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Work has now begun on the sixth generation of cellular technologies (‘6G‘) and cost-efficient global broadband coverage is already becoming a key pillar. Indeed, we are still far from providing universal and affordable broadband connectivity, despite this being a key part of the Sustainable Development Goals (Target 9.c). Currently, both Mobile Net...
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... there is a time dimension to the assessment study period, all costs are discounted using a 5% discount rate to produce the NPV to the current initial period, which is also informed by IMF consumer price forecasts [84]. The network architecture illustrated in Figure 3 is used to upgrade legacy cellular sites to either of the chosen technologies using the unit cost information reported in Table 2, guided by costs from [89], [102]. ...
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... there is a time dimension to the assessment study period, all costs are discounted using a 5% discount rate to produce the NPV to the current initial period, which is also informed by IMF consumer price forecasts [84]. The network architecture illustrated in Figure 3 is used to upgrade legacy cellular sites to either of the chosen technologies using the unit cost information reported in Table 2, guided by costs from [89], [102]. ...
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... On the road towards 6G technology, a comprehensive survey of the four aspects of 6G was considered in recent advances and future trends (You, 2020). Further, IEEE 802.1ax was envisioned to play a major role in the future of multi-tier networks when deployed simultaneously to serve as competitors and complements (Oughton & Jha, 2021). Envisioning 6G as an upcoming technology and still in its early developmental stage, a speculative study was carried out looking at the possible enabling technologies and their innovative elements with the explanation of features beyond 5G (Tariq et al, 2020). ...
Studies have shown that one of the major design principles of 6G technology is to achieve seamless heterogeneous network integration of space, air, ground, and sea. This study argues that the roles of satellites and unmanned aerial vehicles (UAV) cannot be underestimated in achieving such seamless connectivity within the 6G network. While few studies have focused on power control management centered around 5G technology, using a binary exponential algorithm, this approach was not sufficient to guarantee a step-by-step power control adjustment in UAV connection establishment. Hence, a modified power control factor that offers better step-by-step power control, along with a power regeneration algorithm, has been proposed for 6G technology. The regeneration algorithm developed is intended to regenerate one-fifth of the used UAV operation power for every 25 minutes of UAV operation. As such, numerical computations show an adaptable model to extend UAV power if needed, and this would greatly benefit the integration of upcoming 6G technology. The study further highlights some socioeconomic implications of 6G technology and UAV power management that policymakers need to pay attention to. Introduction As digitalization continues to permeate every facet of life, the digitization of socioeconomic activities and data usage has witnessed a significant increase. To accommodate such an increase, the capability and resilience of the underlying communication networks continue to evolve, with the latest being the conceptualization of 6G (6th generation) (Gawas, 2015; Liu et al, 2020). From 1G to 5G, generations of communication networks have enabled the metamorphosis of industrial revolutions and the prevailing digital economy with varying degrees of innovations, as illustrated in Table 1.
... Via stochastic geometry, spectral efficiency values can be estimated producing a distribution of capacity among different UEs at varying distances from a gNodeB (Lim, 2020;Jang, 2022). The NR link budget estimation considers a standard deviation of 6 dB for a rural scenario and different propagation models for rural areas (Lim, 2020;Oughton and Jha, 2021), in line with the literature (Oughton, 2020a,b). The analysis also considers interference from nearby base stations. ...
... Let the expected average user traffic be given as δ t GB/user/month, such that, t ǫ T. Then, the data consumed per day per user, δ t,day MB/day (Oughton and Frias, 2018;Oughton and Jha, 2021). The minimum data speed required per user ζ in Mbps, during the busiest hour of the day (B HF ) using the conversion value of 1 Byte (B) with 8 bits (b), and 1 h with 3,600 s (Oughton et al., 2022b), is calculated as: ...
... Table 4 provides a summary of the simulation parameters and the inputs for different models. The data for the study are obtained from various sources from the literature (Oughton and Frias, 2018;Grijpink et al., 2020;Ofcom, 2020;Oughton and Jha, 2021;5G-New-Thinking, 2022;ITU, 2022;Lappalainen and Rosenberg, 2022). Typically for rural areas, the operating frequencies are in the range of 700 MHz and 3,800 MHz (Partners, 2019). ...
