacy RAN implementations, and the new architectures and benefits of Open RAN.

“Mobile networks comprise two domains: the Radio Access Network (RAN), and the Core Network (Core).

  • RAN: the final link between the phone and network. Includes the antennas and towers we see on top of buildings, as well as base stations. The RAN base station digitises the signal to and from devices. One of the most expensive parts of the network.
  • Core: Provides access controls, authentications of users, routes calls, handles charging and billing, manages interconnect to other networks and internet. Ensures continuity of connection as a user moves and travels from one RAN tower to another.

Traditional, legacy RAN: hardware and software are very closely linked; selecting a vendor for the traditional RAN implementation guarantees performance, however it also constrains feature roadmap. A lack of interoperability means that there is little choice in where equipment is sourced, or the ability to influence innovation; however, identifying the vendor responsible for any fault resolution is simple.

In legacy RAN implementations each single site has its own hardware, however there is no concept of pooling sites’ baseband processing, and this leads to inefficient utilisation of hardware resources.

Legacy sites still need a sufficient space for all the equipment, plus an excellent and reliable power source, and these requirements and limitations have a big impact on the MNO or CSP’s OPEX.

The total cost of ownership (TCO) of Radio sites is still very high, and this impacts the scale and pace of CSPs expansion plans, especially in city outskirts and rural areas; any expansions is completely locked into the current vendor’s equipment.

The drive for new RAN architecture has been powered by better resources utilisation through pooling, and more powerful processing through centralisation. Additionally, the introduction of machine learning (ML) concepts in handling radio resources, as well as reducing sites TCO. The new RAN model should provide CSPs with implementations that need far less space and power, thereby significantly reducing the OPEX.

Before addressing the new RAN architectures, we will first consider the main RAN components we have and how can we split them.

RAN solutions typically have three key components,

  • Radio Unit (RU): radio frequency signals are transmitted, received, amplified and processed
  • Baseband processing: all the digital processing over the signals, along with all the interfaces needed to the transport network, and the CPU functions of the site. Today we can split this function into,
    • Distributed Unit (DU): handling all real time processing over the signal
    • Centralised Unit (CU): non-real-time processing over the signals plus the main computational function for the signal.

3GPP has defined models to split the functions between DU and CU, and provide the CSP/MNOs with a high degree of freedom to deploy the most suitable split model according to their network readiness. With new RAN architectures, away from legacy solutions, there are different implementation options based on the location of DU and CU,

  • Distributed Cloud RAN
    • DU: co-located with RU on the same site, where the remote Radio Unit (RRU) is connected to the DU through fronthaul interface (eCPRI)
    • CU: co-located near(er) the Core, and connected to DU through mid-haul transport network with specific transport network requirements, and connected to the central network (CN) through the backhaul
  • Dual split Cloud RAN
    • DU: is located away from RU, within Edge Cloud. More than cell site could be connected to the same DU, however, the fronthaul requirements should be achieved by the transport network.
    • CU: co-located near(er) the Core, and connected to DU through the mid-haul transport network, with specific transport network requirements, and connected to CN through the backhaul
  • Centralised RAN DU & CU:  centralised in the same location, near to the CN

The selection of the architecture to be deployed, and the functional split model should be carefully considered, with particular awareness of the transport network readiness and capabilities.

DU and CU concepts are introduced along with the concept of virtualisation; now the HW and SW are not locked to a specific vendor and from here we can jump to the ORAN concept.

Open RAN aims to ensure that the interfaces between these components are standardised, interoperable and open – expanding the ecosystem of solutions and vendors, driving speed and diversity of innovation and opening up greater flexibility in deployment.”

Benefits: Open RAN features and vendor flexibility

“Open RAN aims to deliver greater flexibility and vendor choice. When this is implemented as vRAN, the open and flexible architecture virtualizes network functions in software platforms based on general purpose processors.”

Together Open RAN as vRAN can deliver,

  • Cost savings: virtualised network, with containerised components – true scalability and cost management.
  • Sharing via network function virtualisation – one or more virtual machines run different software and processes, on standard high-volume servers, without the need for custom hardware appliances for each network function – enables multiple operators to securely run segregated networks, side by side on the same platform. In the future, this will also enable network sharing through software.
  • Vendor choice: contractual flexibility to balance features, cost, and adjust future decisions; opening up and standardising interfaces gives a greater choice of vendor solutions.
  • Third-party testing: plug-fests and independent testing will give MNOs and CSPs greater clarity on capability and interoperability, enable benchmarked KPIs, and test-labs will develop deep knowledge of quirks and capabilities of different systems.

