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Edge/MEC

Edge computing and multi-access edge computing (MEC) place processing close to where data is generated — at the network edge rather than in distant centralized clouds — to cut latency and reduce backhaul. For applications that demand fast, local responses, such as industrial automation, computer vision, AR, and autonomous systems, the edge is often what makes them viable. Edge is tightly linked to 5G standalone, private networks, and AI inference, and is a key area where operators, hyperscalers, and enterprises both compete and partner. For decision-makers, the questions are where edge genuinely beats centralized cloud and how to balance on-premises, network-edge, and public-cloud processing. This channel covers edge and MEC across operator, hyperscaler, and enterprise deployments — architectures, partnerships, and use cases — with analysis of where moving compute to the edge actually pays off.

OneWeb and AWS collaborate to provide cloud-based connectivity

OneWeb and AWS collaborate to provide cloud-based connectivity
OneWeb has announced that it has signed a letter of intent with Amazon Web Services EMEA SARL (AWS) to explore providing cloud-based connectivity and innovative services to customers worldwide. The collaboration between OneWeb and AWS aims to expand both horizontal and vertical services to provide customizable and integrated solutions for edge-to-edge operations.

42. The Life Cycle of a Cell Site: Maintenance and Modification – Part Three

5G Guys Podcast
Welcome back to our series on Lifecycle of a Cell Site! Today we are focusing on the Modifications and Maintenance phase of the network. As the 5G guys, we understand that maintaining and modifying a cellular network is a complex, ongoing process that...

Transforming the Future of the Telecom Workforce with Leticia Latino-Van Splunteren

5G Talent Talk with Carrie Charles
Joining host Carrie Charles on today's episode of 5G Talent Talk is Leticia Latino Van-Splunteren, CEO of Neptuno USA. Together, they explore the way 5G technology is transforming the telecom industry and discuss the challenges and opportunities for building a talented and diverse workforce in this rapidly evolving field. In this episode, you'll learn about the key skills and knowledge that are in high demand for 5G jobs, the role of lifelong learning in building a successful career in telecom, and the importance of mentorship and collaboration for advancing diversity and inclusion in the workplace. In this episode, Leticia shares her insights on how companies can attract and retain top talent in a highly competitive market, and why embracing innovation is essential for staying ahead in the fast-paced world of 5G.

Schneider, Capgemini and Qualcomm Collaborate for 5G-enabled Private Networks Automated Hoisting Solution

Schneider, Capgemini and Qualcomm Collaborate for 5G-enabled Private Networks Automated Hoisting Solution
Schneider Electric, Capgemini, and Qualcomm Technologies have announced their collaboration on a first-of-its-kind 5G-enabled automated hoisting solution. The three companies have joined efforts on the design and installation of the solution at Schneider Electric’s hoisting lab in Grenoble, France. Replacing wired connections with wireless and unifying existing wireless connections from Schneider Electric’s industrial automation system, the 5G Private Network solution demonstrates how it can simplify and optimize digital technology deployment at scale across industrial sites — from steel plants to ports.

Airtel surpasses 10 million unique customers on its 5G network

Airtel surpasses 10 million unique customers on its 5G network - TeckNexus

5G Future Forum accelerating 5G and Edge Compute solutions around the world

5G Future Forum accelerating 5G and Edge Compute solutions around the world
The 5G Future Forum (5GFF) will lead a first-in-the-world demonstration that is expected to change the evolution of music collaboration. Using the 5GFF Edge Discovery Service (EDS) API, which enables devices to identify and connect to the Mobile Edge Compute (MEC) site providing the lowest latency closest to them, the performance will showcase the value of the interoperability of the EDS API, leveraging Open Sesame's audio platform to sync guitar players across New York, USA (Verizon), Toronto, Canada (Rogers), and London, England (Vodafone).

Deutsche Telekom and Microsoft partner and trial private 5G networks for pharmaceutical enterprise

Deutsche Telekom and Microsoft partner and trial private 5G networks for pharmaceutical enterprise
DT's new offer has standardized 5G campus network solutions. The end-to-end solution is based on Microsoft Azure's private MEC platform, featuring an edge platform and networking capabilities that will allow your business to utilize modern connected applications. This concept was specifically designed with small and medium businesses in mind, as well as those who already have an established landscape of Azure products at their disposal.

