Scalable Parallel Execution of an Event-Based Radio Signal Propagation Model for Cluttered 3D Terrains

2009 ◽  
Author(s):  
Sudip K. Seal ◽  
Kalyan S. Perumalla
Keyword(s):  
Radio Signal ◽  
Signal Propagation ◽  
Parallel Execution ◽  
Propagation Model ◽  
Event Based ◽  
Signal Propagation Model

scholarly journals A Least Square-Based Self-Adaptive Localization Method for Wireless Sensor Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-9
Author(s):  
Baoguo Yu ◽  
Yao Wang ◽  
Chenglong He ◽  
Xiaozhen Yan ◽  
Qinghua Luo
Keyword(s):  
Radio Signal ◽  
Signal Propagation ◽  
Propagation Model ◽  
Least Square ◽  
Wireless Sensor ◽  
Localization Accuracy ◽  
Localization Method ◽  
Unknown Node ◽  
Signal Propagation Model ◽  
Self Adaptive

In the wireless sensor network (WSN) localization methods based on Received Signal Strength Indicator (RSSI), it is usually required to determine the parameters of the radio signal propagation model before estimating the distance between the anchor node and an unknown node with reference to their communication RSSI value. And finally we use a localization algorithm to estimate the location of the unknown node. However, this localization method, though high in localization accuracy, has weaknesses such as complex working procedure and poor system versatility. Concerning these defects, a self-adaptive WSN localization method based on least square is proposed, which uses the least square criterion to estimate the parameters of radio signal propagation model, which positively reduces the computation amount in the estimation process. The experimental results show that the proposed self-adaptive localization method outputs a high processing efficiency while satisfying the high localization accuracy requirement. Conclusively, the proposed method is of definite practical value.

scholarly journals A Review on Human Body Communication: Signal Propagation Model, Communication Performance, and Experimental Issues

2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Jian Feng Zhao ◽  
Xi Mei Chen ◽  
Bo Dong Liang ◽  
Qiu Xia Chen
Keyword(s):  
Human Body ◽  
Signal Propagation ◽  
The Body ◽  
Propagation Model ◽  
Area Network ◽  
Communication Performance ◽  
Channel Characteristics ◽  
Communication Signal ◽  
Signal Propagation Model ◽  
Human Body Communication

Human body communication (HBC), which uses the human body tissue as the transmission medium to transmit health informatics, serves as a promising physical layer solution for the body area network (BAN). The human centric nature of HBC offers an innovative method to transfer the healthcare data, whose transmission requires low interference and reliable data link. Therefore, the deployment of HBC system obtaining good communication performance is required. In this regard, a tutorial review on the important issues related to HBC data transmission such as signal propagation model, channel characteristics, communication performance, and experimental considerations is conducted. In this work, the development of HBC and its first attempts are firstly reviewed. Then a survey on the signal propagation models is introduced. Based on these models, the channel characteristics are summarized; the communication performance and selection of transmission parameters are also investigated. Moreover, the experimental issues, such as electrodes and grounding strategies, are also discussed. Finally, the recommended future studies are provided.

The Hybrid HMM for RSS-Based Localization in Wireless Sensor Networks

2013 ◽  
Vol 347-350 ◽  
pp. 796-802 ◽  
Author(s):  
Yan Hong Zang ◽  
Jin Song Wang ◽  
Lin Ling ◽  
Pei Zhong Lu
Keyword(s):  
Wireless Sensor Networks ◽  
Hidden Markov ◽  
Signal Strength ◽  
Threshold Value ◽  
Signal Propagation ◽  
Propagation Model ◽  
Wireless Sensor ◽  
Node Localization ◽  
Localization Accuracy ◽  
Signal Propagation Model

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.

scholarly journals Spatiotemporal Location Fingerprint Generation Using Extended Signal Propagation Model

2012 ◽  
Vol 7 (5) ◽  
pp. 789-796 ◽  
Author(s):  
Hee-Sung Kim ◽  
Binghao Li ◽  
Wan-Sik Choi ◽  
Sang-Kyung Sung ◽  
Hyung-Keun Lee
Keyword(s):  
Signal Propagation ◽  
Propagation Model ◽  
Spatiotemporal Location ◽  
Signal Propagation Model

scholarly journals Signal Propagation Model for Microcells at 900 MHz Frequency Range

2015 ◽  
Vol 21 (4) ◽  
Author(s):  
Saulius Japertas ◽  
Karolis Pilipavičius ◽  
Dilip Janarthanan
Keyword(s):  
Signal Propagation ◽  
Propagation Model ◽  
Frequency Range ◽  
Signal Propagation Model

scholarly journals Robot Task Allocation Using Signal Propagation Model

2013 ◽  
Vol 18 ◽  
pp. 1505-1514 ◽  
Author(s):  
Małgorzata Żabińska ◽  
Tomasz Sośnicki ◽  
Wojciech Turek ◽  
Krzysztof Cetnarowicz
Keyword(s):  
Task Allocation ◽  
Signal Propagation ◽  
Propagation Model ◽  
Robot Task ◽  
Signal Propagation Model
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