Measuring Specific Absorption Rate by using Standard Communications Equipment

2012 ◽  
pp. 81-111 ◽  
Author(s):  
Diana Bri ◽  
Jaime Lloret ◽  
Carlos Turro ◽  
Miguel Garcia
Keyword(s):  
Absorption Rate ◽  
Specific Absorption Rate ◽  
Wireless Local Area Network ◽  
Local Area Network ◽  
Local Area ◽  
The Body ◽  
Area Network ◽  
Specific Absorption ◽  
The People ◽  
Single Person

Specific Absorption Rate (SAR) is used to measure the body tissue exposure to electromagnetic fields. This chapter describes how SAR values can be estimated from a deployed Wireless Local Area Network (WLAN). We carried out this work using the Received Signal Strength (RSS) obtained from the access points. This parameter is easily obtained by an ordinary wireless network scanner. RSS variations are measured for a different number of people in the same room and without people. It will allow us to estimate how much energy is absorbed by a group of people and by a single person on average. Moreover, we have included the weight of the people in order to know the RSS lost by kilogram. These measurements were taken at the Higher Polytechnic School of Gandia, Universitat Politècnica de València, Spain, in two placements: the library and inside an anechoic camera.

scholarly journals Next-generation UWB antennas gadgets for human health care using SAR

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Aysha Maryam Ali ◽  
Mohammed A. Al Ghamdi ◽  
Muhammad Munwar Iqbal ◽  
Shehzad Khalid ◽  
Hamza Aldabbas1 ◽  
...  
Keyword(s):  
Health Care ◽  
Absorption Rate ◽  
Specific Absorption Rate ◽  
Wide Band ◽  
The Body ◽  
Ultra Wide Band ◽  
Body Area Network ◽  
Area Network ◽  
Body Area ◽  
Specific Absorption

AbstractThe body area network is now the most challenging and most popular network for study and research. Communication about the body has undoubtedly taken its place due to a wide variety of applications in industry, health care, and everyday life in wireless network technologies. The body area network requires such smart antennas that can provide the best benefits and reduce interference with the same channel. The discovery of this type of antenna design is at the initiative of this research. In this work, to get a good variety, the emphasis is on examining different techniques. The ultra-wide band is designed, simulated, and manufactured because the ultra-wide band offers better performance compared to narrowband antennas. To analyze the specific absorption rate, we designed a multilayer model of human head and hand in the high-frequency structure simulator. In the final stage, we simulated our antennas designed with the head and hand model to calculate the results of the specific absorption rate. The analysis of the specific absorption rate for the head and hand was calculated by placing the antennas on the designed model.

Link-Level Simulator for Wireless local Area Network

2018 ◽  
Vol 6 (7) ◽  
pp. 314
Author(s):  
Chaithra. H. U ◽  
Vani H.R
Keyword(s):  
Wireless Local Area Network ◽  
Local Area Network ◽  
Local Area Networks ◽  
Local Area ◽  
Long Term Evolution ◽  
Wireless Local Area Networks ◽  
Area Network ◽  
Network Simulator ◽  
Term Evolution

Now a days in Wireless Local Area Networks (WLANs) used in different fields because its well-suited simulator and higher flexibility. The concept of WLAN  with  advanced 5th Generation technologies, related to a Internet-of-Thing (IOT). In this project, representing the Network Simulator (NS-2) used linked-level simulators for Wireless Local Area Networks and still utilized IEEE 802.11g/n/ac with advanced IEEE 802.11ah/af technology. Realization of the whole Wireless Local Area Networking linked-level simulators inspired by the recognized Vienna Long Term Evolution- simulators. As a outcome, this is achieved to link together that simulator to detailed performances of Wireless Local Area Networking with Long Term Evolution, operated in the similar RF bands. From the advanced 5th Generation support cellular networking, such explore is main because different coexistences scenario can arise linking wireless communicating system to the ISM and UHF bands.

