The rapid worldwide increase in mobile phone use in the last decade has generated considerable interest in possible carcinogenic effects of radio frequency (RF). Because exposure to RF from phones is localized, if a risk exists it is likely to be greatest for tumours in regions with greatest energy absorption. The objective of the current paper was to characterize the spatial distribution of RF energy in the brain, using results of measurements made in two laboratories on 110 phones used in Europe or Japan. Most (97-99% depending on frequency) appears to be absorbed in the brain hemisphere on the side where the phone is used, mainly (50-60%) in the temporal lobe. The average relative SAR is highest in the temporal lobe (6-15%, depending on frequency, of the spatial peak SAR in the most exposed region of the brain) and the cerebellum (2-10%) and decreases very rapidly with increasing depth, particularly at higher frequencies. The SAR distribution appears to be fairly similar across phone models, between older and newer phones and between phones with different antenna types and positions. Analyses of risk by location of tumour are therefore important for the interpretation of results of studies of brain tumours in relation to mobile phone use.

In numerical dosimetry, the recent advances in high performance computing led to a strong reduction of the required computational time to assess the specific absorption rate (SAR) characterizing the human exposure to electromagnetic waves. However, this procedure remains time-consuming and a single simulation can request several hours. As a consequence, the influence of uncertain input parameters on the SAR cannot be analyzed using crude Monte Carlo simulation. The solution presented here to perform such an analysis is surrogate modeling. This paper proposes a novel approach to build such a surrogate model from a design of experiments. Considering a sparse representation of the polynomial chaos expansions using least-angle regression as a selection algorithm to retain the most influential polynomials, this paper proposes to use the selected polynomials as regression functions for the universal Kriging model. The leave-one-out cross validation is used to select the optimal number of polynomials in the deterministic part of the Kriging model. The proposed approach, called LARS-Kriging-PC modeling, is applied to three benchmark examples and then to a full-scale metamodeling problem involving the exposure of a numerical fetus model to a femtocell device. The performances of the LARS-Kriging-PC are compared to an ordinary Kriging model and to a classical sparse polynomial chaos expansion. The LARS-Kriging-PC appears to have better performances than the two other approaches. A significant accuracy improvement is observed compared to the ordinary Kriging or to the sparse polynomial chaos depending on the studied case. This approach seems to be an optimal solution between the two other classical approaches. A global sensitivity analysis is finally performed on the LARS-Kriging-PC model of the fetus exposure problem.

In a case -control study in Japan of brain tumours in relation to mobile phone use, we used a novel approach for estimating the specific absorption rate (SAR) inside the tumour, taking account of spatial relationships between tumour localisation and intracranial radiofrequency distribution. Personal interviews were carried out with 88 patients with glioma, 132 with meningioma, and 102 with pituitary adenoma (322 cases in total), and with 683 individually matched controls. All maximal SAR values were below 0.1 W kg À1 , far lower than the level at which thermal effects may occur, the adjusted odds ratios (ORs) for regular mobile phone users being 1.22 (95% confidence interval (CI): 0.63 -2.37) for glioma and 0.70 (0.42 -1.16) for meningioma. When the maximal SAR value inside the tumour tissue was accounted for in the exposure indices, the overall OR was again not increased and there was no significant trend towards an increasing OR in relation to SAR-derived exposure indices. A non-significant increase in OR among glioma patients in the heavily exposed group may reflect recall bias. British Journal of Cancer (2008) The rapid increase in mobile phone use has raised public concern about their safety (Rothman et

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ObjectivesThe objective of this study was to develop an estimate of a radio frequency (RF) dose as the amount of mobile phone RF energy absorbed at the location of a brain tumour, for use in the Interphone Epidemiological Study.MethodsWe systematically evaluated and quantified all the main parameters thought to influence the amount of specific RF energy absorbed in the brain from mobile telephone use. For this, we identified the likely important determinants of RF specific energy absorption rate during protocol and questionnaire design, we collected information from study subjects, network operators and laboratories involved in specific energy absorption rate measurements and we studied potential modifiers of phone output through the use of software-modified phones. Data collected were analysed to assess the relative importance of the different factors, leading to the development of an algorithm to evaluate the total cumulative specific RF energy (in joules per kilogram), or dose, absorbed at a particular location in the brain. This algorithm was applied to Interphone Study subjects in five countries.ResultsThe main determinants of total cumulative specific RF energy from mobile phones were communication system and frequency band, location in the brain and amount and duration of mobile phone use. Though there was substantial agreement between categorisation of subjects by cumulative specific RF energy and cumulative call time, misclassification was non-negligible, particularly at higher frequency bands. Factors such as adaptive power control (except in Code Division Multiple Access networks), discontinuous transmission and conditions of phone use were found to have a relatively minor influence on total cumulative specific RF energy.ConclusionsWhile amount and duration of use are important determinants of RF dose in the brain, their impact can be substantially modified by communication system, frequency band and location in the brain. It is important to take these into account in analyses of risk of brain tumours from RF exposure from mobile phones.

Abstract-In wireless networks, interferences between transmissions are modelled either in time or frequency domain. In this article, we jointly analyze interferences in the timefrequency domain using a stochastic geometry model assuming the total time-frequency resources to be a two-dimensional plane and transmissions from Internet of Things (IoT) devices timefrequency patterns on this plane. To evaluate the interference, we quantify the overlap between the information packets: provided that the overlap is not too strong, the packets are not necessarily lost due to capture effect. This flexible model can be used for multiple medium access scenarios and is especially adapted to the random time-frequency access schemes used in Low-Power Wide-Area Networks (LPWANs). By characterizing the outage probability and throughput, our approach permits to evaluate the performance of two representative LPWA technologies Sigfox R and LoRaWAN R .

This paper presents a new metric to evaluate electromagnetic exposure induced by wireless cellular networks. This metric takes into account the exposure induced by base station antennas as well as exposure induced by wireless devices to evaluate average global exposure of the population in a specific geographical area. The paper first explains the concept and gives the formulation of the Exposure Index (EI). Then, the EI computation is illustrated through simple phone call scenarios (indoor office, in train) and a complete macro urban data long-term evolution scenario showing how, based on simulations, radio-planning predictions, realistic population statistics, user traffic data, and specific absorption rate calculations can be combined to assess the index. Bioelectromagnetics. 2015;9999:XX-XX.

Although radio frequency (RF) electromagnetic fields emitted by mobile phones have received much attention, relatively little is known about the extremely low frequency (ELF) magnetic fields emitted by phones. This paper summarises ELF magnetic flux density measurements on global system for mobile communications (GSM) mobile phones, conducted as part of the MOBI-KIDS epidemiological study. The main challenge is to identify a small number of generic phone models that can be used to classify the ELF exposure for the different phones reported in the study. Two-dimensional magnetic flux density measurements were performed on 47 GSM mobile phones at a distance of 25 mm. Maximum resultant magnetic flux density values at 217 Hz had a geometric mean of 221 (+198/-104) nT. Taking into account harmonic data, measurements suggest that mobile phones could make a substantial contribution to ELF exposure in the general population. The maximum values and easily available variables were poorly correlated. However, three groups could be defined on the basis of field pattern indicating that manufacturers and shapes of mobile phones may be the important parameters linked to the spatial characteristics of the magnetic field, and the categorization of ELF magnetic field exposure for GSM phones in the MOBI-KIDS study may be achievable on the basis of a small number of representative phones. Such categorization would result in a twofold exposure gradient between high and low exposure based on type of phone used, although there was overlap in the grouping.