How cost-efficient are potential infrastructure sharing business models for the 5G era (and beyond)? This significant question needs to be addressed if we are to deliver universal affordable broadband in line with Target 9.1 of the UN Sustainable Development Goals. Although almost two-thirds of the global population is now connected, many users still lack access to high-speed and reliable broadband connectivity. Indeed, some of the largest connectivity issues are associated with those living in areas of low economic viability. Consequently, this assessment evaluates the cost implications of different infrastructure sharing business models using a techno-economic assessment framework. The results indicate that a rural 5G neutral host network (NHN) strategy helps to reduce total cost between 10 and 50% compared with other sharing strategies. We also find that, compared to a baseline strategy with No Sharing , the net present value of rural 5G sharing strategies can earn between 30 and 90% more profit. The network upgrades to 5G using various sharing strategies are most sensitive to changes in the average revenue per user, the adoption rate, and the amount of existing site infrastructure. For example, the results from this study show that a 20% variation in demand revenue is estimated to increase the net present value of the sharing strategies by 2–5 times compared to the No Sharing strategy. Similarly, a 10% increase in existing infrastructure lowers the net present value by 8–30%. The infrastructure sharing strategies outlined in this study have the potential to enhance network viability while bridging the digital divide in remote and rural locations.
... The approach proposed in [4] uses a more data-driven demand model to perform a techno-economic analysis of how 5G policies may affect universal broadband. Authors leverage population data, night-time luminosity, and site deployment data to calculate a few model inputs such as average number of smartphone users, average revenue per user, and cellular site coverage. ...
As research in wireless communications shifts towards developing the next generation of mobile networks, the demand for spectrum — specifically, the demand for mobile services — continues to grow. Many 6G verticals are envisioned to have much higher data and capacity requirements, which, in turn, will increase the need for more spectrum. While current demand within a mobile network might be known to its respective operator, it is not easily observable by spectrum regulators. Understanding current demand and identifying potential factors that drive demand can greatly assist regulators in ensuring that spectrum is managed and released efficiently to best support emerging technologies and use cases.
In this paper, we leverage a large variety of input features derived from publicly available geospatial datasets in conjunction with a gradient boosting tree-based machine learning model to estimate current demand for mobile services at a local level. The proposed model is able to capture over 60% of the variance in the data for two different test scenarios, effectively outperforming three different baseline algorithms. We also employ a gain-based feature importance algorithm to identify potential key drivers of spectrum demand, which contrast the simple intuition that demand is driven only by population or economic activity. Finally, we build a more sparse and interpretable model to help regulators make more informed spectrum planning decisions.
... To name a few, the 6G networks are ideated to deliver cost-efficiency, spectrumefficiency, energy-efficiency, and security [6]- [8] in the context of machine learning (ML) or artificial intelligence (AI) empowered networks [9], [10]. 5G is supportive to 6G and is conceived to continue supporting and augmenting the performance of the use cases defined by 3GPP, ranging from enhanced mobile broadband (eMBB) to ultra-reliable low latency communication (URLLC) services and massive machine type communications (mMTC) [11], [12]. These use cases have numerous applications such as vehicle to all (V2X), augmented reality (AR), virtual reality (VR) and mission-critical communication which have stringent requirements for enhanced user experience [13]- [15]. ...
... NetDataDrilling(D) 6 D(t e ) = h 7 for all ← γ min to γ max do 8 [L] ← DBSCAN(D(te, l e ), , µ) 9for all n e ∈ L 10 p ← q : n e = L(q) do11 if n e = D(n e ) then 12X aux (p) ← X aux (p) + s e 13 Y aux (p) ← Y aux (p) ...
