Monte Carlo Bayesian Signal Processing for Wireless Communications

2006 ◽  
pp. 89-105 ◽  
Author(s):  
Xiaodong Wang ◽  
Rong Chen ◽  
Jun S. Liu
Keyword(s):  
Signal Processing ◽  
Monte Carlo ◽  
Wireless Communications ◽  
Bayesian Signal Processing

scholarly journals Applications of Time-Frequency Signal Processing in Wireless Communications and Bioengineering

2011 ◽  
Vol 2010 (1) ◽  
Author(s):  
LuisF Chaparro (EURASIP Member) ◽  
Aydın Akan (EURASIP Member) ◽  
SyedIsmail Shah ◽  
Lutfiye Durak-Ata
Keyword(s):  
Signal Processing ◽  
Wireless Communications ◽  
Frequency Signal ◽  
Time Frequency

RF Coupling Simulation Model Development for Optimal Placement of Antennas Supporting Wireless Communications Systems

2009 ◽  
Author(s):  
Robert Gray ◽  
Mike DiBenedetto
Keyword(s):  
Monte Carlo ◽  
Wireless Communications ◽  
Model Development ◽  
Cost Effective ◽  
Optimal Placement ◽  
Communications Systems ◽  
Effective Manner ◽  
Close Proximity ◽  
Wireless Communications Systems ◽  
Antenna Placement

The locomotive cab’s limited rooftop area requires that the transmitting and receiving antennas for communications be placed in close proximity to one another. Currently, no means exist to aid the railroad radio frequency (RF) engineer in placing these antennas so that mutual communications interference is minimized. The goal of this paper is to describe a method that can be used to determine optimal antenna placement in a time- and cost-effective manner. The method described below utilizes various forms of the Friis transmission equation in Monte Carlo simulations.

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