5G network demands massive infrastructure deployment to meet its requirements. The most cost-effective deployment solution is now a challenge. This paper identifies a cost implementation strategy for 5G by reformulating existing cost models. It analyses three geo-type scenarios and calculates the total cost of ownership (TCO) after estimating the Capex and Opex. The calculations are narrowed to specific cities for clearer understanding instead of the usual generic estimates. An end-to-end 5G network resource analysis is performed. Our result shows that by the end of first year Capex constitutes over 90% of TCO for urban scenarios. Also uniform capacity deployment across geo-types impose severe investment challenges.

The adoption of private 5G networks or Non-Public Networks (NPN) by industry verticals is igniting a digital transformation across various sectors and also leading to industry 4.0. This impetus comes from the integration of private wireless networks with 5G capabilities. Currently, a range of innovative applications and use cases are emerging and resulting in improved enterprise performance and solutions. The potential to boost revenue, stimulate cost reduction, and accelerate Return Of Investment (ROI) makes 5G NPN adoption attractive to industry verticals, network operators and other third-party stakeholders. However, a significant infrastructure upgrade is required, which demands understanding of the complexities of 5G NPN deployment scenarios and their economic implications. This paper addresses these needs by conducting a detailed techno-economic analysis on 5G NPN deployment. The study formulates a technoeconomic model that focuses on; (i) Cost savings in support of ROI achieved by enabling Network Function Virtualization (NFV) technology and Neutral Host (NH) concept; (ii) The trade-off study between enterprise goals (cost vs deployment technologies) with a multi-objective sensitive analysis; And (iii) the trends of 5G NPN adoption worldwide. Analytical results confirm savings of up to 53% in Total Cost of Ownership (TCO) reflecting a significant reduction in Capital and Operation Expenditures (Capex and Opex). Simulation analysis identifies a ranking order of deployment parameters, which prioritise the use of Cost saving strategies and Deployment type. And finally, it offers a prediction of a starting annual average worldwide adoption rate of 82.2% with an expected height by 2026.

In this paper, we reported machine-learning based network dynamic abstraction over a field-trial testbed. The implemented network-scale NCMDB allows the ML-based quality-of-transmission predictor abstract dynamic link parameters for further network planning.

Intent driven networking holds the promise of simplifying network operations by allowing operators to use declarative, instead of imperative, interfaces. Adoption of this technology for 5G and beyond networks is however still in its infancy, where the required architectures, platforms, interfaces and algorithms are still being discussed. In this work, we present the design and implementation of a novel intent based platform for private 5G networks powered by a Natural Language Processing (NLP) interface. We demonstrate how our platform simplifies network operations in three relevant private network use cases, including: i) an intent based slice provisioning use case, ii) an intent based positioning use case, and iii) an intent based service deployment use case. Finally, all use cases are benchmarked in terms of intent provisioning time.

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