scholarly journals UNDERGROUND WIRELESS COMMUNICATION CHANNEL MODELING AND SIMULATION USING 0.3GMSK MODULATION CONSIDERING PENETRATION AND SCATTERING LOSS

2014 ◽  
pp. 293-296
Author(s):  
M. N. JAYARAM ◽  
C.R. VENUGOPAL
Keyword(s):  
Experimental Data ◽  
Wireless Communication ◽  
Communication Channel ◽  
Channel Modeling ◽  
Indoor Propagation ◽  
Correction Factors ◽  
Terrestrial Environment ◽  
Propagation Models ◽  
Scattering Loss ◽  
Two Parameters

Wireless communication inside mines and tunnels is very different from that in terrestrial environment because of the strong attenuation of signals. Here, we are developing an empirical model for the underground wireless communication channel based on experimental data which help in predicting the average received signal strength at a given distance from transmitter. The model aims at adding correction factors to the available outdoor and indoor propagation models such as Okumara-hata model, cost231 model, ITU indoor propagation models etc. Modeling is done by choosing the most appropriate model among the available ones and performing regression methods to the model based on experimental data. Correction factors are then added based on two parameters which we are considering namely- Penetration and Scattering loss for 0.3GMSK.

scholarly journals Characterizing the Spectral Properties and Time Variation of the In-Vehicle Wireless Communication Channel

2014 ◽  
Vol 62 (7) ◽  
pp. 2390-2399 ◽  
Author(s):  
Steven Herbert ◽  
Ian Wassell ◽  
Tian-Hong Loh ◽  
Jonathan Rigelsford
Keyword(s):  
Wireless Communication ◽  
Time Variation ◽  
Spectral Properties ◽  
Communication Channel

A Framework for Statistical Channel Modeling in 5G Wireless Communication Systems

2020 ◽  
pp. 31-54
Author(s):  
Caslav Stefanovic ◽  
Danijel Djosic ◽  
Stefan Panic ◽  
Dejan Milic ◽  
Mihajlo Stefanovic
Keyword(s):  
Wireless Communication ◽  
Communication Systems ◽  
Channel Modeling ◽  
Wireless Communication Systems ◽  
Statistical Channel Modeling

scholarly journals Some important details on Richard growth model

2019 ◽  
Vol 23 (Suppl. 6) ◽  
pp. 1901-1908
Author(s):  
Mehmet Gurcan ◽  
Arzu Demirelli
Keyword(s):  
Experimental Data ◽  
Growth Models ◽  
Theoretical Distribution ◽  
Applied Statistics ◽  
Link Function ◽  
Parametric Methods ◽  
Location Parameters ◽  
High Flexibility ◽  
Two Parameters ◽  
Wrapped Distribution

The distribution of the data is very important in all of the parametric methods used in the applied statistics. More clearly, if the experimental data fit well to the theoretical distribution, the results will be more efficient in parametric methods. The adaptability of experimental data to a theoretical distribution depends on the flexibility of the theoretical distribution used. If the flexibility of the theoretical distribution is sufficient, it can be used easily for experimental data. Most of the theoretical distributions have shape and location parameters. However, these two parameters are not always sufficient for the distribution adapt to the experimental data. Therefore, theoretical distributions with high flexibility in parametric methods are needed. Obtaining the new theoretical distributions that provide this feature is important for the literature. In this study, a new probability distribution has been obtained via Richard link function which has been high flexibility. In the introduction, important information is given related to growth models and Richard growth curve. Later, some details about the Richard distribution and wrapped distribution have been given.

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