Ray Tracing Based Wireless Channel Modeling over the Sea Surface near Diaoyu Islands

2015 ◽  
Author(s):  
Yanyang Wu ◽  
Zhibin Gao ◽  
Canbin Chen ◽  
Lianfen Huang ◽  
Hua-Pei Chiang ◽  
...  
Keyword(s):  
Ray Tracing ◽  
Channel Modeling ◽  
Wireless Channel ◽  
Sea Surface ◽  
Wireless Channel Modeling

Marine mobile wireless channel modeling based on improved spatial partitioning ray tracing

2020 ◽  
Vol 17 (3) ◽  
pp. 1-11
Author(s):  
Zhibin Gao ◽  
Bang Liu ◽  
Zhipeng Cheng ◽  
Canbin Chen ◽  
Lianfen Huang
Keyword(s):  
Ray Tracing ◽  
Channel Modeling ◽  
Wireless Channel ◽  
Spatial Partitioning ◽  
Mobile Wireless ◽  
Wireless Channel Modeling

Underwater Optical Wireless Channel Modeling Using Monte-Carlo Method

2011 ◽  
Author(s):  
P. Sri Saini ◽  
Shanthi Prince ◽  
P. Predeep ◽  
Mrinal Thakur ◽  
M. K. Ravi Varma
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Channel Modeling ◽  
Wireless Channel ◽  
Optical Wireless ◽  
Wireless Channel Modeling

A Generic Method for the Reliable Calculation of Large-Scale Fading in an Obstacle-Dense Propagation Environment

2013 ◽  
pp. 256-277
Author(s):  
Theofilos Chrysikos ◽  
Stavros Kotsopoulos ◽  
Eduard Babulak
Keyword(s):  
Large Scale ◽  
Path Loss ◽  
Signal Strength ◽  
Channel Modeling ◽  
Wireless Channel ◽  
Mathematical Tool ◽  
Shadow Fading ◽  
Estimation Model ◽  
Statistical Parameters ◽  
Wireless Channel Modeling

The aim of this chapter is to summarize and present recent findings in the field of wireless channel modeling that provide a new method for the reliable calculation of the statistical parameters of large-scale variations of the average received signal (shadow fading). This algorithm is theoretically based on a path loss estimation model that incorporates losses due to walls and floors. This has been confirmed to be the most precise mathematical tool for average signal strength prediction for various frequencies of interest and propagation environments. The total path loss is estimated as a sum of two independent attenuation processes: free space loss and losses due to obstacles. This solution allows for a direct and reliable calculation of the deviation of the fluctuations of the average received signal in an obstacle-dense environment.

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