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

被引:11
作者
Dolha, Stelian [1 ]
Negirla, Paul [1 ]
Alexa, Florin [2 ]
Silea, Ioan [1 ]
机构
[1] Politehn Univ Timisoara, Dept Automat & Appl Informat, Timisoara 300006, Romania
[2] Politehn Univ Timisoara, Dept Commun, Timisoara 300006, Romania
关键词
sensor networks; RSSI (Received Signal Strength Indicator) acquisition; adjusted transmission power; sensor location estimation; non-linearity of the measured values; RSSI; LOCALIZATION;
D O I
10.3390/s19194179
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Wireless Sensor Networks (WSN) are widely used in different monitoring systems. Given the distributed nature of WSN, a constantly increasing number of research studies are concentrated on some important aspects: maximizing network autonomy, node localization, and data access security. The node localization and distance estimation algorithms have, as their starting points, different information provided by the nodes. The level of signal strength is often such a starting point. A system for Received Signal Strength Indicator (RSSI) acquisition has been designed, implemented, and tested. In this paper, experiments in different operating environments have been conducted to show the variation of Received Signal Strength Indicator (RSSI) metric related to distance and geometrical orientation of the nodes and environment, both indoor and outdoor. Energy aware data transmission algorithms adjust the power consumed by the nodes according to the relative distance between the nodes. Experiments have been conducted to measure the current consumed by the node depending on the adjusted transmission power. In order to use the RSSI values as input for distance or location detection algorithms, the RSSI values can't be used without intermediate processing steps to mitigate with the non-linearity of the measured values. The results of the measurements confirmed that the RSSI level varies with distance, geometrical orientation of the sensors, and environment characteristics.
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页数:20
相关论文
共 24 条
[1]   An accurate prediction method for moving target localization and tracking in wireless sensor networks [J].
Ahmadi, Hanen ;
Viani, Federico ;
Bouallegue, Ridha .
AD HOC NETWORKS, 2018, 70 :14-22
[2]   RSSI-Based Indoor Localization and Identification for ZigBee Wireless Sensor Networks in Smart Homes [J].
Bianchi, Valentina ;
Ciampolini, Paolo ;
De Munari, Ilaria .
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2019, 68 (02) :566-575
[3]   Adaptive iteration localization algorithm based on RSSI in wireless sensor networks [J].
Chen, Haijun ;
Tan, Guanzheng .
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2019, 22 (02) :S3059-S3067
[4]  
Erdogan SZ, 2007, LECT NOTES COMPUT SC, V4809, P389
[5]   Using received signal strength variation for energy efficient data dissemination in wireless sensor networks [J].
Erdogan, Senol Zafer ;
Hussain, Sajid .
DEXA 2007: 18TH INTERNATIONAL CONFERENCE ON DATABASE AND EXPERT SYSTEMS APPLICATIONS, PROCEEDINGS, 2007, :620-+
[6]  
Farooq-i-Azam M, 2012, WIRELESS SENSOR NETWORKS: CURRENT STATUS AND FUTURE TRENDS, P179
[7]   Experimental data set analysis of RSSI-based indoor and outdoor localization in LoRa networks [J].
Goldoni, Emanuele ;
Prando, Luca ;
Vizziello, Anna ;
Savazzi, Pietro ;
Gamba, Paolo .
INTERNET TECHNOLOGY LETTERS, 2019, 2 (01)
[8]   Impacts of Temperature and Humidity variations on RSSI in indoor Wireless Sensor Networks [J].
Guidara, Amir ;
Fersi, Ghofrane ;
Derbel, Faouzi ;
Ben Jemaa, Maher .
KNOWLEDGE-BASED AND INTELLIGENT INFORMATION & ENGINEERING SYSTEMS (KES-2018), 2018, 126 :1072-1081
[9]   Error control and adjustment method for underwater wireless sensor network localization [J].
Han, Yunfeng ;
Zhang, Jucheng ;
Sun, Dajun .
APPLIED ACOUSTICS, 2018, 130 :293-299
[10]   Using received signal strength variation for surveillance in residential areas [J].
Hussain, Sajid ;
Peters, Richard ;
Silver, Daniel L. .
DATA MINING, INTRUSION DETECTION, INFORMATION ASSURANCE, AND DATA NETWORKS SECURITY 2008, 2008, 6973