Operators achieve success in the transition to renewable energy

Operators achieve success in the transition to renewable energy
According to an analysis by the GSMA, approximately 25% of all electricity purchased for the worldwide mobile industry is now derived from renewable sources. This indicates that operators are making major strides in order to achieve their net zero goals.

Telstra CEO thinks the role of operator is to become an ecosystem builder

Telstra CEO thinks the role of operator is to become an ecosystem builder
Telstra CEO Vicki BradyBrady thinks the role of the operator is to become an “ecosystem builder” that brings together technologies such as 5G, AI, automation, edge computing, and “an explosion of applications”. She also warned that if operators don’t change, they run the risk that the “value created over our networks gets captured by others.” Indeed, Brady advised operators to get comfortable with the idea of not always being in control of the end-to-end solution.

Navigating the Changing Landscape of Telecom with Chad Rasmussen of Y-COM

5G Talent Talk with Carrie Charles
As we head further into 2023, new trends come surfing in the telecom industry. In such an ever-changing landscape, how does a company meet the changing needs of its clients? In this episode, Chad Rasmussen, President and CEO of Y-COM, discusses his unique approach to paving the way for the future of telecom. He shares how Y-COM has evolved to stay ahead of the curve, connecting the dots between the trends and providing cutting-edge solutions to their clients. He discusses how Y-COM navigates the challenging labor market to recruit and retain top talent. Do you want to hear more about the latest trends and future outlook of the telecom industry? Tune in to this episode to hear Y-COM's role in shaping the future of connectivity with Chad Rasmussen.

Industry throws weight behind GSMA API initiative | CAMARA Alliance

Industry throws weight behind GSMA API initiative - CAMARA Alliance - MWC 2023
The GSMA announced a new industry-wide initiative called GSMA Open Gateway, a framework of universal network Application Programmable Interfaces (APIs), designed to provide universal access to operator networks for developers. Launched with the support of 21 mobile network operators, the move is aimed at changing the way the telecoms industry designs and delivers services in an API economy world.

Cisco and NTT Collaborate to Bring Private 5G to Enterprise Customers to Accelerate Industry Transformation

Private networks - TeckNexus
Cisco and NTT announced plans to collaborate to drive Private 5G adoption across the Automotive, Logistics, Healthcare, Retail, and Public sectors. Together, the companies can rapidly enable critical Industry 4.0 capabilities such as push-to-talk ‘walkie talkie’ communications, automated guided vehicles (AGVs), always-connected PCs (for digital frontline workers), machine vision (e.g., predictive maintenance, PPE detection), and more.

