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T2T (TelCo 2 TechCo) AGILITY - Challenges & Solutions

5G and the impact on Telecom Engineers Technical Skills

5G requires new technical skills for Telecom engineers. Concepts like programming, scripting, and automation, before reserved almost exclusively for software developers, are now also important for the Telecom field. A focus on software, microservices, virtualization and containers (e.g., Kubernetes and Docker) is crucial and apply to all 5G technology experts. It is no longer acceptable for a Telecom engineer to program every device through a command-line interface (CLI). The complexity requires software-defined programmability, orchestration, and automation.

Consequently, the following are some of the critical areas for Telecom engineer skills1:

  • Software-Defined Networking (SDN), for Routing and Switching,

  • Software-Defined Radio Access Networks (SDRAN), for the radio connection to mobile handsets and devices.

  • Network Function Virtualization (NFV), for physical network applications virtualization and functions such as gateways, firewalls, or load balancing or any specific Core Network Function (AMF, UPF, SMF, etc)

  • Containerized Network Functions (CNF), The nature of the 5G core network requires a cloud-native approach that uses web-scale, containerized network functions (CNFs) that are resilient and decomposed into microservices2.

  • Automation and orchestration, for handling changes almost immediately and efficiently based on the current conditions or workloads of the network.

Changing the Way We Work, Continuous Evolution

The traditional way of configuration through CLI at the network element level is disappearing, as we move to an almost completely virtualized network world where programmable devices and automation will drive most of what happens in networking.

Gone are the days when Telecom professionals were fully dedicated to developing exclusively Telecommunications technical skills, such as signaling analysis, transport technologies i.e., GPON, WDM, etc. We saw this trend in the late 2000s with the breakthrough of IP technologies. Every Telecom engineer required to develop a certain level of understanding about IP Technologies to be proficient enough on her/his daily work.

With the adoption of cloud technologies in the early 2010s and the subsequent adoption of these into the Telecom industry, virtualization has become a mainstream technical skill. Telecom vendors have adopted hardware-software decoupling schemes and many LTE networks are implemented under the NFV architecture. Besides IP, every Telecom engineer had to learn these new skills to stay updated. Next phase is a cloud-native network architecture.

The nature of the 5G network architecture requires new skills to incorporate into the Telecom knowledge, Artificial Intelligence (AI) and Machine Learning (ML) algorithms, Open Radio Access Network (ORAN), Internet of Things (IoT), big data, scripting and programming focused on automation.

Take as an example AI in Telecom Network Analysis:

Not long ago, Telecom Operators used to send field personnel onsite to periodically check up on network devices. This practice resulted in slow resolution times, errors, and high costs, resulting in negative impact on customers experience. Many unplanned on-site visits can be avoided with the use of AI: Algorithms can monitor millions of signals within a network to identify anomalies and determine root cause in real-time. Based on such insights, the Telecom Operator can react in time by load balancing, restarting the involved software, or sending field personnel to fix the issue only if the cause really requires it, and in this way, avoid outages before they happen or even end user notices. The demand for skilled professionals to implement, maintain and lead the use of these technologies requires a Telecom engineer proficient enough in his knowledge area but also, with sufficient understanding of software and AI.

Additionally, according to Harvard Business Review, the pandemic has accelerated the adoption of data analytics and AI among network operators. Telecom Operators already use AI and machine learning techniques to optimize network performance, improve customer satisfaction and retention, streamline their business processes for higher profit, and more.

Continuous Learning As A Way To Adapt to New Technologies

Professional development is a vital part of any engineering discipline. In the case of Telecommunications, with technologies moving at a rapid rate, it is our responsibility to keep learning and developing as the engineering world evolves.

Like in previous decades, to be a successful Telecom engineer, we must develop a strong sense of adaptability. Continuous learning is truly the core skill of a Telecom engineer to stay updated.

Continuous learning is the way to reach this adaptability in the Telecom fast-changing world. And as we all know, evolution means basically, adapt, or die.

Besides continuous learning, which other core skills do you think Telecom engineers must get to keep adapting?


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