How Do 5G Enablers Engage in Digital Transformation?

İlhan Bağören, CEO
Published

5G Enablers Engage

What Opportunities Does 5G Bring to Telecommunications?

The rapid transformation in the telecommunications industry has brought about many potential revenue opportunities for operators across the globe. Many telecommunications companies that seek to seize these opportunities make considerable investments in the wireless spectrum to build 5G networks and adopt new business models.

Nowadays, telecommunications companies are restructuring to act more as enabling platforms offering a wide range of more complex value-added services supported across value chains, rather than acting solely as connectivity providers like they had been doing so far. In close collaboration with partners, operators are delivering services to a broader consumer group and generating shared revenue within an ecosystem-driven model.

Adding modularity and flexibility to the telecom industry, 5G enables communication service providers to respond to changing demands in better and more efficient ways. By providing an exceptional level of interconnectedness, 5G systems offer many significant benefits such as higher data-throughput rates, reduced costs, enhanced system capacity, and energy savings.

Moreover, multiple networks can be created on a shared infrastructure through network slicing, enabling telecommunications companies to provide on-demand networking with a better user experience. Effectively reducing the need to create dedicated networks for specific tasks, 5G delivers connectivity in a highly efficient way, with higher-capacity 5G frequencies enabling the handling of many high-demand applications simultaneously.

With the huge amount of data generated by the Internet of Things (IoT) and 5G applications, operators now have many opportunities, including an improved customer view, thanks to the availability of real-time data and an increased number of interactions. Many telecommunications companies are aiming beyond mobile connectivity and reaching toward edge computing, private networks, value-added solutions, and IoT as trusted partners offering next-generation networks and solutions.

Impacts of 5G on Communication Service Provider Environments

As this new technology enables faster connections and more data reliable streaming, it offers many opportunities for communication service providers. Looking to build dense, low-latency edge networks affordably and securely, communication service providers focus on open source, container-based network infrastructures that meet the 5G requirements associated with latency, reliability, and flexibility. Security along with affordable deployment and maintenance are among the main concerns of CPSs seeking to offer a comprehensive range of innovative solutions to create new revenue streams. As they transition to 5G systems, telecommunications providers gain further flexibility to enable specific capabilities for new use cases and applications and to generate additional income using the same technological infrastructure. The open architecture of 5G allows more extensive use of the network infrastructure. Using containerized and virtualized applications, service providers can now deploy many workloads on a single system.

Through Network Functions Virtualization (NFV), communications service providers can now take better advantage of new open source technologies with reduced time-to-value and increased agility. With the ability to dynamically shift resources depending on workloads and available capacity, telecommunications providers utilize their excess capacity while also offering multi-tenant and Edge clouds. The higher-bandwidth and lower-latency connectivity of 5G networks enable telecom providers to integrate their connectivity services into many diverse industry-specific applications ranging from mobility to healthcare.

5G Enablers for Digital Transformation

5G Digital Transformation

As the 5G system is on its way to revealing its full potential, certain emerging enablers enable different and flexible business and operational models in the telecom industry.

Network Telco Cloud

By adopting virtualization, mobile network operators (MNOs) are expanding their operations to cover a diverse range of services. Integral to the advances in the 5G system, network virtualization through cloud-native models within a service-based framework enables flexibility and adaptability, as well as accelerating time-to-market for new services. It also optimizes the utilization of network resources while helping operators meet new demands.

Today, virtualization is widely adopted within a cloud-native paradigm in the telecom industry. Upon the introduction of Network Functions Virtualization (NFV), a network architecture concept where network appliance hardware is replaced with virtual machines, the commodity hardware as a primary component of the telco cloud enables service providers to run their network on standard servers rather than proprietary servers. In a telco cloud, network functions are realized as cloud-native Virtual Network Functions (VNFs) hosted by cloud infrastructures. In terms of edge computing, these infrastructures are responsive to distribution, decentralization, and localization, enabling many benefits including lower total cost of ownership, accelerated time-to-market, enhanced agility, as well as improved innovation and dynamism.

By covering all the layers of operator networks, the telco cloud facilitates optimized service performance and end-user experience in collaboration with an autonomic framework. As a software-defined and resilient cloud infrastructure, the telco cloud enables telecommunications providers to act in a more agile manner and manage their resources more efficiently.

