Considerations about the Signal Level Measurement in Wireless Sensor Networks for Node Position Estimation

Dolha, Stelian-Ilie; Negirla, Paul; Alexa, Florin; Silea, Ioan

doi:10.3390/s19194179

Cited by 14 publications

(13 citation statements)

References 22 publications

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“…We deduced that area 1 and area 2 are the optimal cases in terms of localization accuracy. In addition to the distance impact, the authors in [ 39 ] prove that the main drawback of the RSSI technique is its sensitivity to harsh and uncertain sensing environments. Additionally, the RSSI level changes according to the geometrical orientation of sensors and environmental characteristics, which leads to significant estimation errors.…”

Section: The Proposed Recursive Localization Algorithmmentioning

confidence: 99%

Improved Recursive DV-Hop Localization Algorithm with RSSI Measurement for Wireless Sensor Networks

Messous

Liouane

Cheikhrouhou

et al. 2021

Sensors

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As localization represents the main backbone of several wireless sensor networks applications, several localization algorithms have been proposed in the literature. There is a growing interest in the multi-hop localization algorithms as they permit the localization of sensor nodes even if they are several hops away from anchor nodes. One of the most famous localization algorithms is the Distance Vector Hop (DV-Hop). Aiming to minimize the large localization error in the original DV-Hop algorithm, we propose an improved DV-Hop algorithm in this paper. The distance between unknown nodes and anchors is estimated using the received signal strength indication (RSSI) and the polynomial approximation. Moreover, the proposed algorithm uses a recursive computation of the localization process to improve the accuracy of position estimation. Experimental results show that the proposed localization technique minimizes the localization error and improves the localization accuracy.

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Section: The Proposed Recursive Localization Algorithmmentioning

confidence: 99%

Improved Recursive DV-Hop Localization Algorithm with RSSI Measurement for Wireless Sensor Networks

Messous

Liouane

Cheikhrouhou

et al. 2021

Sensors

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“…At this time, each node can calculate RSSI for other neighbor nodes. According to RSSI research [ 21 , 28 , 29 , 30 , 31 ], the signal strength gradually decreases as the distance increases. In addition, according to RSSI research [ 32 ], as the RSSI signal decreases, the packet reception rate decreases as well.…”

Section: Proposed Schemementioning

confidence: 99%

Energy-Efficient and Reliable Face-Routing Scheme in Wireless Networks

Cho

Kim

et al. 2021

Sensors

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Face-routing is one of the reliable recovery schemes when geographic routing fails to transmit data packets. Although studies on face-routing can overcome the failure of the data transmission, they lead to much energy consumption due to frequent data transmissions between adjacent nodes for carrying out the rule of face-routing. To avoid the frequent data transmissions, several face-routing schemes have been recently proposed to transmit data packets to the farthest-neighbor node. However, they happen with many data retransmissions because the farthest-neighbor node has a relatively low transmission success ratio. To solve this problem, we propose a new face-routing scheme that determines the most appropriate neighbor node to balance the trade-off between energy efficiency and transmission reliability with two viewpoints. The first viewpoint focuses on how to increase the distance progress of the data delivery in one-hop range to enhance energy efficiency. After that, the second viewpoint focuses on how to increase the success ratio of the data delivery to enhance the transmission reliability. As a result of the simulation, it was confirmed that the proposed method achieves better performance in terms of energy efficiency than existing face-routing research, and it is better than recent face-routing research in terms of reliability and retransmission.

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“…In addition to topological arrangement, other elements that affect WSN node transmission include distance between communicating nodes and their alignment, channel characteristics and signal attenuation and fading, and presence of noise and other interfering signals, such elements are approximated using path loss and shadowing models. WSN topologies are linked to path loss parameters, and better designs can be achieved when values resulting from node communication are obtained using an appropriate path loss model, which also includes routing protocols and WSN nodes life time [21][22][23][24][25][26].…”

Section: Introductionmentioning

confidence: 99%

Investigation of Error Probability for Grid and Random Uniform Topologies in a Variable Noise Environment

Iskandarani

2022

Journal of Computer Networks and Communications

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Investigation of the effect of topology on the communication efficiency of WSN nodes is carried out through simulation of 9 nodes in a 12 by 12 meters area. The obtained data and plots indicate that the grid topology is a more efficient and stable topology to use in comparison to the random uniform topology. The deduction is supported by probability of error as a function of error distribution values. Five different noise levels are used in the simulation (0dBm, −20 dBm, −40 dBm, −60 dBm, −80 dBm, and −100 dBm) with an output power of −10 dBm. The work shows that at −60 dBm redistribution of probability of error as a function of error values started to occur with higher level error values associated with the random uniform topology compared with the grid topology occurring at −60 dBm noise. The work also shows the relationship between received signal strength indicator (RSSI) and probability of error which decreases as RSSI increase in a similar manner as signal to noise ratio (SNR). Both RSSI and SNR are related through the mathematical model presented in the paper which is based on the path loss model. Common features between the error probability model and Gaussian interpolation function are also presented. A simplified 1-D design model is also presented to enable initial topology considerations. Criteria are also established to enable relating SNR, RSSI, topology, and WSN incremental position.

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Considerations about the Signal Level Measurement in Wireless Sensor Networks for Node Position Estimation

Cited by 14 publications

References 22 publications

Improved Recursive DV-Hop Localization Algorithm with RSSI Measurement for Wireless Sensor Networks

Improved Recursive DV-Hop Localization Algorithm with RSSI Measurement for Wireless Sensor Networks

Energy-Efficient and Reliable Face-Routing Scheme in Wireless Networks

Investigation of Error Probability for Grid and Random Uniform Topologies in a Variable Noise Environment

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