Assessing the capacity, coverage and cost of 5G infrastructure strategies: Analysis of the Netherlands

Oughton, Edward J.; Frías, Zoraida; Gaast, Sietse van der; Berg, Rudolf van der

doi:10.1016/j.tele.2019.01.003

Cited by 109 publications

(56 citation statements)

References 25 publications

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“…Moreover, the years of experience of marketing staff and other staff from network and product development as well as rich customer data across all network elements within the enterprise contributed to it. While data traffic of mobile service providers will continue to grow as a result of demand from customers and an increasing number of connected devices and terminals with data-intensive applications [56], mobile service providers must be equipped with robust pricing tools and techniques not only to avoid price wars amongst competitors but also to be profitable and manage CAPEX investment.…”

Section: Resultsmentioning

confidence: 99%

A Fuzzy Logic Expert System for Pricing Digital Services: The Case of Price Adjustment for a Mobile Service Provider

Dairo¹,

Szűcs²

2020

IJFIS

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As connected smart devices and terminals continue to grow along with digital content, data traffic of mobile service providers is also growing, and the price war in mobile markets is driving traffic growth without a commensurable increase in revenue. As a result, network capital expenditure (CAPEX) investment, quality of experience, and customer experience are under enormous pressure. In a competitive mobile market, strategic pricing may play an essential role in managing this pressure only if appropriate tools are available for the service providers. In this paper, a fuzzy knowledge-based expert pricing system was developed with a focus on solving network traffic, price war, and business revenue challenges in a competitive mobile market. Its core lay in its ability to recommend digital-and data services-related price points within a competitive and price war mobile environment. The proposed pricing system was experimentally evaluated through a pilot conducted on a few segments of a mobile service provider's customer base in an emerging market and later scaled up to a broader base. Upon implementation, data services revenue increased, and overall gross margin increased with a reduction in data traffic, resulting in better throughput and network quality and, consequently, better customer experience with improved net promoter score.

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Section: Resultsmentioning

confidence: 99%

A Fuzzy Logic Expert System for Pricing Digital Services: The Case of Price Adjustment for a Mobile Service Provider

Dairo¹,

Szűcs²

2020

IJFIS

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“…cdcam has already been used to test the capacity, coverage and cost of 5G infrastructure in Britain and the Netherlands (Oughton et al, 2019a).…”

Section: Applicationsmentioning

confidence: 99%

cdcam: Cambridge Digital Communications Assessment Model

Oughton¹,

Russell²

2020

JOSS

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Digital connectivity is an essential infrastructure service, as more and more people and machines are connected to the internet. Mobile internet access is one of the cheapest ways to connect wirelessly, and new technologies (particularly 5G) can offer access speeds which can rival fixed broadband connections. Successive generations of mobile telecommunication technologies (3G-5G) have increased data transmission rates and reduced latency. However, user-generated data traffic has been growing exponentially over the past decade which is concerning for both mobile network operators and policy decision-makers, with future growth forecasts indicating this trend is likely to continue (Oughton et al., 2018). The Cambridge Digital Communications Assessment Model (cdcam), is a decision-support model which quantifies the performance of digital infrastructure strategies for mobile digital communications. cdcam models the performance of 4G and 5G technologies as they roll-out over space and time, given a set of exogenous population and data growth scenarios, and potential deployment strategies.

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“…Com a expansão do LTE (Long Term Evolution) e os avanços no sistema de quinta geração (5G), a demanda por comunicação sem fio tem sido a força motriz por trás do progresso da tecnologia sem fio. Sob estas circunstâncias, o aumento no fluxo de dados previsto para os próximos anos [Khan et al 2018] [Oughton et al 2019] torna as redes de acesso por rádio descentralizadas (D-RAN) muito caras para as operadoras de serviços móveis [Khorsandi and Raffaelli 2018] e ineficientes quando se tem demanda de tráfego dinâmica. Esse comportamento do tráfego, denominado Efeito de Maré, gera o deslocamento do fluxo de comunicação em diferentes topologias de rede, especialmente em regiões que possuem migração diária da população [Yan et al 2018] [Zhong et al 2016].…”

Section: Introductionunclassified

Provisionamento de Recursos de Hardware em Redes Híbridas de Acesso por Rádio com Base no Efeito de Maré

Falcão¹,

Vieira²,

Seruffo³

et al. 2019

Anais Do Workshop Em Desempenho De Sistemas Computacionais E De Comunicação (WPerformance)

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A arquitetura C-RAN (Centralized Radio Access Network) é uma proposta para atender à alta demanda das redes de quinta geração (5G). Devido o tráfego de comunicação possuir um comportamento dinâmico em decorrência do “Efeito de Maré” (fenômeno responsável pela movimentação do fluxo de rede), a arquitetura atual, o D-RAN (Decentralized Radio Access Network) não garante o fornecimento eficiente de recursos. Este trabalho apresenta uma heurı́stica para o dimensionamento de recursos de hardware considerando o Número de Usuários Atendidos e Vazão Agregada. A abordagem atendeu a variabilidade do tráfego, maximizando a eficiência da BBU (BaseBand Unit) e quantificando as SC’s (Small Cells) necessárias para cobrir a demanda da rede.

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Assessing the capacity, coverage and cost of 5G infrastructure strategies: Analysis of the Netherlands

Cited by 109 publications

References 25 publications

A Fuzzy Logic Expert System for Pricing Digital Services: The Case of Price Adjustment for a Mobile Service Provider

A Fuzzy Logic Expert System for Pricing Digital Services: The Case of Price Adjustment for a Mobile Service Provider

cdcam: Cambridge Digital Communications Assessment Model

Provisionamento de Recursos de Hardware em Redes Híbridas de Acesso por Rádio com Base no Efeito de Maré

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