p> We propose a novel density-based learning technique assisted by real data to determine the appropriate Epsilon and to locate the HTC. We have also studied the correlation of anomalous BSs (ABs) in the data in the context of network planning. The algorithm, density-based network clustering (DNC), determines the ABs, identifies the HTC and the appropriate value of Epsilon by satisfying the MNOs’ requirements on the highest traffic density MB/km2 and the target deployment area in km2 . We use the k nearest neighbors (k-NN) as a benchmark to compare the appropriate value of Epsilon and other performance parameters. </p
... To name a few, the 6G networks are ideated to deliver cost-efficiency, spectrumefficiency, energy-efficiency, and security [6]- [8] in the context of machine learning (ML) or artificial intelligence (AI) empowered networks [9], [10]. 5G is supportive to 6G and is conceived to continue supporting and augmenting the performance of the use cases defined by 3GPP, ranging from enhanced mobile broadband (eMBB) to ultra-reliable low latency communication (URLLC) services and massive machine type communications (mMTC) [11], [12]. These use cases have numerous applications such as vehicle to all (V2X), augmented reality (AR), virtual reality (VR) and mission-critical communication which have stringent requirements for enhanced user experience [13]- [15]. ...
... NetDataDrilling(D) 6 D(t e ) = h 7 for all ← γ min to γ max do 8 [L] ← DBSCAN(D(te, l e ), , µ) 9for all n e ∈ L 10 p ← q : n e = L(q) do11 if n e = D(n e ) then 12X aux (p) ← X aux (p) + s e 13 Y aux (p) ← Y aux (p) ...
p> We propose a novel density-based learning technique assisted by real data to determine the appropriate Epsilon and to locate the HTC. We have also studied the correlation of anomalous BSs (ABs) in the data in the context of network planning. The algorithm, density-based network clustering (DNC), determines the ABs, identifies the HTC and the appropriate value of Epsilon by satisfying the MNOs’ requirements on the highest traffic density MB/km2 and the target deployment area in km2 . We use the k nearest neighbors (k-NN) as a benchmark to compare the appropriate value of Epsilon and other performance parameters. </p
... Importantly, wireless mobile broadband can generally have a relatively low cost compared to other broadband communications technologies (e.g. fixed broadband networks) [4]- [6]. However, the economic viability of 5G can be challenging in low demand areas, mainly to satisfy strict high capacity, low latency performance requirements [7]- [9]. ...
... More often, it is the rural and remote areas that experience poor broadband services, if coverage is even offered at all. Thus, building wireless broadband infrastructure is a pressing economic development issue [4], [41]. However, this needs to be supported by evidence exploring cost-efficient ways to invest the limited financial capital available, ensuring the right technologies and business models are selected to maximize societal benefits [42], [43]. ...
... Table 2 provides a summary of the simulation parameters and the inputs for different models. The data for the study are obtained from different sources from the literature [4], [39], [72], [74], [132], [137], [138]. In this evaluation, for the existing technology with a takeup rate (x), 50% of P , consider that 30% of those users would upgrade to 5G services, and an additional 20% of P would join the network. ...
p>How cost-efficient are potential infrastructure sharing business models for the 5G/6G era? How should telecommunications regulators formulate a national policy to improve mobile broadband connectivity? These are significant questions that need to be addressed if we are to deliver universal, affordable broadband and achieve Target 9c of the UN Sustainable Development Goals.</p
... This analysis is useful when it is difficult to quantify the benefits and the results of the analysis are not shown as economic benefits. In particular, the discounting process is applied not to the benefit side but to the cost side when the NPV is calculated [30,31]. The comparison between alternatives can be performed using a fixed-cost approach or a fixed-effect approach. ...
The telecommunications sector has experienced enormous advances with technological evolution, and various alternatives for technology development toward 5G technologies have been proposed. To achieve effective research and development (R&D) management, these alternatives should be evaluated. Although cost–benefit analysis, which can help facilitate a technology with the most benefits and the least costs, is generally applied, technology related to public goods should consider both market and non-market perspectives. Since many telecommunications technologies have social impacts as well as market profitability, e.g., 5G, the economic feasibility analysis of such technologies needs to apply market and non-market approaches. Therefore, this paper presents an R&D impact analysis based on usage scenarios that reflect the characteristics of a telecommunications technology. Accordingly, we investigate how the target technology will be employed in a product or service, what costs and benefits the technology will produce, and what methods can be used to measure the costs and benefits. First, the scenarios are constructed to identify different types of benefits while avoiding the overlaps between them. Detailed guidelines are developed to link the most appropriate methods among various economic-feasibility analyses to assess costs and benefits for each usage scenario. Then, the proposed framework is applied to the case of 5G low-latency technology used in vehicle-to-everything (V2X) and validated. The case study findings indicate that the framework is useful in converting direct and indirect benefits of telecommunications technology into a single economic value and is thus expected to be employed in technology evaluation.
