Coverage prediction and optimization algorithms for indoor environments

David, Paul A.; Joseph, Wout; Vanhecke, Kris; Tanghe, Emmeric; Martens, Luc

doi:10.1186/1687-1499-2012-123

Cited by 74 publications

(164 citation statements)

References 22 publications

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“…The padding or minimum distance between absorbing boundaries (UPML) and the bounding box around the human body model and the antenna was set to half a wavelength. These simulations are validated by measurements in an office environment (Plets et al 2012), and good agreement is obtained. Fig.…”

Section: Application: Simulation Of Field Strength With Realistic Dutmentioning

confidence: 76%

Determination of the duty cycle of WLAN for realistic radio frequency electromagnetic field exposure assessment

Joseph

Pareit

Vermeeren

et al. 2013

Progress in Biophysics and Molecular Biology

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Wireless Local Area Networks (WLANs) are commonly deployed in various environments. The WLAN data packets are not transmitted continuously but often worst-case exposure of WLAN is assessed, assuming 100 % activity and leading to huge overestimations. Actual duty cycles of WLAN are thus of importance for time-averaging of exposure when checking compliance with international guidelines on limiting adverse health effects. In this paper, duty cycles of WLAN using Wi-Fi technology are determined for exposure assessment on large scale at 179 locations for different environments and activities (file transfer, video streaming, audio, surfing on the internet, etc.). The median duty cycle equals 1.4 % and the 95th percentile is 10.4 % (standard deviation SD = 6.4%). Largest duty cycles are observed in urban and industrial environments. For actual applications, the theoretical upper limit for the WLAN duty cycle is 69.8% and 94.7% for maximum and minimum physical data rate, respectively. For lower data rates, higher duty cycles will occur. Although counterintuitive at first sight, poor WLAN connections result in higher possible exposures. File transfer at maximum data rate results in median duty cycles of 47.6% (SD = 16%), while it results in median values of 91.5% (SD = 18%) at minimum data rate. Surfing and audio streaming are less intensively using the wireless medium and therefore have median duty cycles lower than 3.2% (SD = 0.5-7.5%). For a specific example, overestimations up to a factor 8 for electric fields occur, when considering 100 % activity compared to realistic duty cycles. We have included the document "Response to reviewers" at the end of the revised manuscript. This is a detailed summary of the changes made in preparing the revised manuscript. We have put an asterisk before our answers and changes. This document contains the detailed summary of the changes made in preparing the revised manuscript. We hope the changes we made according to your suggestions (explanation unit of time, multiple clients, far vs. near exposure vs. duty cycle, etc.) will satisfy you. We have put an asterisk before our answers and changes. We thank you for spending your time reviewing our paper. *We have put an asterisk (*) before every response. Reviewers' comments:Reviewer #1: This is a well written and interesting paper, reporting methods to calculate the duty cycle for WLAN transmitters under different real time scenarios. The data reported will be very useful in realistic assessment of the exposure of people to WLAN sources. *Thank you for appreciating our paper.Here are some comments:1-The main comment is related to the unit of time (relevant time frame) for duty cycle calculations. In Khalid et al 2011, the unit of time was considered as the duration of a typical lesson in a school ( about 30min). However the authors here considered the duration of a file transfer for example ( or any other activity), as the unit of time. This needs to be elaborated further as whether the time to transfer a file (which is very sma...

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Section: Application: Simulation Of Field Strength With Realistic Dutmentioning

confidence: 76%

Determination of the duty cycle of WLAN for realistic radio frequency electromagnetic field exposure assessment

Joseph

Pareit

Vermeeren

et al. 2013

Progress in Biophysics and Molecular Biology

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“…the path along which the signal encounters the lowest obstruction. The model, constructed for the 2.4-to 2.6-GHz band, has shown excellent correspondence between predictions and validation measurements as shown in (15). The tool allows automatic network planning based on a userdefined throughput using a minimal number of access points (APs) (traditional deployment) or a planning for a minimal human exposure (exposure-optimised deployment).…”

Section: Impact On Total Exposure In Wlan Deploymentsmentioning

confidence: 99%

“…The networks are planned according to the WHIPP tool's automatic network planning algorithm described in (15). Figure 2a and b shows the AP locations for the 'traditional' network planning.…”

Section: Application: Impact Of Microwave Oven Leakage On Exposure Inmentioning

confidence: 99%

“…The latter can be predicted by a wireless network planner. Here, the microwave oven exposure values will be implemented into the WiCa Heuristic Indoor Propagation Prediction (WHIPP) tool described in (15). It uses a heuristic planning algorithm, developed and validated for the prediction and optimisation of wireless coverage in indoor environments.…”

Section: Impact On Total Exposure In Wlan Deploymentsmentioning

confidence: 99%

“…Further, a model applicable to assess microwave oven exposure in a large office building is developed. It is then applied to two types of WLAN network deployments: a traditional deployment with few high-power access points and an exposure-optimised deployment with many low-power access points (15,16) . Such an assessment of the impact of a microwave oven exposure on the total network exposure has not yet been performed according to the authors' knowledge.…”

Section: Introductionmentioning

confidence: 99%

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EXPOSURE ASSESSMENT OF MICROWAVE OVENS AND IMPACT ON TOTAL EXPOSURE IN WLANs

David

Verloock

Bossche

et al. 2015

Radiat Prot Dosimetry

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In situ exposure of electric fields of 11 microwave ovens is assessed in an occupational environment and in an office. Measurements as a function of distance without load and with a load of 275 ml of tap water were performed at distances of <1 m. The maximal measured field was 55.2 V m 21 at 5 cm from the oven (without load), which is 2.5 and 1.1 times below the International Commission on Non-Ionizing Radiation Protection reference level for occupational exposure and general public exposure, respectively. For exposure at distances of >1 m, a model of the electric field in a realistic environment is proposed. In an office scenario, switching on a microwave oven increases the median field strength from 91 to 145 mV m 21 (191 %) in a traditional Wireless Local Area Network (WLAN) deployment and from 44 to 92 mV m 21 (1109 %) in an exposure-optimised WLAN deployment.

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An Indoor Path Loss Prediction Model Using Wall Correction Factors for Wireless Local Area Network and 5G Indoor Networks

et al. 2018

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A modified indoor path loss prediction model is presented, namely, effective wall loss model. The modified model is compared to other indoor path loss prediction models using simulation data and real‐time measurements. Different operating frequencies and antenna polarizations are considered to verify the observations. In the simulation part, effective wall loss model shows the best performance among other models as it outperforms 2 times the dual‐slope model, which is the second best performance. Similar observations were recorded from the experimental results. Linear attenuation and one‐slope models have similar behavior, the two models parameters show dependency on operating frequency and antenna polarization.

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Coverage prediction and optimization algorithms for indoor environments

Cited by 74 publications

References 22 publications

Determination of the duty cycle of WLAN for realistic radio frequency electromagnetic field exposure assessment

Determination of the duty cycle of WLAN for realistic radio frequency electromagnetic field exposure assessment

EXPOSURE ASSESSMENT OF MICROWAVE OVENS AND IMPACT ON TOTAL EXPOSURE IN WLANs

An Indoor Path Loss Prediction Model Using Wall Correction Factors for Wireless Local Area Network and 5G Indoor Networks

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