Techno-economic analysis of ultra-dense and DAS deployments in mobile 5G

Bouras, Christos; Kokkinos, Vasileios; Κόλλια, Αναστασία; Papazois, Andreas

doi:10.1109/iswcs.2015.7454337

Cited by 22 publications

(37 citation statements)

References 7 publications

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“…It is possible to combine it with 802.11 and even enhance it. In previous research activity [9], it was indicated that two antennas per floor of a building could sufficiently cover the floor of a block of flats or an under-populated building. But, when it comes to larger places, several sets of antennas need to be added to succeed in covering the whole place.…”

Section: B Distributed Antenna System (Das)mentioning

confidence: 99%

“…These two different cost categories are really deviant and therefore, a specific methodology followed in [9] could help in forming both costs. The annual cost estimation is achieved by considering that the CAPEX as an investment, whose capital was obtained through a loan.…”

Section: Pricing Modelmentioning

confidence: 99%

“…In order to conduct the experiments and conclude to the influence of the cost parameters in the overall model concerning that the operators will be encouraged or discouraged to invest in this technology, it is crucial that a specific test bench with appropriate parameter values are opted. Values for the network components of the Greek Market are available, because of previous research activity [9]. 5G is going to be realized in the future, it is fundamental to make a provision concerning, what the prices will be.…”

Section: E Tcomentioning

confidence: 99%

“…Authors have already presented research concerning the techno-economics of 5G technologies. They have already developed ultra-dense and DAS techno-economic models [9], Sensitivity Analysis (SA) of DAS and small cells [10], [11]. In previous research, they have presented cost models for SDN and NFV [12] and they have also thoroughly analyzed the SDN and NFV concepts in mobile networks alongside with the advancements and challenges they induce [13].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Techno-economic analysis of MIMO & DAS in 5G

Bouras

Kokkalis

Κόλλια

et al. 2018

2018 11th IFIP Wireless and Mobile Networking Conference (WMNC)

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Section: B Distributed Antenna System (Das)mentioning

confidence: 99%

Section: Pricing Modelmentioning

confidence: 99%

Section: E Tcomentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Techno-economic analysis of MIMO & DAS in 5G

Bouras

Kokkalis

Κόλλια

et al. 2018

2018 11th IFIP Wireless and Mobile Networking Conference (WMNC)

Self Cite

View full text Add to dashboard Cite

“…Most of these studies do not directly address the question of how changing the spectrum resources would impact overall costs, but to the extent they enable such calculations they can contribute to estimating the opportunity cost (value) of different spectrum resources. Examples of studies that have estimated the costs of building wireless networks with different spectrum resources include Oughton and Frias (2017), who provide a detailed cost-model for building out 5G small cell infrastructure across the UK; who consider the total cost of ownership of different portfolios of spectrum assets; Johansson et al (2007), who model the costs of supporting heterogeneous wireless networks; and Bouras et al (2015), who model the costs of dense cell deployments. Gomez and Weiss (2013) offer one of the few papers to examine how different technical features may limit spectrum substitutability, thereby reducing the fungibility of different spectrum rights.…”

Section: Estimating the Value Of Commercial Spectrum Licensesmentioning

confidence: 99%

Spectrum Valuation: Implications for Sharing and Secondary Markets

et al. 2018

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TPRC46 Abstract 1How much is electromagnetic spectrum worth? Appropriate metrics and methodologies for valuing spectrum help policymakers, network operators, service providers, and end-users in planning wireless-related investment and in ensuring that spectrum resources are used efficiently. Secondary markets have often served to provide publicly observable, market-based valuation metrics, but in the case of spectrum, these are under-developed and segmented, limiting the availability and comparability of market transactions as indicators of spectrum value. Furthermore, the continued growth in wireless services and networks of all types and further advances in wireless technologies enabling more dynamic and granular spectrum sharing are transforming the supply and demand conditions for RF spectrum.Today, the most common metric for valuing spectrum resources is $/MHz-POP, derived from dividing the value of a spectrum transaction by the total population in the coverage area of the license times the bandwidth (in MHz). Traditionally, spectrum value has been observed in spectrum auctions, M&A transactions involving the transfer of spectrum usage rights, or from infrequent secondary market activity. This was a viable approach when the fungibility of spectrum resources was limited by technical, market, and regulatory factors that constrained the commodification of highly differentiated spectrum resources and limited the potential for dynamically reallocating, substituting and transferring spectrum rights via markets.With increased opportunities for spectrum sharing, the transition to 5G, smaller cell architectures, and the emergence of IoT, new spectrum usage patterns are arising and enabling more granular, multi-dimensional, virtualized spectrum management (in terms of frequency, location, time, etc.). In a world of increasing spectrum sharing, dynamic spectrum access, and commercial applications of higher frequencies for wireless service, $/MHz-POP may be an increasingly noisy indicator of spectrum value.In this paper, we consider how changing technology, markets and policy are enabling the commoditization of spectrum resources and explore what that implies for traditional spectrum value metrics that are used to project auction proceeds and value spectrum transactions.

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Techno‐Economic Analysis for Programmable Networks

Bouras¹,

Κόλλια²

2019

Wiley 5G Ref

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The advent of the fifth generation (5G) of mobile networks will boost technology, as new solutions are needed to meet the growing 5G‐related demands identified both by scientists and telecommunication providers. Programmable logic solutions will be used, as they provide financial, performance, and environmental benefits. The programmable logic nowadays is represented by the combination of the software‐defined networking (SDN) technology with network function virtualization (NFV). This combination not only reduces hardware – as most network components are replaced by network functions or virtual machines (VMs) – but also offers better resource allocation and provides more bandwidth, CPU, etc., to the parts of the network that have become more congested. Solutions, such as SDN, may concentrate fundamental advantages and profits, but they appear to face basic problems, therefore raising key questions concerning their cost and safety. One of these issues contains all the expenses for the acquisition of the technology and the adjustments that need to be incorporated into current infrastructure in order to cover SDN networks as well. This article analyzes a programmable model of SDN combined with NFVs. A sensitivity analysis (SA) is conducted to determine the factors that largely influence the pricing so as to propose ways to significantly reduce several types of costs and propose solutions or research directions to cut down on the expenses of these network factors.

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Techno-economic analysis of ultra-dense and DAS deployments in mobile 5G

Cited by 22 publications

References 7 publications

Techno-economic analysis of MIMO & DAS in 5G

Techno-economic analysis of MIMO & DAS in 5G

Spectrum Valuation: Implications for Sharing and Secondary Markets

Techno‐Economic Analysis for Programmable Networks

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