... Recent research has demonstrated the potential of dataanalytics for spectrum insights. In [12], the authors combine mathematical models with diverse data sets to inform spectrum policy decisions, especially regarding national spectrum pricing policies. Further, the authors in [13] use big data analytics and sensor data to derive insights on how to manage the RAN for cognitive systems. ...
As the demand for wireless services continues to grow, the need for efficient and effective management of the radio frequency (RF) spectrum becomes increasingly important. A spectrum management approach based on data analysis and interpretation i.e. data-driven, offers a solution as it provides valuable insights into spectrum usage patterns, demand, and the potential for harmful interference in shared spectrum scenarios. This paper focuses on the opportunities and challenges of incorporating diverse data sources into the management of spectrum, with a specific emphasis on spectrum sharing, particularly within database-assisted spectrum sharing systems. The benefits of adopting a data-driven approach to these systems are demonstrated through simulation of specific case studies. These studies indicate the potential for achieving up to a 60% greater density of spectrum use compared to conventional approaches, while also effectively managing harmful interference.
... Importantly, wireless mobile broadband can generally have a relatively low cost compared to other broadband communications technologies (e.g. fixed broadband networks) [6]- [8]. However, the economic viability of 5G can be challenging in low demand areas, mainly to satisfy strict high capacity, low latency performance requirements [9]- [12]. ...
... More often, it is the rural and remote areas that experience poor broadband services, if coverage is even offered at all. Thus, building wireless broadband infrastructure is a pressing economic development issue [6], [38]. However, this needs to be supported by evidence exploring cost-efficient ways to invest the limited financial capital available, ensuring the right technologies and business models are selected to maximize societal benefits [39], [40]. ...
p>How cost-efficient are potential infrastructure sharing business models for the 5G/6G era? How should telecommunications regulators formulate a national policy to improve mobile broadband connectivity? These are significant questions that need to be addressed if we are to deliver universal, affordable broadband and achieve Target 9c of the UN Sustainable Development Goals.</p
... Importantly, wireless mobile broadband can generally have a relatively low cost compared to other broadband communications technologies (e.g. fixed broadband networks) [6]- [8]. However, the economic viability of 5G can be challenging in low demand areas, mainly to satisfy strict high capacity, low latency performance requirements [9]- [12]. ...
... More often, it is the rural and remote areas that experience poor broadband services, if coverage is even offered at all. Thus, building wireless broadband infrastructure is a pressing economic development issue [6], [38]. However, this needs to be supported by evidence exploring cost-efficient ways to invest the limited financial capital available, ensuring the right technologies and business models are selected to maximize societal benefits [39], [40]. ...
How cost-efficient are potential infrastructure sharing business models for the 5G/6G era? How should telecommunication regulators formulate a national policy to improve mobile broadband connectivity? These are significant questions that need to be addressed if we are to deliver universal affordable broadband and achieve Target 9c of the UN Sustainable Development Goals. For example, over one-third of the global population has never used the Internet, with many of these users in areas of low economic viability. Consequently, this assessment evaluates the cost implications of different infrastructure
sharing business models. Over a decade, the results show that a rural 5G neutral host network (NHN) strategy helps to reduce the total cost by 10-50% over “No Sharing”, “Passive Sharing”, or “Active Sharing”
approaches. We also find that compared to a baseline strategy with “No Sharing”, the net present value of rural 5G sharing strategies can earn between 30-90% more profit. The network upgrades to 5G using
various sharing strategies are most sensitive to changes in the average revenue per user, the adoption rate, and the amount of existing site infrastructure. For example, a 20% variation in demand revenue is estimated to increase the net present value of the sharing strategies by 2-5 times compared to the net present value of the “No Sharing” strategy. Similarly, a 10% increase in existing infrastructure lowers the net present value by 8-30%.