PERANCANGAN ANTENA MIKROSTRIPRECTANGULAR

Jurnal Teknik ◽  
2018 ◽  
Vol 7 (1) ◽  
Author(s):  
Heru Abrianto
Keyword(s):  
Dielectric Constant ◽  
Patch Antenna ◽  
Wireless Lan ◽  
Microstrip Antenna ◽  
Wireless Local Area Network ◽  
Local Area Network ◽  
Local Area ◽  
Area Network ◽  
Dual Polarization ◽  
Feeding Technique

Microstrip antenna which designed with dual feeding at 2.4 GHz and 5.8 GHz can meet WLAN (Wireless Local Area Network) application.Antenna fabrication use PCB FR4 double layer with thickness 1.6 mm and dielectric constant value 4.4. The length of patch antenna according to calculation 28.63 mm, but to get needed parameter length of patch should be optimized to 53 mm. After examination, this antenna has VSWR 1.212 at 2.42 GHz and 1.502 at 5.8 GHz, RL -13.94 dB at 2.42 GHz and -20.357 dB at 5.8 GHz, gain of antenna 6.16 dB at 2.42 GHz and 6.91 dB at 5.8 GHz, the radiation pattern is bidirectional. Keywords : microstrip antenna, wireless LAN, dual polarization, single feeding technique

IEEE 802.11 Tutorial

2018 ◽  
Author(s):  
Kiramat
Keyword(s):  
Access Control ◽  
Ieee 802.11 ◽  
Wireless Local Area Network ◽  
Local Area Network ◽  
Local Area ◽  
Physical Layer ◽  
Media Access Control ◽  
Area Network ◽  
Media Access ◽  
Computer Communications

IEEE 802.11 is a set of media access control (MAC) and physical layer (PHY) specifications for implementing wireless local area network (WLAN) computer communications. Maintained by the Institute of Electrical and Electronics Engineers (IEEE) LAN/MAN Standards Committee (IEEE 802). This document highlights the main features of IEEE 802.11n variant such as MIMO, frame aggregation and beamforming along with the problems in this variant and their solutions

scholarly journals Multi-terminal Experimental System Based on Wireless Local Area Network

2020 ◽  
Vol 1550 ◽  
pp. 032078
Author(s):  
Kaigang Fan ◽  
Xin Chen ◽  
Biao Zhao ◽  
Jiale Wang ◽  
Wenbin Cui ◽  
...  
Keyword(s):  
Wireless Local Area Network ◽  
Local Area Network ◽  
Experimental System ◽  
Local Area ◽  
Area Network

scholarly journals DeepLocBox: Reliable Fingerprinting-Based Indoor Area Localization

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2000
Author(s):  
Marius Laska ◽  
Jörg Blankenbach
Keyword(s):  
Wireless Local Area Network ◽  
Indoor Localization ◽  
Local Area Network ◽  
Success Probability ◽  
Local Area ◽  
Position Estimation ◽  
Location Based Services ◽  
Global Navigation Satellite Systems ◽  
Area Network ◽  
Floor Plan

Location-based services (LBS) have gained increasing importance in our everyday lives and serve as the foundation for many smartphone applications. Whereas Global Navigation Satellite Systems (GNSS) enable reliable position estimation outdoors, there does not exist any comparable gold standard for indoor localization yet. Wireless local area network (WLAN) fingerprinting is still a promising and widely adopted approach to indoor localization, since it does not rely on preinstalled hardware but uses the existing WLAN infrastructure typically present in buildings. The accuracy of the method is, however, limited due to unstable fingerprints, etc. Deep learning has recently gained attention in the field of indoor localization and is also utilized to increase the performance of fingerprinting-based approaches. Current solutions can be grouped into models that either estimate the exact position of the user (regression) or classify the area (pre-segmented floor plan) or a reference location. We propose a model, DeepLocBox (DLB), that offers reliable area localization in multi-building/multi-floor environments without the prerequisite of a pre-segmented floor plan. Instead, the model predicts a bounding box that contains the user’s position while minimizing the required prediction space (size of the box). We compare the performance of DLB with the standard approach of neural network-based position estimation and demonstrate that DLB achieves a gain in success probability by 9.48% on a self-collected dataset at RWTH Aachen University, Germany; by 5.48% for a dataset provided by Tampere University of Technology (TUT), Finland; and by 3.71% for the UJIIndoorLoc dataset collected at Jaume I University (UJI) campus, Spain.

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