Vehicle-to-vehicle Channel Characteristics in Municipal Lake Scenarios at 5.9 GHz

2018 ◽  
Author(s):  
Fuxing Chang ◽  
Kun Yang ◽  
Wei Chen ◽  
Changzhen Li ◽  
Junyi Yu
Keyword(s):  
Channel Characteristics ◽  
Vehicle To Vehicle ◽  
Municipal Lake

scholarly journals Analysis of Non-Stationarity for 5.9 GHz Channel in Multiple Vehicle-to-Vehicle Scenarios

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3626
Author(s):  
Fang Li ◽  
Wei Chen ◽  
Yishui Shui
Keyword(s):  
Transmission Rate ◽  
Radio Channel ◽  
Vertical Direction ◽  
Statistical Characteristics ◽  
Small Scale ◽  
Delay Spread ◽  
Important Indicator ◽  
Power Delay Profile ◽  
Channel Characteristics ◽  
Vehicle To Vehicle

The vehicle-to-vehicle (V2V) radio channel is non-stationary due to the rapid movement of vehicles. However, the stationarity of the V2V channels is an important indicator of the V2V channel characteristics. Therefore, we analyzed the non-stationarity of V2V radio channels using the local region of stationarity (LRS). We selected seven scenarios, including three directions of travel, i.e., in the same, vertical, and opposite directions, and different speeds and environments in a similar driving direction. The power delay profile (PDP) and LRS were estimated from the measured channel impulse responses. The results show that the most important influences on the stationary times are the direction and the speed of the vehicles. The average stationary times for driving in the same direction range from 0.3207 to 1.9419 s, the average stationary times for driving in the vertical direction are 0.0359–0.1348 s, and those for driving in the opposite direction are 0.0041–0.0103 s. These results are meaningful for the analysis of the statistical characteristics of the V2V channel, such as the delay spread and Doppler spread. Small-scale fading based on the stationary times affects the quality of signals transmitted in the V2V channel, including the information transmission rate and the information error code rate.

Vehicle-to-Vehicle Radio Channel Characteristics for a Long-Distance Urban Congestion Scenario at 5.9 GHz

2021 ◽  
Author(s):  
Kun Yang ◽  
Ning Zhou ◽  
Haoyu Zhang ◽  
Tong Peng ◽  
Junyi Yu ◽  
...  
Keyword(s):  
Radio Channel ◽  
Long Distance ◽  
Channel Characteristics ◽  
Vehicle To Vehicle

scholarly journals Vehicle-to-Vehicle Channel Characterization Based on Ray-Tracing for Urban Road Scenarios

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Lei Xiong ◽  
Zhiyi Yao ◽  
Haiyang Miao ◽  
Bo Ai
Keyword(s):  
Ray Tracing ◽  
Path Loss ◽  
Angular Spread ◽  
Line Of Sight ◽  
Delay Spread ◽  
Urban Road ◽  
Rms Delay Spread ◽  
Channel Characteristics ◽  
Vehicle To Vehicle ◽  
Simulation Results

In this paper, the vehicle-to-vehicle (V2V) channel characteristics in peak hours at the 5.9 GHz band in two typical urban road scenarios, the urban straight road and the intersection, are investigated. The channel characteristics, such as path loss, root mean square (RMS) delay spread, and angular spread, are derived from the ray-tracing (RT) simulations. Due to the low height of antennas at both the transmitter (Tx) and the receiver (Rx), the line of sight (LOS) between the Tx and the Rx will often be obstructed by other vehicles. Based on the RT simulation results, the shadowing loss is modelled by the multimodal Gaussian distribution, and path loss models in both LOS and non-LOS (NLOS) conditions are obtained. And the RMS delay spread in two scenarios can be modelled by the Weibull distribution. In addition, the deployment of an antenna array is discussed based on the statistics distribution of the angular spread.

Stereological Analyses of Hepatocyte Ultrastructure Monitor Arsenic Liver Burdens

1980 ◽  
Vol 38 ◽  
pp. 442-443
Author(s):  
E. M. B. Sorensen ◽  
R. R. Mitchell ◽  
L. L. Graham
Keyword(s):  
Drainage System ◽  
Water Levels ◽  
Ultrastructural Changes ◽  
Hepatocyte Ultrastructure ◽  
Lepomis Cyanellus ◽  
Large Numbers ◽  
Activation Data ◽  
Water Analyses ◽  
Municipal Lake ◽  
Green Sunfish

Endemic freshwater teleosts were collected from a portion of the Navosota River drainage system which had been inadvertently contaminated with arsenic wastes from a firm manufacturing arsenical pesticides and herbicides. At the time of collection these fish were exposed to a concentration of 13.6 ppm arsenic in the water; levels ranged from 1.0 to 20.0 ppm during the four-month period prior. Scale annuli counts and prior water analyses indicated that these fish had been exposed for a lifetime. Neutron activation data showed that Lepomis cyanellus (green sunfish) had accumulated from 6.1 to 64.2 ppm arsenic in the liver, which is the major detoxification organ in arsenic poisoning. Examination of livers for ultrastructural changes revealed the presence of electron dense bodies and large numbers of autophagic vacuoles (AV) and necrotic bodies (NB) (1), as previously observed in this same species following laboratory exposures to sodium arsenate (2). In addition, abnormal lysosomes (AL), necrotic areas (NA), proliferated rough endoplasmic reticulum (RER), and fibrous bodies (FB) were observed. In order to assess whether the extent of these cellular changes was related to the concentration of arsenic in the liver, stereological measurements of the volume and surface densities of changes were compared with levels of arsenic in the livers of fish from both Municipal Lake and an area known to contain no detectable level of arsenic.

Channel characteristics in the LED traffic lights to vehicles communications

2014 ◽  
Author(s):  
Jinguo Quan ◽  
Weihao Liu ◽  
Shuang Jin ◽  
Yan Zhang
Keyword(s):  
Traffic Lights ◽  
Channel Characteristics

FPGA Based Vehicle to Vehicle Communication in Spartan 3E

2020 ◽  
Vol 8 ◽  
pp. 14-21
Author(s):  
Surya Man Koju ◽  
Nikil Thapa
Keyword(s):  
Signal Processing ◽  
Autonomous Vehicle ◽  
Processing Unit ◽  
Warning Signals ◽  
Vehicle Communication ◽  
Digital Vlsi ◽  
Vehicle To Vehicle ◽  
Vehicle Operation ◽  
Vehicle Technology ◽  
The Voice

This paper presents economic and reconfigurable RF based wireless communication at 2.4 GHz between two vehicles. It implements digital VLSI using two Spartan 3E FPGAs, where one vehicle receives the information of another vehicle and shares its own information to another vehicle. The information includes vehicle’s speed, location, heading and its operation, such as braking status and turning status. It implements autonomous vehicle technology. In this work, FPGA is used as central signal processing unit which is interfaced with two microcontrollers (ATmega328P). Microcontroller-1 is interfaced with compass module, GPS module, DF Player mini and nRF24L01 module. This microcontroller determines the relative position and the relative heading as seen from one vehicle to another. Microcontroller-2 is used to measure the speed of vehicle digitally. The resulting data from these microcontrollers are transmitted separately and serially through UART interface to FPGA. At FPGA, different signal processing such as speed comparison, turn comparison, distance range measurement and vehicle operation processing, are carried out to generate the voice announcement command, warning signals, event signals, and such outputs are utilized to warn drivers about potential accidents and prevent crashes before event happens.

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