Papers by Keyword: Received Signal Strength

Abstract: Nowadays, mobile robot tracking is the one of application in wireless sensor networks (WSNs). A one of promising localization algorithm in range-free algorithm is the weighted centroid localization (WCL) algorithm. This work proposed the improved WCL algorithm with quadratic means based on received signal strength (RSS). The ZigBee operated at 2.4 GHz frequency is used to measure in the indoor environment. The final results will be discuss about the comparison of the typically WCL algorithm and the improved WCL algorithm. From the results, the 1-meter-precision of improved WCL is 91.67% and WCL is 83.33%. Moreover, the improved WCL obtained the 16.67% no error of estimated position.

Abstract: The three-dimensional positioning algorithm has become a hot research direction in wireless sensor networks localization algorithms, however the existing 3D positioning algorithms have general shortcomings, such as high complexity, low positioning accuracy, great energy consumption. Aiming at the existing problems of 3D localization algorithm, we propose an decentralized 3D positioning algorithm based on RSSI ranging and free ranging mechanism. The algorithm firstly use measured RSSI to establish beacon node neighborhood. Then the method adopts regional division to obtain initial location information for unknown nodes. Finally, the method use the iterative optimization process to achieve a position information updates. Simulation results demonstrate that proposed algorithm is feasible and has better localization accuracy.

Abstract: We proposea method of RSS-base localization in WSN (Wireless Sensor Network), called Hybrid HMM, to improve the stabilityof node localization basedon RSS(Received Signal Strength).This model utilizesHMM(Hidden Markov Model) to takeinto account the time factor when receiving the RSS sequence, andconverts the action of ranging into an operationof classification.For the received RSS used for localization,our Hybrid HMMwill compare it withthe preset RSS threshold value, and put the result into one of two categories for subsequent processing: If the received value is higher than the threshold value, the distance value will be drawn from the signal propagation model. If lower, the information will be obtained from a trained HMM. Experimental results show that the Hybrid HMM method can greatly improve the localization accuracy.

Abstract: This paper investigates enhancement of fuzzy logic indoor positioning system (FLIPS) and its effect upon the wireless station deployment. The proposed scheme adopts an average filter to improve stability in transforming received signal strength (RSS) between a sensor and stations into distance. Based on the reliable distance data set, a fuzzy logic inference engine determines precise coordinates of the sensor. In order to evaluate the optimal deployment of wireless stations, this study experiments on three different size test areas within three to eight stations. Those results provide considered analysis to develope a more efficient FLIPS.

Abstract: The success of wireless local area networks (WLANs) has led to an intense interest among wireless engineers in understanding and predicting radio propagation characteristics within buildings. This paper present radio signal propagation measurement and modeling at 2.4GHz, within a building in the Faculty of Engineering, University of Benin. A base station built around SENAO access point, and a PA24 flat panel directional antenna of 19dBi gain and 17.50 beam-widths was setup for the experimentation. Signals were monitored from the fixed BS using LINKSYS, and NET STUMBLER version 4.0 software run on a Laptop. In this report, the effect of multi-path and delay spread was not considered. The result of the investigation revealed a significant attenuation of the radio signal within the small distance. A path loss exponent of 7.8 to 8.9 on the ground floor, and 2.9 to 5.2 for the 2nd floor were obtained for the period of investigation.