A massive increase in multimedia consumption, a growth in digital services, higher uptake of user engagement platforms, and increasingly complex and dynamic traffic patterns are imposing new requirements on modern networks. Operators and vendors around the world are trialing and deploying open radio access networks (RAN) to modernise their network infrastructure. The advantages of this are manyfold, from a reduction in the total cost of ownership to opening up of new avenues of innovation and a diversified supplier ecosystem.
Although open RAN is yet to achieve mass commercialisation, global adoption is expected to bolster in light of the recent technological developments in the domain. Operators are leveraging next-generation technologies such as artificial intelligence (AI), machine learning (ML), virtualisation and data analytics to accelerate the automation of software components of the open RAN architecture. The integration of these innovations with open RAN creates numerous benefits. These include enhanced operational efficiency, more intelligent and scalable networks, accelerated time-to-market of new services and functions, and CAPEX and OPEX efficiencies.
A look at how these technologies are augmenting the open RAN landscape…
AI and ML are key to intelligent management and operation of networks for addressing the increasing network complexity. These technologies are being leveraged by mobile network operators (MNOs) worldwide to significantly improve the network performance of open RAN and automate operations. These technologies consist of algorithms that learn from experience and continuously improve the system. The algorithms further enable the operators to analyse enormous amounts of real-time traffic data and network load, without compromising network capacity. Additionally, these technologies enhance the end-user experience by enabling telecom service providers (TSPs) to provide the quality of experience demanded by consumers and enterprises. Thus, allowing TSPs to adjust network conditions and ensure proper load balancing, and, in turn, offering seamless transfer of active call or data sessions between channels or networks. Some use cases of these technologies in the open RAN domain include forecasting parameters, detection of anomalies in the system, traffic steering and prediction of failures.
Further, the O-RAN Alliance introduced the RAN Intelligent Controller (RIC), which is an entity of open RAN architecture responsible for RAN general operations as well as constant optimisation. It provides advanced control functionality with the support of data-driven approaches such as AI/ML tools to improve resource management capabilities. Leading open RAN solutions offer natively built-in AL/ML capabilities into the RAN architecture for the non-real time (non-RT) and near-RT RIC functions. ML models are trained in non-RT RIC rApps based on data received from different functions in the network. These are then used for analysis and to make inferences so as to provide the best end-user experience. With the commercial roll-out of 5G networks, AI and ML will have a much more comprehensive and transformative impact on the end-to-end network in an open RAN environment.
Zero-touch provisioning performs automated software installation and configurations, eliminating the need for manual intervention. Besides significantly reducing complexity in provisioning, it minimises time, errors and cost. Zero-touch provisioning is considered safe for RAN installation, and significantly helps in the deployment of hundreds of sites without requiring a site visit. While it will take time to drive automation towards zero-touch, it will be critical for dense deployment of 5G networks when a large number of sites will need to be configured.
Continuous integration and continuous delivery (CI/CD) is a methodology designed to accelerate the software development process and delivery with more frequent product releases. The presence of different components from various vendors makes CI/CD essential in the open RAN space. Through automation, CI/CD software allows upgrade/downgrade in seconds or minutes with minimal human intervention, thereby substantially reducing cost, time and errors as compared to site visits for testing and upgrades. Further, these updates can be monitored to evaluate their impact on end users and whether they are helping in achieving business goals.
The CI/CD approach has been recognised as a critical element for the software requirements of the RAN ecosystem. Leading cloud-native open RAN solutions provide CI/CD frameworks to enhance agility and flexibility for MNOs to launch new features, fix bugs in the system and implement software upgrades. Implementation of CI/CD software in the open RAN architecture can enable MNOs to collaborate with different ecosystem participants, thus fostering innovation.
Continuous network deployment processes such as CI/CD will drive the demand for edge computing for faster execution from network edges. Key benefits of deploying open RAN systems at the edge include lower latency, an enhanced user experience, alleviated network congestion, optimised network efficiency and locally enabled computing power for devices. Through these benefits, it opens up avenues for dense 5G use cases such as autonomous vehicles and internet of things (IoT), and enables immersive experiences. Further, disaggregated network in open RAN allows computing power to be pushed to the edge, while other processes remain at the core. Telcos can thus design and provide the network based on end-user applications.
Virtualised RAN (vRAN) is an agile approach to the deployment and management of RAN that virtualises RAN network functions and deploys them on cloud platforms. It employs network functions virtualisation that helps operators to control and route cellular resources more efficiently, which is crucial for 5G core networks. This allows interoperability among RAN components and enhances supply chain security. Moreover, virtualisation offers improved operational efficiency by using industry-established components for common tasks, thus eliminating the need for vendor-specific solutions and allowing operators to focus on business-specific components. It also provides greater flexibility in terms of functionality and capacity to meet the demands of 5G use cases. Finally, a wide adoption of vRAN can address the barriers in cross-domain innovation, leading to the development of new use cases and services.
According to a report by Analysys Mason, vRAN is the fastest-growing segment of cloud investment for operators, with spending forecast to reach $11 billion by 2025 at a compound annual growth rate (CAGR) of 132 per cent. Meanwhile, a study by Mavenir reveals that 95 per cent of MNOs understand the importance of virtualisation and have it on their open RAN roadmaps.
A cloud-native open RAN solution enables automation by taking over infrastructure management and operations, handling the management of computing, storage and network resources. Cloudification of RAN essentially means the virtualisation of RAN services in containers and micro services to ensure quick decision-making at the edge of where the RAN equipment is set up. Each micro service can be deployed, upgraded, scaled and restarted independently of other micro services in the RAN application, thus allowing frequent updates to live applications without impacting service level agreements. By enabling automation, the integration of cloud in the RAN architecture offers numerous benefits such as a reduction in administrative overhead costs, greater resource utilisation, scalability and efficient power consumption. Disaggregating RAN software and hardware in the cloud opens up the possibility of independent innovation in hardware and software.
Cloud RAN will soon adopt leading practices and become a foundation for openness and innovation in the 5G era. The involvement of big public cloud providers, or hyperscalers, such as Amazon, Google and Microsoft, will be a significant driver of the open RAN initiative.
Data analytics is deployed as rApps in the non-RT RIC and uses big data to provide an overview of the network conditions. Analytics provide a visual representation of patterns or abnormalities in the network, thus enabling MNOs to comprehend and draw inferences on fixing and improving network performance for a better user experience. It facilitates the review of AI data and the generation of reports on ML performance in network improvement. To optimally leverage data analytics, big data and data mining in the open RAN ecosystem, better openness and application programming interfaces between vendors and MNOs will be required.
Despite certain challenges such as high integration complexity due to multi-vendor environments, security concerns, and integration issues for brownfield operators, open RAN-based solutions are steadily gaining momentum. As 5G and IoT use cases continue to mature, RIC and automation will become increasingly essential in the open RAN environment. The integration of new-age technologies in the RAN framework will enable MNOs to expand their networks into new areas and fulfill the promise of bringing 5G within the reach of underserved markets. The open standards promoted by the O-RAN Alliance will further help leverage technologies such as AI/ML and real-time analytics to develop open interfaces and faster deployment of open RAN. The trend toward these technologies is set to create new dynamics and opportunities in the open RAN ecosystem.