Open RAN architecture

“The model above shows the new open interfaces available as part of Open RAN. These have been introduced between fully virtualised nodes with the newly standardised concept of RIC (RAN intelligent controller, with near RT RIC and non real time RIC options) for controlling the radio resources and features. They enable huge opportunities for new vendors to innovate new algorithms and features to enhance the overall performance of the new system supported with Machine Learning and Deep Learning algorithms.”

Challenges for the new RAN evolution

AbdelRahman, you have shared a lot of technical insights into the changes in RAN technology, and the benefits the new standards and architecture OpenRAN will bring. But let’s balance that out, it can’t all be good news!

AbdelRahman, what do you consider to be the three greatest challenges currently?

  1. “Performance: For sure, comparing the performance of very mature solutions from vendors who deployed very early, against the very latest ORAN vendors solution is not very fair! There is still a long way to go to reach good maturity for ORAN solutions
  2. Real interoperability: Actually, one of the big issues of the ORAN nowadays is the full interoperability between OS, SW, HW and orchestrators vendors. In reality, today, not all vendors are compatible for the time being, and that’s why, before deployment, CSPs still need to do IOT interoperability testing of the solution
  3. Infrastructure readiness: In ORAN the fronthaul interface is mostly conveying real time data and signalling. That’s why we need to adopt very strict performance requirements between sites and EDGE clouds or Central clouds according to the selected split options.”

In conversation with AbdelRahman Fady, Digis Squared CTO.

A whole new world of acronyms

Let’s answer some common queries!

Is cloud RAN the same as Open RAN? And what about vRAN?

  • Cloud RAN / C-RAN: centralised, consolidating the baseband functionality across a smaller number of sites in the telco’s network and cloud.
  • Virtualised, vRAN: more open and flexible architecture which virtualizes network functions in software platforms based on general purpose processors.
  • Open-RAN (notice the hyphen!): uses new open standards to replace legacy, proprietary interfaces between the baseband unit (BBU) at the foot of the cell tower and the remote radio unit (RU) at the top of the tower.

What is the difference between O-RAN, OpenRAN, Open-RAN and Open RAN?

  • O-RAN: an organisation, the O-RAN Alliance. Work to support open standards.
  • OpenRAN: a standard written by TIP, Telecom Infra Project.
  • Open-RAN (notice the hyphen!): uses new open standards to replace legacy, proprietary interfaces between the baseband unit (BBU) at the foot of the cell tower and the remote radio unit (RU) at the top of the tower.
  • Open RAN: industry-wide interface standards that enable RAN equipment and software from different vendors to communicate.

How can Digis Squared help you with Open RAN?

The Digis Squared team are here to help, and can provide their experience, AI-led tools, and capabilities to help operators and CSPs with all aspects of Open RAN strategy, testing and deployment optimisation.

  • We provide the industry with a range of OpenRAN related services including integration, performance benchmarking and systemisation.
  • Collaborate with operators, vendors, system integrators and research institutes to promote and accelerate OpenRAN ecosystem development, focused on,
    • System Integration
    • Interoperability between vendor components
    • Release validation
    • End to end performance benchmarking
    • Trials and PoCs.
  • Showcase and promote OpenRAN within the industry (TIP, O-RAN, GSMA)
    • Capacity solutions, cost-effective rural coverage, 5G solutions.

If you or your team would like to discover more about our OpenRAN capability, or other elements of the work we do, please get in touch: use this link or email sales@DigisSquared.com .

Read CCO Mohamed Hamdy’s blog, Digis Squared Open RAN projects and capabilities.

Keep up to speed with company updates, product launches and our quarterly newsletter, sign up here.

Digis Squared, independent telecoms expertise.

