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

Abstract

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...

Temporal 24-hour assessment of radio frequency exposure in schools and homes

“…with a high duty cycle followed by lower duty cycles as observed in [24]. Table 1 shows that for the considered schools and homes (at the location of the temporal assessment), the field values measured over 24 hours satisfy the ICNIRP reference levels.…”

“…The WiFi/WLAN duty cycle in schools has only been investigated in [25] and for various applications in [24]. No attempt to assess the 24 hour variation of the WiFi duty cycle was made.…”

“…The duty-cycles in [24] and [25] are similar: median values varied from 1.2 to 1.9 % (standard deviations from 3.1 to 7.1% or 0.6 dB) in [24] and from 1.0% to 11.7% or 1.1 dB with a mean of 4.79% in [25]. Here, we obtained standard deviations of 1.5 dB, when considering all data (Table 3), which is similar.…”

Downlink electric-field and uplink SAR prediction algorithm in indoor wireless network planner

“…WHIPP simulations have already been validated with measurements in [7]. For WiFi APs, the calculated electric-field strength is multiplied by the square root of the duty cycle (here assumed 2%, based on measured 'Skype voice' duty cycles in [8]). For the prediction of the electric-field strength due to the UMTS macrocell, we use actual received power measurements.…”

“…In order to predict the localized SAR values, an accurate prediction of the emitted power P Tx is required (see equation (1)). For UL WiFi traffic, P Tx will be assumed equal to the product of P max (20 dBm or 0.1 W) and the duty cycle (2% [8]) (no power control). For UL UMTS to femtocell, the mobile phone's emitted power P Tx will be predicted by the WHIPP tool (limited between -57 dBm and 23 dBm [9]).…”