The telecommunication industry is undergoing a significant transformation. Just as manufacturing has evolved from manual labour to highly automated processes, automation is now making inroads into the telecom sector. Mobile network operators (MNOs) globally are being presented with new revenue opportunities in the radio access network (RAN) domain.
Traditionally, RAN has been a closed system with hardware tightly integrated with software from specific manufacturers, resulting in a market where only a few organisations dominate. However, with non-proprietary, open interfaces, MNOs can now utilise one supplier’s radios with another’s processors, a concept known as an open radio access network (ORAN).
With ORAN, operators can employ software-based network functions using standard commercial-off-the-shelf (COTS) servers. Several next-generation technologies are enabling this transition towards ORAN.
Next-gen automation enablers of ORAN
Cloud-native automation tools such as zero-touch provisioning (ZTP), continuous integration (CI)/continuous delivery (CD), cloud automation, artificial intelligence (AI), and machine learning (ML) enable the development of agile, flexible and efficient applications in dynamic ORAN environments.
ZTP
ZTP is an automated way of provisioning a service with no manual intervention. In a ZTP-enabled ORAN, network operations, such as fault detection and resolution, performance optimisation and security management, are automated. This enables operators to deploy and operate RAN networks more efficiently, with lower costs, fewer errors and a faster time-to-market for new services. It also provides greater flexibility in network management, and the ability to quickly adapt to changing network conditions and customer needs. Through ZTP, cell sites can be instantly and automatically configured by MNOs.
In addition, ZTP is relatively safe for RAN installation and facilitates deployment at multiple sites without the need for on-site visits. Notably, ZTP will be critical for dense 5G deployments when hundreds of sites will have to be configured.
Once the sites are configured, CI/CD in ORAN comes into play, automating updates and reducing the manual labour required on-site or in data centres, resulting in cost reductions.
CI/CD
In the telecom industry, CI/CD involves a set of practices designed to ensure the efficient delivery of RAN software. While adopting CI/CD for ORAN, two important factors must be considered. The first factor is disaggregation as hardware and software components come from different vendors, and the second factor pertains to physical components, such as servers and radios, within the RAN.
Once the network is provisioned, any new features, bug fixes, or software upgrades and downgrades are automated using CI/CD. Without automation, it can be a tedious and costly task to send personnel to sites for software upgrades and testing. CI/CD software automation enables upgrades and downgrades in seconds or minutes with no manual intervention, resulting in significant cost and time savings.
Furthermore, the integration, software upgrades and lifecycle management of disaggregated software components running on COTS hardware are enabling a new testing model. Under the model, software from various groups within an organisation is not tested in silos but rather under the overall CI/CD framework. By implementing CI/CD, MNOs foster greater collaboration among different ecosystem members, thereby driving innovation. It supports the onboarding and lifecycle management of multi-vendor, cloud-native network functions.
AI/ML
One of the key benefits of ORAN is its ability to leverage AI and ML algorithms to optimise network performance. In traditional RAN systems, network resource management is tightly integrated with the hardware, making it challenging to implement AI-driven techniques. In contrast, ORAN decouples software from hardware, enabling operators to deploy AI algorithms that can analyse vast amounts of data generated by the network and make real-time decisions to optimise performance. This can significantly improve network capacity, coverage and user experience, leading to innovation, cost reduction, and faster deployment of advanced wireless networks.
By automating various aspects of network management, AI minimises human intervention, thus reducing the operational expenditure (opex). For example, AI algorithms can predict equipment failures and automatically initiate preventive maintenance, reducing the need for site visits by technicians. Furthermore, as networks become more open and complex, AI can help operators detect and mitigate risks by continuously monitoring network traffic, identifying anomalies, and taking appropriate action. In addition, the ORAN Alliance specifications provide a framework for the use of AI and ML in long term evolution (LTE) and 5G networks.
The role of AI/ML in ORAN deployment is multifaceted and essential for the success of the new network architecture. As the telecom industry continues to evolve, the integration of AI/ML and ORAN will become increasingly important in shaping the future of wireless networks.
Cloud computing
Cloud technology is revolutionising networks by making them more adaptable and intelligent. One of the factors driving ORAN adoption is the aim to make mobile networking technologies cloud-based. Switching to a disaggregated software/hardware infrastructure allows operators to implement RAN functions as cloud-native applications and leverage cloud-centric technologies like AI and automation. Thus, the ultimate objective is to deliver fully cloud-based RANs, known as cloud RANs (C-RANs).
In a C-RAN, key networking functions are centralised in a baseband unit (BBU) hotel instead of being distributed as individual BBU base stations. BBU hotels are responsible for converting digital signals into radio waves. The single, central BBU hotels will allow wireless networks to become more flexible, scalable, and energy efficient. This is made possible through the disaggregated nature of new technological approaches like ORAN.
Cloudification is the foundation for setting up the network environment. Thus, RAN architecture needs to be cloud-native to facilitate automation.
Virtualisation
The complete virtualisation of RAN offers significant technical and business benefits, such as agility, flexibility and scalability. It supports innovations such as AI algorithms across RAN functions, enables networks to deliver ever-more capabilities at an optimised cost, and minimises MNOs’ capex and opex by breaking down silos.
With virtualised RAN (vRAN), service providers can quickly implement new capabilities and deliver enhanced services. They can upgrade virtual functions in software more quickly than they can upgrade embedded functions within proprietary systems. The technology also enables interoperability among RAN components and enhances supply chain security.
Moreover, vRAN provides a single uniform hardware platform across the core network. This simplifies network management, reducing operation and maintenance costs. The ability to run network functions from multiple vendors on the same hardware provides service providers with increased flexibility. An open platform can remove barriers to cross-domain innovation and facilitate the development of new use cases and services.
Big data analytics
Big data analytics is a helpful tool that allows MNOs to gain insights into their network performance and its impact on the subscriber experience. It provides a visual representation of patterns or abnormalities, helping MNOs understand what needs to be corrected to improve network performance for a better subscriber experience. It is an opportunity to review AI data and generate reports highlighting the positive impact of ML on the network. Analytics is deployed as rApps in the non-real-time RAN intelligent controller and utilises big data to provide an overall view of network conditions.
Telco deployments
In India, telcos have started exploring opportunities in the ORAN domain. For instance, Vodafone Idea Limited (Vi) is exploring ORAN and vRAN technologies to reduce the cost of 5G network deployment. For vRAN, the telco has implemented proof-of-concept (PoC) projects with Samsung in Tamil Nadu. By using vRAN and ORAN, Vi will benefit from vendor interoperability, resulting in lower deployment capex and total cost of ownership (TCO).
Other global operators, including NTT Docomo and Verizon, are also virtualising their RAN to yield cloud benefits such as improved resource utilisation, network agility and automation. However, to fully reap the benefits of the cloud, the system must be entirely fiberised.
Conclusion
The RAN ecosystem has evolved significantly from 2G to 5G. Moving forward, ORAN has the potential to bring in new revenue streams, lower capex, and provide operators with diversity advantages. With the help of new technologies, mobile operators can leverage ORAN by avoiding vendor lock-in, improving resource utilisation and reducing overall TCO.
To achieve these benefits, operators can leverage next-generation technologies to manage networks efficiently and optimise their key performance indicators, thereby improving the overall customer experience.