Sources

  1. Nokia
  2. Mavenir 1 and 2

Abbreviations

  • CN: Central Network
  • CSP: Communications Service Provider (ComSP)
  • CU: Centralised Unit
  • DL: Deep Learning (AI)
  • DU: Distributed Unit
  • eCPRI: enhanced Common Public Radio Interface
  • HW: hardware
  • ML: Machine Learning (AI)
  • NFV: Network Function Virtualization (=VNF, Virtualized Network Function)
  • PoC: Proof of Concept
  • RAN: Radio Access Network
  • RIC: RAN Intelligent Controller
  • RU: Radio Unit
  • RRU: Remote Radio Unit
  • SW: software
  • VNF: Virtualized Network Function (= NFV, Network Function Virtualization)

Image credit, Digis Squared social media and blog banner image: Andy Newton @bacchanalia, The Floating Harbour, Bristol dock, UK.

Intel case study | Video & TCP optimisation for Tier 1 MNO

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As mobile data usage continues to increase globally, it becomes ever more vital to ensure that mobile network infrastructure is optimised to maximise data throughput efficiently and continue to deliver excellent customer Quality of Experience. This case study looks at some recent System Integration work Digis Squared delivered to a Tier One Operator in the Middle East, which achieved over 30% improvement in mobile data downlink throughput.

Data growth – why optimisation will always be vital

Forecasts of mobile data growth are based on difficult to imagine numbers: exabytes.
1EB = 1 exabyte = 1000000000000000000 bytes = 1,000 petabytes = 1 million terabytes = 1 billion gigabytes


Digis Squared comparison of global mobile data traffic forecasts, source data [1] and [2]

Whilst mobile data forecasts vary significantly – in the data set shown above, Ericsson and Cisco have a 75% variance in their 2026 forecasts – it is clear that mobile data traffic will increase significantly in the next 5 years.

With over 106 5G network launches so far globally [5], 5G is forecast to account for as many as 1.2 billion connections by 2025 [6], and the GSMA estimate over 20% of these mobile connections – a substantial amount of this mobile data traffic – will be carried over new 5G networks by 2026.


Global 5G network rollout, [5] [7]

Data varies by source, but today video traffic is estimated to account for over 60% of all mobile data traffic, and some forecasts project it will increase to 77% by 2026 [1]. Therefore, the ability to optimise mobile data traffic, particularly for video usage, is of great importance to Communication Service Providers (ComSPs), and this is primarily achieved via the optimisation of TCP.

Video & TCP optimisation: vital for delivering excellent customer QoE

Transmission Control Protocol (TCP), is the key transport protocol for all internet traffic; it drives video streaming, file transfers, web browsing, and communications. Additionally, it establishes and manages traffic connections and congestion, handles transmission errors, and enables us to share resources with billions of connected devices, globally, simultaneously.

TCP is ever-evolving, to address new issues and continually improve optimisation as new technologies are deployed. Without efficient tuning, TCP can cause more optimisation issues than it solves. An optimised TCP implementation delivers increased goodput (lower error rate in data throughput), improved network efficiency, high TCP transfer speeds, lower retransmission rates, and more consistent TCP round-trip times – and who doesn’t want all of that?! All of this translates into improved Quality of Experience for customers, and as our expectations of device experience continue to rise, TCP becomes ever more vital.

With mobile data traffic rising exponentially, the increasing pace of 5G deployment, and growth in data-intensive video calls, video content and online gaming, the need for CSPs to optimise their network has never been greater.

Intel case study | Video & TCP optimisation for a Tier One Operator in the Middle East

In 2020 Digis Squared was selected by a Tier One Operator in the Middle East to manage the entire System Integration of end-to-end services and implementation for video and TCP optimisation on top of the packet core, over 3 core sites.

The solution implemented by the Digis Squared team was built with compute resources utilising 2nd generation Intel® Xeon® Scalable processors.

Yasser ElSabrouty, Digis Squared Co-Founder and System Integration Business Unit Director, explained that “Selecting Intel processors ensured we could confidently deliver the performance and reliable scalability that is vital for efficient and demanding TCP optimisation.  Customers’ expectations of QoE continue to escalate. The pandemic has normalised video interactions far faster than any forecast. We are all experiencing more video calls for communication to mitigate lack of in-person interactions with friends, family, clients and colleagues due to lockdowns and changed working practices. Plus, there is far greater use of video on social media and content platforms as we try to alleviate boredom and entertain each other. As 5G rolls out, people will expect continued improvements – buffering, patchy connectivity, dropped video calls all immediately impact network reputation. Maintaining efficient and optimised TCP requires solutions built on expertise, investment and the right equipment.”

“Working for this Tier One client, the Digis Squared team project managed the integration of this solution, selecting and managing vendors, implementing all elements of hardware and software, and optimising the solution to deliver the maximum efficiencies across the data network.”