Frequently Asked Questions

What’s the difference between ‘the cloud’ and ‘the edge’ in telecom?
Cloud computing typically runs in a relatively small number of large, centralized data centers, often located far from any individual user, which is efficient for many workloads but introduces unavoidable physical distance, and therefore latency, between where data is generated and where it’s processed. Edge computing, specifically MEC, places computing resources much closer to where data actually originates, at cell towers, base stations, or local facilities, cutting the round-trip delay for applications where that distance meaningfully matters. The tradeoff is that edge sites generally have far less raw computing capacity than a massive centralized data center, so edge deployments tend to handle specific, latency-sensitive workloads locally while still relying on the broader cloud for less time-critical processing and coordination.
Is MEC mainly a telecom-specific concept, or does it apply more broadly?
It started as a mobile-network-specific concept, originally called Mobile Edge Computing when ETSI introduced it in the mid-2010s, focused on placing computing resources within mobile radio access network infrastructure. ETSI broadened the concept to Multi-access Edge Computing in 2017 specifically to extend it beyond cellular networks to also cover fixed-line broadband and Wi-Fi access, recognizing that the underlying need, computing resources close to the point of data generation, applies regardless of access technology. Current standards work is extending the concept further still, with ETSI’s MEC group releasing Phase 4 specifications in late 2025 focused on developer-friendly APIs for vertical industries and explicit alignment with emerging 6G requirements.
What applications actually benefit from edge computing?
The clearest use cases are ones where milliseconds genuinely matter, or where large amounts of locally generated data would otherwise need to travel back to a distant data center unnecessarily. Autonomous vehicles need to process sensor data and make navigation decisions in near real time, where even modest added latency could be meaningful for safety. Industrial automation and predictive maintenance benefit from edge processing of sensor data from factory equipment. AR and VR applications need responsive, low-latency rendering support. Smart city video analytics, like traffic monitoring, generates enormous volumes of video data far more efficient to process locally. Increasingly, running AI inference closer to users for real-time applications is becoming one of the most significant edge use cases of all.
Why are telecom operators excited about edge computing as a revenue source?
Beyond reducing backhaul costs, edge sites give telecom operators something cloud hyperscalers don’t have by default: physical proximity and direct integration with the radio network across thousands of locations nationwide. This positions operators uniquely to offer latency-sensitive computing services that a centralized cloud data center simply can’t match on responsiveness, regardless of raw computing power. Operators are increasingly positioning these edge locations specifically as AI inference points, sometimes described as compact ‘AI factories,’ capable of running real-time AI workloads close to users. This opens a genuinely new monetization path beyond selling connectivity itself, letting operators compete in the broader computing and AI infrastructure market using distributed physical infrastructure cloud-only providers would need years to replicate.
How mature is MEC deployment in 2026?
By 2026, MEC has moved well past the concept or early-pilot stage into active, expanding commercial deployment. ETSI’s MEC group has produced more than 50 technical specifications covering reference architectures, service enablers, and deployment guidelines, and released its Phase 4 work in late 2025, focused on developer-friendly APIs and explicit alignment with open-source projects and 6G preparation. Telecom operators worldwide are actively pairing MEC deployments with private 5G networks, AI workloads, and Open RAN integration in live commercial deployments rather than isolated trials. The technology continues to mature rather than being fully settled; convergence between MEC and Open RAN architectures remains an active area of development.
How does edge computing relate to private 5G networks?
Edge computing and private 5G networks are frequently deployed together because they solve complementary problems for the same enterprise use cases. A private 5G network provides dedicated, reliable, high-performance wireless connectivity across a facility like a factory or port, while edge computing provides the local processing power needed to actually act on the data that connectivity carries, without sending everything back to a distant cloud data center. A manufacturing facility, for example, might use private 5G to connect cameras and sensors across the factory floor, with an edge deployment at that same facility processing video analytics or controlling automated machinery in near real time. This pairing is one of the most common patterns in enterprise digital transformation projects today.
What’s the difference between edge computing and Open RAN’s ‘Cloud RAN’ concept?
Edge computing and Cloud RAN address related but distinct parts of the network. Cloud RAN refers specifically to running radio access network functions, the software controlling how a cell site transmits and receives wireless signals, on cloud-based, software-defined infrastructure rather than dedicated radio hardware. Edge computing, particularly MEC, refers more broadly to running general-purpose application workloads, not just radio network functions, close to the network edge, things like video analytics, AI inference, or industrial automation software. In practice, the two concepts increasingly converge physically, since the same edge infrastructure supporting Cloud RAN’s virtualized radio functions can often also host MEC application workloads on shared hardware.
What are the biggest technical challenges in deploying edge computing at scale?
Deploying edge computing at scale introduces several persistent technical challenges. Managing and orchestrating computing resources across potentially thousands of geographically distributed edge sites is meaningfully more complex than managing a small number of centralized data centers, since each edge location has limited physical space, power, and cooling capacity. Ensuring consistent security across so many distributed locations, each a potential point of vulnerability, requires more extensive security architecture than securing a handful of centralized facilities. There’s also a workload placement challenge: deciding which tasks genuinely benefit from edge processing versus which are better handled centrally, since over-provisioning edge capacity for workloads that don’t truly require it can be an inefficient use of limited, expensive infrastructure.
Private Network Leadership Awrads 2026

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