Extended Gradient RSSI Predictor and Filter for Signal Prediction and Filtering in Communication Holes
In wireless communication, received signal strength indicator (RSSI) is a measurement of power in the received signal. This parameter is mainly used in radio frequency (RF) based distance estimation, position estimation, and handover mechanisms. In real-time applications such as object tracking, a h...
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Kluwer Academic Publishers
2015
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my.utp.eprints.259742021-08-30T08:48:51Z Extended Gradient RSSI Predictor and Filter for Signal Prediction and Filtering in Communication Holes Subhan, F. Ahmed, S. Ashraf, K. Imran, M. In wireless communication, received signal strength indicator (RSSI) is a measurement of power in the received signal. This parameter is mainly used in radio frequency (RF) based distance estimation, position estimation, and handover mechanisms. In real-time applications such as object tracking, a handover mechanism, distance estimations require continuous reception of RSSI measurements in order to accurately estimate the position of the object. However, there are some constraints such as signal attenuation, signal loss, multi-path effects. These parameters cause variations in RSSI, and hence it becomes weak, which produces communication holes. Communication holes refer to the phenomenon when the signal drops to zero, and there is a communication blockage, which is practically negligible and can be considered as disconnection. This communication hole occurs due to various factors such as multi-path effects, noise, moving out of the coverage zone, device manufacturing faults, and inquiry procedure as well. The main focus of this paper is to address the issue of communication holes in Bluetooth networks. In Bluetooth networks communication holes also occur due to the delay in the inquiry procedure. Therefore, an existing gradient filter is modified based on the most recent measurements received. The proposed extended gradient filter is tested using simulated and real time RSSI measurements and compared with Kalman Filter and Kalman Smoother. The results show better performance in case of communication holes occurrence. © 2015, Springer Science+Business Media New York. Kluwer Academic Publishers 2015 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-84930542439&doi=10.1007%2fs11277-015-2394-2&partnerID=40&md5=5804cb1d9efcc677581084a3ed21e0ac Subhan, F. and Ahmed, S. and Ashraf, K. and Imran, M. (2015) Extended Gradient RSSI Predictor and Filter for Signal Prediction and Filtering in Communication Holes. Wireless Personal Communications, 83 (1). pp. 297-314. http://eprints.utp.edu.my/25974/ |
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In wireless communication, received signal strength indicator (RSSI) is a measurement of power in the received signal. This parameter is mainly used in radio frequency (RF) based distance estimation, position estimation, and handover mechanisms. In real-time applications such as object tracking, a handover mechanism, distance estimations require continuous reception of RSSI measurements in order to accurately estimate the position of the object. However, there are some constraints such as signal attenuation, signal loss, multi-path effects. These parameters cause variations in RSSI, and hence it becomes weak, which produces communication holes. Communication holes refer to the phenomenon when the signal drops to zero, and there is a communication blockage, which is practically negligible and can be considered as disconnection. This communication hole occurs due to various factors such as multi-path effects, noise, moving out of the coverage zone, device manufacturing faults, and inquiry procedure as well. The main focus of this paper is to address the issue of communication holes in Bluetooth networks. In Bluetooth networks communication holes also occur due to the delay in the inquiry procedure. Therefore, an existing gradient filter is modified based on the most recent measurements received. The proposed extended gradient filter is tested using simulated and real time RSSI measurements and compared with Kalman Filter and Kalman Smoother. The results show better performance in case of communication holes occurrence. © 2015, Springer Science+Business Media New York. |
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Subhan, F. Ahmed, S. Ashraf, K. Imran, M. |
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Subhan, F. Ahmed, S. Ashraf, K. Imran, M. Extended Gradient RSSI Predictor and Filter for Signal Prediction and Filtering in Communication Holes |
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Subhan, F. Ahmed, S. Ashraf, K. Imran, M. |
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Subhan, F. |
title |
Extended Gradient RSSI Predictor and Filter for Signal Prediction and Filtering in Communication Holes |
title_short |
Extended Gradient RSSI Predictor and Filter for Signal Prediction and Filtering in Communication Holes |
title_full |
Extended Gradient RSSI Predictor and Filter for Signal Prediction and Filtering in Communication Holes |
title_fullStr |
Extended Gradient RSSI Predictor and Filter for Signal Prediction and Filtering in Communication Holes |
title_full_unstemmed |
Extended Gradient RSSI Predictor and Filter for Signal Prediction and Filtering in Communication Holes |
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extended gradient rssi predictor and filter for signal prediction and filtering in communication holes |
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Kluwer Academic Publishers |
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2015 |
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https://www.scopus.com/inward/record.uri?eid=2-s2.0-84930542439&doi=10.1007%2fs11277-015-2394-2&partnerID=40&md5=5804cb1d9efcc677581084a3ed21e0ac http://eprints.utp.edu.my/25974/ |
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