“The project delivered considerable benefits to the client, and end customers. The Digis Squared project team benchmark data measured,

  • a 27% increase in processing cores [3]
  • 50% increase in bandwidth over previous generation Xeon processors [3]
  • 30% down link throughput enhancement, thanks to the data traffic optimisation achieved. [4]

We’re really proud of what we’ve been able to achieve for this client, knowing that their end-users will benefit from improved QoE that they can really see.”

In conversation with Yasser ElSabrouty, Digis Squared Co-Founder and System Integration Business Unit Director.

This article appeared first on the Intel Network Builders blog.

Additionally, it is available as a stand-alone white paper here.

If you or your team would like to discover more about our System Integration capability, video and TCP optimisation, or other elements of mobile network optimisation, please get in touch: use this link or email sales@DigisSquared.com .

Keep up to speed with company updates, product launches and our quarterly newsletter, sign up here.

Digis Squared, independent telecoms expertise.

Sources

  1. Ericsson: Mobile data traffic outlook
  2. Researchgate (Cisco)
  3. Dell EMC Spec Sheet
  4. Digis Squared project data (first published in this blog post)
  5. GSMA Future networks
  6. GSMA Future networks
  7. GSMA Intelligence Global Mobile Trends 2021 Report

Abbreviations

  • CSP Communications Service Provider (ComSP)
  • EB exabyte = 1000000000000000000 bytes = 1,000 petabytes = 1 million terabytes = 1 billion gigabytes
  • TCP Transmission Control Protocol

Image credits

  • Digis Squared social media and blog banner image: Linda K Nicely
  • The Intel® Network Builders logo and graphics are copyright and trademark Intel.
  • The “digis2” logo is copyright and trademark Digis Squared Limited.

Technology sunset & spectrum refarming

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Technology sunset & spectrum refarming | Navigating a path from legacy technologies to the future.

Amr Maged, Co-Founder & Chief Strategy Officer at Digis Squared, considers the benefits and issues of refarming spectrum, and the scope and timelines of such projects. This blog post follows on from CTO Abdelrahman’s previous Technology Sunset blog, and was first published here as a downloadable short, graphic-rich document on LinkedIn.

The background

As 5G rollouts gather pace globally, and new technology deployments continue their unstoppable march, many networks are also grappling with what to do about legacy technologies. In 1991 Radiolinja launched 2G in Finland, and 2001 brought the first 3G launch, achieved by NTT DoCoMo in Japan – both network technologies are still in active commercial use around the world, but for how much longer? Technology sunset strategies consider how to re-allocate and optimise finite spectrum resources, efficiently, whilst taking care of customer impact.

Pro’s & con’s of re-farming 2G and or 3G spectrum

2G & 3G (Keep one of them, but arguments apply to both)

Why keep it?

  • When VoLTE not available, voice calls fall back to 2G or 3G network (CSFB, circuit-switched fall back).
  • Calls from a VoLTE handset to a 2G/3G handset use CSFB over 2G /3G.
  • Early implementations of eCall service in Europe use 2G/3G for the voice call element of the mandatory service – no plans were made to be able to replace the equipment in these vehicles.
  • Most IoT devices don’t need the high bandwidth 4G and 5G deliver, and can make service cost-prohibitive.

Why switch it off?

  • Re-allocate spectrum: new 4G and 5G technologies are more efficient and more capable, delivering enhanced speed, bandwidth and security.
  • Operational cost optimisation.
  • IoT: LPWA-LTE, NB-IoT and other new technologies maximise battery life and battery cost, data usage, indoor coverage, and have lower cost modules.
  • Regulatory driven spectrum reallocation and or harmonisation.

2G

Why keep it?

  • 3G devices can “roll down” to 2G connectivity.
  • Support 2G-only consumer handsets –typically low income, or elderly seeking simpler devices.
  • Support 2G-only M2M devices
    • Early M2M devices in tricky to reach geographies, or deep within long-life equipment (cars) and never designed for replacement.
    • Early implementations of eCall service in Europe (uses 2G/3G for the voice call element of the mandatory service.)
    • IoT devices deep inside buildings (indoor coverage).
  • 2G base stations can be installed further apart – robust voice services over a large territory, more efficiently than 3G.
  • Smaller carrier bandwidth spare, enables more bandwidth for 4G and 5G.

