Comparison of average global exposure of population induced by a macro 3G network in different geographical areas in France and Serbia

Huang, Yuanyuan; Varsier, Nadège; Niksic, Stevan; Kočan, Enis; Pejanović-Djurišić, Milica; Popović, Milica; Koprivica, Mladen; Nešković, Aleksandar N.; Milinković, Jelena; Gati, Azeddine; Person, Christian; Wiart, Joe

doi:10.1002/bem.21990

Cited by 16 publications

(11 citation statements)

References 9 publications

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“…In this configuration, results show that the uplink component of exposure is as expected dominating EI and the exposure of indoor users is higher than outdoor users due to the contribution of uplink exposure. In addition the computed EI value for the presented scenario is 3.62 × 10 −8 W/kg at 1800 MHz and 3.03 × 10 −8 W/kg at 2600 MHz which is less than values reported in UMTS and LTE macro cell scenarios in other studies [8] [4]. This can be explained by the reduced distance between SC and UEs and therefore the reduced uplink emitted powers.…”

Section: Resultscontrasting

confidence: 63%

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Statistical model of the human RF exposure in small cell environment

et al. 2018

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Small cells are one of the solutions to face the imperative demand on increasing mobile data traffic. They are low-powered base stations installed close to the users to offer better network services and to deal with increased data traffic. In this paper, the global exposure induced in such networks as a whole from user equipment and base stations has been investigated. As the small cell is close to the user, the propagation channel becomes highly variable and strongly susceptible by environmental factors such as the road traffic. An innovative statistical path loss model is constructed based on measurements on two French commercial LTE small cells, operating at LTE 1800 MHz and 2600 MHz . This statistical path loss model is then used to assess global exposure of the adult proportion of a population in a scenario composed of a street lined with buildings, indoor and outdoor data users.Keywords RF exposure · Small cell · exposure index · drive test measurements · path loss · statistical modeling 1 Introduction Nowadays radio frequency (RF) wireless communication systems are intensively used in different aspects of daily life. Phenomenal progresses in technologies, new applications, wireless devices and networks have led to a strong growth in data traffic over the last decade [1] . To respond to such demand, research efforts have been carried out to improve the efficiency of communication protocols. Current mobile networks are essentially made up of long-range radio equipment (macro cells) deployed to ensure coverage in the different territories. To face 5G ambitious aims (even more data traffic, higher frequency bands with poorer propagation capacities), this long-range layer will be supplemented by medium-range antennas (small cells) to improve coverage and connectivity for all, as the population increasingly uses mobile networks.Small cells (SC) are low-powered base stations (BS). Deploying SCs results in offloading traffic from macro cells, hence, network performance, coverage, and capacity are increased. The coverage of a SC is less than a macro cell: it is ranged typically from a few meters to a few hundreds of meters [2]. Furthermore, SC antenna is often deployed at a low height, e.g., on top of a bus station. As a consequence, SC can be more numerous than macro cells and antennas closer to the users than macro antennas typically installed on a roof top or on top of a mast. By bringing the antennas closer to the users, it is also expecting to reduce the emitted power by user equipements (UE) and to increase the available throughput for users. UEs are therefore able to benefit from SCs, their greater quality and larger throughput than those of classical macro cells. SCs are expected to be deployed massively in order to cover the maximum number of users but such deployment can result to an important raise in public concerns. Despite the intensive use of wireless communication devices and existing international safety limits, there is still public concerns and risk perceptions about human exposure to RF electrom...

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Section: Resultscontrasting

confidence: 63%

“…In this study, path loss model was constructed, based on measurements, according to the following equation [4][11]:…”

Section: Path Loss Modelingmentioning

confidence: 99%

Statistical model of the human RF exposure in small cell environment

et al. 2018

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“…smartphones or tablets) and cellular base stations (BS) or access points [2]. In this respect, advanced computational propagation tools were used in many studies [2,3,4] to characterize the signal's attenuation between a transmitter and a receiver. Such tools can provide accurate path loss results, however they are strongly dependent on detailed building and terrain data, which increases the computational burden.…”

Section: Introductionmentioning

confidence: 99%

Surrogate Modeling of Stochastic Functions-Application to Computational Electromagnetic Dosimetry

Azzi

Huang

Sudret

et al. 2019

Int. J. UncertaintyQuantification

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Metamodeling of complex numerical systems has recently attracted the interest of the mathematical programming community. Despite the progress in high performance computing, simulations remain costly, as a matter of fact, the assessment of the exposure to radio frequency electromagnetic fields is computationally prohibitive since one simulation can require hours. Moreover, in many engineering problems, carrying out deterministic numerical operations without considering uncertainties can lead to unreliable designs. In this paper we focus on the surrogate modeling of a particular type of computational models called stochastic simulators. In contrast to deterministic simulators which yield a unique output for each set of input parameters, stochastic simulators inherently contain some sources of randomness and the output at a given point is a probability density function. Characterizing the stochastic simulators is even more time consuming. This paper represents stochastic simulators as a stochastic process and describes a metamodeling approach based on the Karhunen-Loève spectral decomposition.

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“…Samsung, Apple, Microsoft Mobile and LG are the most popular mobile device manufacturers (Huang et al, 2016). This is presumably due to aggressive promotion and effective marketing strategy.…”

Section: Introductionmentioning

confidence: 99%

Correlation between marketing strategy, product quality and promotion on the mobile devices market in Serbia

Bakator¹,

Petrović²

2016

JEMC

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This paper examines the correlation between promotion as a marketing mix instrument, product quality and marketing strategy on the mobile devices market. The research paper consists of four sections. Each section determines the key factors of the main subject's elements. The research makes analysis of the influence of promotional activities on consumer behavior. It was conducted via survey questions. The questions referred to mobile device brands, user satisfactory rates and other parameters in the Republic of Serbia. The aim was to define the impact of promotional activities on consumer choice when purchasing a mobile device. In addition, the product quality and marketing strategies of top mobile device brands are also taken into consideration. Observational statements are made based on statistical evidence from the completed research surveys.

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Comparison of average global exposure of population induced by a macro 3G network in different geographical areas in France and Serbia

Cited by 16 publications

References 9 publications

Statistical model of the human RF exposure in small cell environment

Statistical model of the human RF exposure in small cell environment

Surrogate Modeling of Stochastic Functions-Application to Computational Electromagnetic Dosimetry

Correlation between marketing strategy, product quality and promotion on the mobile devices market in Serbia

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