Path loss exponent analysis in Wireless Sensor Networks: Experimental evaluation

Miranda, Jorge; Abrishambaf, Reza; Gomes, Tiago; Gonçalves, Paulo B.; Cabral, Jorge; Tavares, Adriano; Monteiro, João L.

doi:10.1109/indin.2013.6622857

Cited by 104 publications

(64 citation statements)

References 8 publications

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“…7b. This is expected, as the free space path loss exponent is known to be 2 [26]. Similarly, C is calculated to be C = −65.24 with 95% confidence bound between (−66.74, −63.74) and C = −88.78 with 95% confidence bound between (−90.7, −86.87), for the indoor and outdoor environments, respectively.…”

Section: B Path Loss Modelmentioning

confidence: 65%

Smart Parking System Based on Bluetooth Low Energy Beacons With Particle Filtering

Mackey

Spachos

Plataniotis

2020

IEEE Systems Journal

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Urban centers and dense populations are expanding, hence, there is a growing demand for novel applications to aid in planning and optimization. In this work, a smart parking system that operates both indoor and outdoor is introduced. The system is based on Bluetooth Low Energy (BLE) beacons and uses particle filtering to improve its accuracy. Through simple BLE connectivity with smartphones, an intuitive parking system is designed and deployed. The proposed system pairs each spot with a unique BLE beacon, providing users with guidance to free parking spaces and a secure and automated payment scheme based on real-time usage of the parking space. Three sets of experiments were conducted to examine different aspects of the system. A particle filter is implemented in order to increase the system performance and improve the credence of the results. Through extensive experimentation in both indoor and outdoor parking spaces, the system was able to correctly predict which spot the user has parked in, as well as estimate the distance of the user from the beacon.

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Section: B Path Loss Modelmentioning

confidence: 65%

Smart Parking System Based on Bluetooth Low Energy Beacons With Particle Filtering

Mackey

Spachos

Plataniotis

2020

IEEE Systems Journal

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“…The v term is the path-loss exponent and takes values between 2 and 6. 37 The v term is set to 2 for the performance analysis. This is also a reasonable system model assumption.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…The d term is the distance and the v term is the path-loss exponent, which takes values between 2 and 6. 37 By defining Ω h = 1 d v and Ω g = 1 (1−d) v and substituting these terms into the derived asymptotic CDF expressions, (18) is utilized, the following expressions can be obtained. Please note that, since the CDF expressions, which are related to one-way information exchange process, in Proposition 1 do not contain the information regarding S 2 → j th untrustworthy relay terminal path, the two-way information exchange CDF derivations are utilized in this subsection.…”

Section: The Untrustworthy Relay Terminals' Optimum Locationmentioning

confidence: 99%

Leakage rate–based untrustworthy relay selection

Özduran

2019

Trans Emerging Tel Tech

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This paper investigates the leakage rate based untrustworthy relay selection strategies, which are based on the untrustworthy relay terminals operate in half-duplex, full-duplex, and hybrid modes. The investigation considers a dual-hop one/two-way half/full-duplex wireless relaying network in the system model. The investigation also considers that a finite number of friendly jammers affect the untrustworthy relay terminals. According to analytical, asymptotic, and Monte Carlo simulation results, the LR-based untrustworthy relay selection strategies achieve cooperative diversity order in high-signal-to-noise ratio.However, friendly jammers and loop interference severely affect the system performance and degrade the achievable diversity order from M to 0 and also cause system coding gain losses. In addition, friendly jammers and loop interference also degrade the system achievable rate performance and cause saturation in high SNRs.Trans Emerging Tel Tech. 2019;30:e3755.wileyonlinelibrary.com/journal/ett

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“…This may lead to suboptimal solution as path losses in free space would be quite different as compared to factories and automation environments. Path loss exponent is a measure of how fast the signal attenuates as a function of distance, is different for these environments in which the CR network would be deployed for which the values are given in Table 1 [14]. This paper investigates power control in CR within these different environments and focuses in the underlay scenario where the PUs and SUs transmit simultaneously in the network.…”

Section: Introductionmentioning

confidence: 99%

Power control in cognitive radios, Internet-of Things (IoT) for factories and industrial automation

Etim

Lota

2016

IECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society

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Abstract-Cognitive radio (CR) is fast emerging as a promising technology that can meet the machine-to machine (M2M) communication requirements for spectrum utilization and power control for large number of machines/devices expected to be connected to the Internet-of Things (IoT). Power control in CR as a secondary user can been modelled as a non-cooperative game cost function to quantify and reduce its effects of interference while occupying the same spectrum as primary user without adversely affecting the required quality of service (QoS) in the network. In this paper a power loss exponent that factors in diverse operating environments for IoT is employed in the non-cooperative game cost function to quantify the required power of transmission in the network. The approach would enable various CRs to transmit with lesser power thereby saving battery consumption or increasing the number of secondary users thereby optimizing the network resources efficiently.

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Path loss exponent analysis in Wireless Sensor Networks: Experimental evaluation

Cited by 104 publications

References 8 publications

Smart Parking System Based on Bluetooth Low Energy Beacons With Particle Filtering

Smart Parking System Based on Bluetooth Low Energy Beacons With Particle Filtering

Leakage rate–based untrustworthy relay selection

Power control in cognitive radios, Internet-of Things (IoT) for factories and industrial automation

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