Why switch it off?

  • Generally, lower number of 2G-only users than 3G, and lower ARPU.
  • 2G delivers lower spectral efficiency than 3G.
  • 2G voice calls are lower quality than 3G.
  • Very limited data services in areas with no 4G coverage.

3G

Why keep it?

  • Some MNOs: 3G network costs not yet amortised.
  • 3G & HSPA provide far better data experience than 2G.
  • Multi-RAB concept gives 3G users the option of having both voice and data services simultaneously.
  • Performance of 3G interoperability with 4G + 5G is far better than 2G interoperability with 4G + 5G.

Why switch it off?

  • 3G devices can “roll down” to 2G connectivity.
  • Re-use 3G spectrum to add more capacity to LTE networks + expand 5G networks.
  • 3G is not operating in band 3 (1800 MHZ band), the most famous 4G band – this is a significant limitation from the point of view of technology combination.

Technology sunset timeline

Whilst all projects vary, this indicative timeline highlights key milestones on the path from legacy technologies to the future.

1. Assess status

  • License end dates and regulatory requirements
  • Assess spectrum availability
  • Re-farm existing spectrum
  • Options/ timeline to acquire
  • Government expectations around new technology deployment
  • Competitor activity & plans
  • Infrastructure contract status incl backhaul, transmission and towers
  • Subscriber network stats and forecasts (incl roaming and coverage)
  • Other market constraints (MVNO contracts, M2M installed base and limitations….)
  • Assess the RRUs & BBUs used, and their current configuration

2. Identify options

  • Agree governance and scope
  • Migration impacts, risks and mitigations, including,
    • Coverage and infrastructure forecasts
    • Brand perception
    • Contracts: new and revised infrastructure and support contracts, extra fibre backbone services, additional project resource, lower energy consumption
    • Savings delivered and investments needed
    • Roaming contracts
  • Timescale: lights out on one day, or slower decommissioning cells and degrading network over 6 months to 2 years?

3. Gain agreement

  • Telecom Regulatory approval needed? Co-ordinated sunset activity and communication across sector? Is a shared legacy network required?
  • M2M: complex customer migration plans (may involve Energy Regulator), consider how to recognise costs
  • Elderly groups: address concerns and sell simple handsets
  • Board sign-off

4. Detailed plans

  • Date to stop selling new 2G / 3G subscriptions
  • Consumer: campaign to churn and recycle legacy handsets, maintain affordable and simple option
  • Extend coverage address gaps
  • Work with M2M partners and customers (many are international, and may have experience in other territories)
  • IoT /all contracts: ensure provision for future technology sunsets
  • Procurement & legal contracts
  • Training: ops, retail and customer-facing staff
  • Return to 3, and repeat as needed

5. Implement

  • Maintain quality of service and extend coverage, handle increased data demand, and continue to optimise networks as balance changes
  • IoT: don’t underestimate complexity + some old implementations may be undocumented
  • Learn lessons: will need to switch off other networks in future

Discover more

This blog post is also available as a stand-alone white paper.

Amr Maged, Co-Founder & Chief Strategy Officer at Digis Squared.

Please get in touch: use this link or email sales@DigisSquared.com .

Keep up to speed with company updates, product launches and our quarterly newsletter, sign up here.

Digis Squared, independent telecoms expertise.

Sources

  1. The Mobile Economy 2020, GSMA / GSMA Mobile Intelligence, Q1 2020
  2. Mobility Report, Ericsson, June 2020
  3. Legacy mobile network rationalisation, experiences of 2G and 3G migrations in Asia-Pacific, GSMA, May 2020

Abbreviations

  • ARPU: Average Revenue Per User
  • BBU: Baseband Unit
  • CAT-M1: see LTE-M.
  • CSFB: Circuit Switched Fallback
  • NB-IoT: Narrowband Internet of Things. One of two data networking technologies available on 4G (the other is LTE-M, aka CAT-M1). Intended for narrow band (250 kbps) low power data applications and does not support voice communications.
  • LTE-M: LTE Machine Type Communication. Also known as Cat-M1. One of two data networking technologies available on 4G (the other is NB-IoT). Provides considerably higher bandwidth (1Mbps), supports voice and full mobility.
  • RRU: Remote Radio Unit
  • VoLTE: Voice over LTE

Image credits: Quino Al