Path Loss Algorithms for Data Resilience in Wireless Body Area Networks for Healthcare Framework

Alzubi, Ahmed

doi:10.1016/b978-0-12-811373-8.00013-6

Cited by 10 publications

(6 citation statements)

References 38 publications

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“…It is crucial to remember that even when a path is lost, the transmitted signal may still travel along other paths to its destination; this process is known as multipath. Since these waves or transmitted data travel along different paths, the wave may reconvene at the destination point, resulting in significantly different received signals [ 38 ].…”

Section: Literature Reviewmentioning

confidence: 99%

Path Loss Measurements and Model Analysis in an Indoor Corridor Environment at 28 GHz and 38 GHz

Oladimeji

Kumar

Elmezughi

2022

Sensors

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This paper examines the large-scale path loss models for an indoor corridor environment at frequencies of 28 and 38 GHz. The measurement environment consists of an indoor corridor with both line-of-sight (LOS) and non-line of sight (NLOS) scenarios using vertical–vertical (V–V) and vertical–horizontal (V–H) antenna polarizations. The single-frequency close-in (CI), floating intercept (FI), free space large-scale path loss models and measured data from the measurement campaign were used to evaluate the performance analysis. The paper also focuses on various parameters, such as standard deviation, path loss exponent (PLE), accuracy, simplicity, and stability of the models. The analysis focuses on the peculiarity of the effect of the wall proximity on the path loss parameters as well as comparisons with the parameters in some of the reviewed literature studies. The FI and CI models produce comparable results for both antenna polarizations and clearly fit with the measured path loss. The PLE, with the highest value of 3.33 at 38 GHz (V–H), is much higher in the NLOS scenario with V–H polarization due to the signal degradation along the path from the transmitter (Tx) to the receiver (Rx). This is because there is no direct LOS between the Tx and Rx antennas. The Rx only relies on signal diffractions and reflections from obstacles as it transmits through the path from the Tx antenna. The path loss measurements and model analysis presented here are useful in designing 5G wireless communication systems for indoor environments, particularly for power budget calculations.

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Section: Literature Reviewmentioning

confidence: 99%

Path Loss Measurements and Model Analysis in an Indoor Corridor Environment at 28 GHz and 38 GHz

Oladimeji

Kumar

Elmezughi

2022

Sensors

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“…Path loss is an attenuation that occurs as an electromagnetic wave travels through a channel, reducing its power density. Path loss can take several forms, ranging from natural radio wave propagation to diffraction path loss caused by interference, to saturation path loss caused by the presence of a signal that is not transparent to electromagnetic waves [23]. Between communication hops, we use the sum of all path losses.…”

Section: Environment Modelmentioning

confidence: 99%

Reinforcement Learning Environment for Advanced Vehicular Ad Hoc Networks Communication Systems

Teixeira

Huszák

2022

Sensors

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Ad hoc vehicular networks have been identified as a suitable technology for intelligent communication amongst smart city stakeholders as the intelligent transportation system has progressed. However, in a highly mobile area, the growing usage of wireless technologies creates a challenging context. To increase communication reliability in this environment, it is necessary to use intelligent tools to solve the routing problem to create a more stable communication system. Reinforcement Learning (RL) is an excellent tool to solve this problem. We propose creating a complex objective space with geo-positioning information of vehicles, propagation signal strength, and environmental path loss with obstacles (city map, with buildings) to train our model and get the best route based on route stability and hop number. The obtained results show significant improvement in the routes’ strength compared with traditional communication protocols and even with other RL tools when only one parameter is used for decision making.

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“…ESTIMATOR Under ideal conditions, the power density of BLE signals are only attenuated as their waves expand through space. This phenomenon is widely-known as path-loss [15]. Considering this phenomenon, the relationship between BLE-RSSI and the distance between transmitter and receiver can be inferred.…”

Section: Rssi-fuzzy Classification As Distancementioning

confidence: 99%

Smartphone Distance Estimation Based on RSSI-Fuzzy Classification Approach

Pascacio

Casteleyn

Torres-Sospedra³

2021

2021 International Conference on Localization and GNSS (ICL-GNSS)

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Path Loss Algorithms for Data Resilience in Wireless Body Area Networks for Healthcare Framework

Cited by 10 publications

References 38 publications

Path Loss Measurements and Model Analysis in an Indoor Corridor Environment at 28 GHz and 38 GHz

Path Loss Measurements and Model Analysis in an Indoor Corridor Environment at 28 GHz and 38 GHz

Reinforcement Learning Environment for Advanced Vehicular Ad Hoc Networks Communication Systems

Smartphone Distance Estimation Based on RSSI-Fuzzy Classification Approach

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