Name
Abstract | ||
|---|---|---|
Log-distance path loss model have been using as a simple positioning method because of its simplicity which is mainly depends on Received Signal Strength (RSS) along with path loss exponent and random Gaussian noise variable with zero-mean. This model can be extensively used in urban and remote area because it is related to energy representation. On the other hand, fingerprint positioning is also an alternative solution in positioning due to it reliable performance. It is noticed that antenna gain and background thermal noise should be included into the model such that the accuracy could be improved. In this investigation, a sub-urban route was selected as testing area and carried the Particle Swarm Optimization (PSO) for an optimal coordinate. Experimental results show that the new scheme was implemented successfully in RSS positioning resulting in about averaged 100 meters and 84 meters in daytime and evening time respectively in same experiment scene. This new scheme provides a more reliable way in calculating a sensors position. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/IECON.2014.7049087 | IECON |
Keywords | Field | DocType |
gaussian noise,particle swarm optimisation,signal processing,pso,rss,antenna gain,background thermal noise,energy representation,fingerprint positioning,log distance path loss model,outdoor environment,particle swarm optimization,path loss exponent,random gaussian noise variable,received signal strength,remote area,sensors positioning,simple positioning method,suburban route,urban area,antenna,log-distance model,node positioning,noise models,databases,fingerprint recognition,base stations,sensors,mobile communication,accuracy,wireless sensor networks | Particle swarm optimization,Antenna gain,Simulation,Fingerprint recognition,Noise (electronics),Path loss,Engineering,Wireless sensor network,Gaussian noise,RSS | Conference |
ISSN | Citations | PageRank |
1553-572X | 0 | 0.34 |
References | Authors | |
15 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Faan Hei Hung | 1 | 7 | 5.99 |
| Hao Ran Chi | 2 | 45 | 9.32 |
| Benjamin Yee Shing Li | 3 | 1 | 1.02 |
| Kim Fung Tsang | 4 | 61 | 26.02 |