Edge Computing

Locating resources at the network edge through decentralized and distributed network architectures is essential for today’s telecom companies seeking to seize the opportunities of the future. Through localized processing, end-users are provided with a tailored and context-based service experience with optimum performance.

As a distributed IT architecture in which client data is processed as close to where data is generated as possible, edge computing is an effective way to respond to the many challenges associated with moving the rapidly growing amounts of data today.

With edge computing and telco cloud, mobile network operators and third-party applications can be hosted on dedicated platforms, which in turn enables applications to be run closer to the customer with many benefits. So, it is all about location. Edge computing takes a part of storage and computes resources closer to the data source. Thus, processing takes place right where the data are generated. Ultra-low latency increased reliability, and new partnership opportunities are just a few examples of the benefits enabled by edge computing.

Open Radio Access Network

5G Access Network

The growing need to meet 5G’s throughput, latency, and reliability requirements result in mobile network operators’ demands for disaggregation on network platforms through open interfaces and the promotion of multi-vendor interoperability. Conventionally realized by single-vendor solutions, a radio access network imposes limitations on network construction, particularly with the diversification of deployment scenarios and frequency bands. Complimentary for multi-access edge computing, disaggregated radio access networks enable flexibility, efficiency, agility, and scalability when combined with virtualization.

Built entirely on cloud-native principles, open radio network access separates integrated radio network access systems into modular parts, enabling many benefits for telecommunications providers to effectively overcome market challenges by making a diverse range of suppliers available. Interoperable interfaces and multi-vendor radio access networks allow the utilization of the innovative solutions of different vendors, increasing the competitiveness in the vendor ecosystem. This results in increased cost-effectiveness in the construction of networks and accelerates innovation.

Autonomic Management and Control

To reap the benefits of virtualization, cloud, and edge computing to the greatest extent possible, telecommunication providers are increasingly adopting an autonomic management and control framework that encompasses both autonomous and automatic behaviors. This way, the complexity-related challenges resulting from 5G can be addressed efficiently to support service and application diversification.

As a significant enabler for innovative business models, an autonomic management framework provides benefits for both the operators and their customers in terms of customization. The telco cloud supports customer service requirements by a network slice where the required resources are allocated. The network and user equipment cooperate within the autonomic management and control framework, optimizing system performance. Automated network slicing procedures facilitate isolation, enabling improvements in security and privacy, aligned with the self-Configuration, Healing, Optimization, and Protection (CHOP) characteristics of an end-to-end autonomic management and control framework. Such characteristics enable a transition to more agile, programmable, and autonomic capabilities in virtually real-time. Ensuring that the layered self-CHOP framework is clearly defined with standardized interfaces is essential for optimal performance and less complex integration.

Artificial Intelligence (AI) and Machine Learning (ML)

Artificial Intelligence (AI) and Machine Learning (ML) offer effective methods to meet the requirements of a distributed 5G system. As a virtualized and decentralized 5G system has certain requirements associated with connectivity, capacity, coverage, and services that need to be addressed flexibly, the utilization of AI and ML enables optimized solutions. Adopting AI and ML approaches is essential to have a better understanding of the users and environment to build better and more robust networks that can efficiently optimize and update themselves as required.

AI- and ML-based methods contribute to increased quality, reduced CAPEX, and enhanced performance, as well as unleashing the considerable potential to generate additional income from diverse streams. Aiding mobile network operators in intelligent and real-time, data-driven decision-making for various scenarios with a high level of collaboration among network infrastructures, AI enables them to better manage their resources and traffic.

Considered the most powerful learning approach and capable of operating with both structured and unstructured data, Deep Learning (DL), an augmentation of machine learning enabled through multilayer neural network algorithms, helps in handling many complex use cases effectively. As these methods are capable of working efficiently with uncertainty, enhanced analysis accuracy, as well as improved management, control, and maintenance can be achieved through these methods.

The processing of the massive amounts of data resulting from the simultaneous connections to multiple IoT devices requires the utilization of ML and AI. By integrating them, operators can achieve a high level of automation at the network edge, improved dynamic change identification and user distribution forecasting, efficient capacity expansion, and dynamic network slicing.

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