Investigation of indoor WIFI radio signal propagation

Ali, Abdul Malik Mohd; Razak, Mohd Raziff Abd; Hidayab, Muzaiyanah; Azman, Syuwari Ashraf; M, Jasmin.; Zainol, Mohd Azmir

doi:10.1109/isiea.2010.5679486

Cited by 31 publications

(16 citation statements)

References 8 publications

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“…When the wireless signal propagates in the indoor environment, it is influenced by the obstacles in the propagation path, which cause reflection and diffraction. After the propagation of different paths, each component reaches the receiving end with different strengths and phases, resulting in a multipath effect [16]. The indoor propagation model of the wireless signal is shown in Figure 1.…”

Section: Indoor Propagation Model Of Wireless Signalmentioning

confidence: 99%

Monitoring of Huntington’s Disease Based on Wireless Sensing Technology

et al. 2020

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Huntington’s disease (HD) is a rare genetic disorder that cannot be cured by current medical techniques. With the development of the disease, the life of patients will become more and more difficult. It is necessary to timely and effectively evaluate the development of the patient’s condition based on the patient’s clinical symptoms to help doctors to formulate a reasonable and effective treatment plan, alleviate the condition, and improve the quality of life, which reflects humane care. Currently, wearable devices or video surveillance are generally used to monitor the patients, and these schemes have some disadvantages. This paper presents a new method to monitor patients with HD using wireless sensing technology. Firstly, experimental data were collected by the self-developed microwave sensing platform (MSP), and then the data were preprocessed. Finally, support vector machine (SVM) and random forest (RF) algorithms were used to train the model. The MSP system continuously monitors patients in a non-contact way, which will not bring inconvenience to patients’ lives, and will not involve privacy issues. The experimental results show that the prediction accuracy of SVM can be as high as 98.0% and that of RF can be as high as 96.7%, which proves the feasibility of the technical scheme described in this paper.

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Section: Indoor Propagation Model Of Wireless Signalmentioning

confidence: 99%

Monitoring of Huntington’s Disease Based on Wireless Sensing Technology

et al. 2020

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“…A simple and well accepted propagation model, which takes into account the existence of some obstacles, in open and closed environments, is the Log Distance Path Loss [10,14], whose path loss is calculated with Equation 2:…”

Section: Log-distance Path Loss Modelmentioning

confidence: 99%

802.11g Signal Strength Evaluation in an Industrial Environment

et al. 2020

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The advances in wireless network technologies and Industrial Internet of Things (IIoT) devices are easing the establishment of what is called Industry 4.0. For the industrial environments, the wireless networks are more suitable mainly due to their great flexibility, low deployment cost and for being less invasive.Although new wireless protocols are emerging or being updated, changes in existing industries generally can lead to large expenditures. As the well known and accepted IEEE 802.11g standard, mostly used in residential and commercial applications, has a low deployment and maintenance cost, many industries also decide to adopt it. In this scenario, there is a need to evaluate the signal quality to better design the network infrastructure in order to obtain good communication coverage. In this work, we present a practical study about the 802.11g signal strength in a thermoelectric power plant. We collected signal strength values in different points along the engine room and compared our measured values with the estimated ones through the Log-Distance Path Loss model. We concluded that it is possible to use this model in an industrial environment to estimate signal strength with a low error by choosing the right propagation (path loss) exponent.

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“…As shown in Figure 1 , in an indoor environment, the wireless signal is obstructed by obstacles existing in the environment, and the signal is reflected and diffracted to form a multipath effect [ 30 ]. Different objects interfere differently with the transmission route, and the personnel are located in different locations; therefore, the signal characteristics are not the same.…”

Section: Preliminariesmentioning

confidence: 99%

A Novel Passive Indoor Localization Method by Fusion CSI Amplitude and Phase Information

Dang

Hao

et al. 2019

Sensors

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With the rapid development of wireless network technology, wireless passive indoor localization has become an increasingly important technique that is widely used in indoor location-based services. Channel state information (CSI) can provide more detailed and specific subcarrier information, which has gained the attention of researchers and has become an emphasis in indoor localization technology. However, existing research has generally adopted amplitude information for eigenvalue calculations. There are few research studies that have used phase information from CSI signals for localization purposes. To eliminate the signal interference existing in indoor environments, we present a passive human indoor localization method named FapFi, which fuses CSI amplitude and phase information to fully utilize richer signal characteristics to find location. In the offline stage, we filter out redundant values and outliers in the CSI amplitude information and then process the CSI phase information. A fusion method is utilized to store the processed amplitude and phase information as a fingerprint database. The experimental data from two typical laboratory and conference room environments were gathered and analyzed. The extensive experimental results demonstrate that the proposed algorithm is more efficient than other algorithms in data processing and achieves decimeter-level localization accuracy.

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Investigation of indoor WIFI radio signal propagation

Cited by 31 publications

References 8 publications

Monitoring of Huntington’s Disease Based on Wireless Sensing Technology

Monitoring of Huntington’s Disease Based on Wireless Sensing Technology

802.11g Signal Strength Evaluation in an Industrial Environment

A Novel Passive Indoor Localization Method by Fusion CSI Amplitude and Phase Information

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