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Item type:Item, Distance-based indoor localization system utilizing general path loss model and RSSI(2020-11-01) ;Suroso, Dwi Joko ;Arifin, MuhammadCherntanomwong, PanaratWireless sensor networks (WSNs) have a vital role in indoor localization development. As today, there are more demands in location-based service (LBS), mainly indoor environments, which put the researches on indoor localization massive attention. As the global-positioning-system (GPS) is unreliable indoor, some methods in WSNs-based indoor localization have been developed. Path loss model-based can be useful for providing the power-distance relationship the distance-based indoor localization. Received signal strength indicator (RSSI) has been commonly utilized and proven to be a reliable yet straightforward metric in the distance-based method. We face issues related to the complexity of indoor localization to be deployed in a real situation. Hence, it motivates us to propose a simple yet having acceptable accuracy results. In this research, we applied the standard distance-based methods, which are is trilateration and min-max or bounding box algorithm. We used the RSSI values as the localization parameter from the ZigBee standard. We utilized the general path loss model to estimate the traveling distance between the transmitter (TX) and receiver (RX) based on the RSSI values. We conducted measurements in a simple indoor lobby environment to validate the performance of our proposed localization system. The results show that the min-max algorithm performs better accuracy compared to the trilateration, which yields an error distance of up to 3m. By these results, we conclude that the distance-based method using ZigBee standard working on 2.4 GHz center frequency can be reliable in the range of 1-3m. This small range is affected by the existence of interference objects (IOs) lead to signal multipath, causing the unreliability of RSSI values. These results can be the first step for building the indoor localization system, which low-cost, low-complexity, and can be applied in many fields, especially indoor robots and small devices in internet-of-things (IoT) world's today. - Some of the metrics are blocked by yourconsent settings
Item type:Item, Prediction model for broadcasting propagation in urban area(2017-01-01) ;Keawbunsong, Pitak ;Supannakoon, PitchayaPromwong, SathapornThis study proposes an optimization of the path loss propagation model for prediction digital terrestrial television broadcasting in urban area Southern of Thailand. The measurement areas are considered both Songkla and Surathani Provinces that we conducted the data collection of the received signal radio broadcasting in 4 channels (510-790 MHz). The optimization of the path loss propagation model is based on Least Square (LS) method. The statistical results such Hata path loss model is optimized as a comparison with others model. We confirm that the proposed method provides for a data processing suitably in a prediction path loss model. - Some of the metrics are blocked by yourconsent settings
Item type:Item, Investigated performance of Davidson model for DVB-T2 propagation in medium and small urban area(2017-01-01) ;Keawbunsong, Pitak ;Supannakoon, PitchayaPromwong, SathapornThis study investigates the efficiency of Davidson Path Loss Model in order to apply for use in the DVB-T2 propagation network design for medium and small urban areas in southern Thailand. The data being collected from the electric field strength while broadcasting of two channels within urban areas of Hadyai, Songkla Province are used for the path loss analysis. The result through a comparison on the efficiency of an old Davidson Model and a calibrated Root Mean Square Error (RMSE) model along with an efficiency index of Relative Error (RE) shows that the old Davidson Model is closer to the measured data than the calibrated ones. The statistics also demonstrates that the RE of the old Davidson Model is at the least when being compared with the RE of both the calibrated and the Hata Models. The old Davidson Model is therefore, the most accurate and the most optimized for the design of the propagation network. - Some of the metrics are blocked by yourconsent settings
Item type:Item, Optimum path loss model calibration for prediction DTTV propagation in urban area of southern Thailand(2015-12-01) ;Keawbunsong, PitakPromwong, SathapornThis article offers an optimum path loss model calibration for the prediction of DTTV propagation in an urban area of southern Thailand by selecting the urban area of Hat Yai, Songkla Province where there is density of high rises and buildings as a data collecting place. The data are collected from the measurement of the network operators’ transmitted signal levels among four channels: CH26 with the frequency of 514 MHz; CH42 with the frequency of 642 MHz; CH46 with the frequency of 674 MHz and CH54 with the frequency of 738 MHz, whereas the distance from the transmitted station ranges between 2.5 and 6.5 km. The calibration is conducted through a method of mean error (ME) and root mean square error (RMSE) from the value of the received signal and the calibrated model’s efficient indicator is through the value of relative error (RE). The analytical results of ME and RMSE show that the new Hata Path Loss Model is optimal for the calibration as its RE value is not only closer to zero but also closer to the measured data than the original model or other compared models. The path loss calibration with ME value is more accurate and more suitable for the work of the network design than the ones using RMSE value. - Some of the metrics are blocked by yourconsent settings
Item type:Item, Optimization of path loss model for prediction DTTV propagation in urban area of Southern Thailand(2015-10-01) ;Keawbunsong, Pitak ;Supannakoon, PitchayaPromwong, SathapornThis article presents the optimization of a path loss model in order to design the DTTV propagation network in the urban area of southern Thailand by selecting urban Hat Yai, Songkla Province as the case study for data collection on received signal power from the signal measurement during the broadcasting of the network operators in 4 channels. A least square method is used to optimize the path loss model while an efficient indicator is conducted through a statistical value of mean error (ME), root mean square error (RMSE) and standard deviation of error (SD). It is found that Hata path loss model is the most suitable for the optimization process. Through the least square method, a parameter of the constant value of each frequency is obtained. The statistical values indicate that new Hata path loss model is closer to the measured data than the original predicted model which proves that the Hata model is more precise and more optimized for the planning and designing the network. - Some of the metrics are blocked by yourconsent settings
Item type:Item, Measurement and modeling of UWB path loss for single-band and multi-band propagation channel(2005-12-01) ;Chamchoy, Monchai ;Doungdeun, WorawootPromwong, SathapornIn this paper, the measured data and the empirical path loss models for 3.1-10.6 GHz ultra-wideband (UWB) radio propagation in the residential environment for single-band and multi-band communication are presented. The path loss characteristics are demonstrated based on the measured channel for line of sight (LOS) propagation by using the double ridge horn antenna and the biconical antenna to investigate the dependence of the antenna directivity on the UWB system. The characterization of the path loss exponent, n, and the reference path loss, PL(d<inf>0</inf>), are provided. In the case of the single-band propagation, as the results, the path loss increases as the T-R separation distance increases as same as the multi-band propagation. For the case of the multi-band channel, however, the path loss exponent can randomly change according to each propagation scheme and subband frequency. Therefore, the propagation path loss models are developed to understand the phenomenon of the indoor residential com-munication systems for home wireless networking. © 2005 IEEE.
