Radio propagation at microwave frequencies for line-of-sight microcellular mobile and personal communications

1991 ◽  
Vol 40 (1) ◽  
pp. 203-210 ◽  
Author(s):  
A.J. Rustako ◽  
N. Amitay ◽  
G.J. Owens ◽  
R.S. Roman
Keyword(s):  
Radio Propagation ◽  
Line Of Sight ◽  
Personal Communications ◽  
Microwave Frequencies

Radio propagation characteristics for line-of-sight microcellular and personal communications

1993 ◽  
Vol 41 (10) ◽  
pp. 1439-1447 ◽  
Author(s):  
H. Xia ◽  
H.L. Bertoni ◽  
L.R. Maciel ◽  
A. Lindsay-Stewart ◽  
R. Rowe
Keyword(s):  
Radio Propagation ◽  
Line Of Sight ◽  
Propagation Characteristics ◽  
Personal Communications

scholarly journals Oliver Heaviside and the Heaviside layer

2018 ◽  
Vol 376 (2134) ◽  
pp. 20170459
Author(s):  
Hugh Griffiths
Keyword(s):  
Long Range ◽  
Electromagnetic Theory ◽  
Upper Atmosphere ◽  
Radio Propagation ◽  
Line Of Sight ◽  
Theme Issue ◽  
Guglielmo Marconi

In an entry in the Encyclopaedia Britannica in 1902, Oliver Heaviside had suggested the existence of a reflecting layer in the upper atmosphere to account for long range beyond line-of-sight radio propagation of the type demonstrated by Guglielmo Marconi in 1901, in the first transatlantic radio transmission. In about 1910, William Eccles proposed the name ‘Heaviside Layer’ for this phenomenon, and the name has subsequently been adopted and used quite widely. This paper describes the basis of Marconi's experiments and various interpretations of the results in the context of Heaviside's wider work. It also describes some later experiments to measure the height of the ionosphere. This article is part of the theme issue ‘Celebrating 125 years of Oliver Heaviside's ‘Electromagnetic Theory’’.

Ray-tracing analysis of the radio propagation on the line-of-sight maritime wireless environments

2018 ◽  
Vol 8 (4) ◽  
pp. 196
Author(s):  
Yoshinori Matsuura ◽  
Kohei Shimada ◽  
Yasuhiro Sato ◽  
Masaaki Yamanaka ◽  
Daiki Hashimoto
Keyword(s):  
Ray Tracing ◽  
Radio Propagation ◽  
Line Of Sight ◽  
Wireless Environments

Tactical line-of-sight radio propagation reliability modeling

2002 ◽  
Author(s):  
V.J. Procopio ◽  
K.H. Brockel ◽  
J.R. Inserra ◽  
F.G. Loso ◽  
P.A. Major ◽  
...  
Keyword(s):  
Radio Propagation ◽  
Line Of Sight ◽  
Reliability Modeling

scholarly journals An environmental channel throughput and radio propagation modeling for vehicle-to-vehicle communication

2018 ◽  
Vol 14 (4) ◽  
pp. 155014771877253 ◽  
Author(s):  
Mohammed Abdulhakim Al-Absi ◽  
Ahmed Abdulhakim Al-Absi ◽  
TaeYong Kim ◽  
Hoon Jae Lee
Keyword(s):  
Network Performance ◽  
Path Loss ◽  
Packet Delivery Ratio ◽  
Propagation Model ◽  
Radio Propagation ◽  
Propagation Path ◽  
Line Of Sight ◽  
Delivery Ratio ◽  
Intelligent Transport System ◽  
Packet Delivery

Developing a secure and smart intelligent transport system for both safety and non-safety application services requires a certain guarantee of network performance, especially in terms of throughput and packet collision performance. The vehicular ad hoc network propagation is strongly affected due to varying nature of the environment. The existing radio propagation path loss models are designed by using mean additional attenuation sophisticated fading models. However, these models do not consider the obstacle caused due to the obstacle of the vehicle in line of sight of the transmitting and receiving vehicle. Thus, the attenuation signal at the receiving vehicles/devices is affected. To address this issue, we present an obstacle-based radio propagation model that considers the effect caused due to the presence of obstructing vehicle in line of sight. This model is evaluated under different environmental conditions (i.e. city, highway, and rural) by varying the speed of vehicles and vehicles’ density. The performance of the model is evaluated in terms of throughput, collision, transmission efficiency, and packet delivery ratio. The overall result shows that the proposed obstacle-based throughput model is efficient considering varied speed and density. For instance, in the city environment, the model achieves an average improvement of 9.98% and 25.02% for throughput performance over other environments by varying the speed and density of devices respectively and an improvement of 15.04% for packet delivery ratio performance over other environments considering varied speed of devices.

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