Scheduling and Control of Mobile Communications Networks with Randomly Time Varying Channels by Stability Methods

2006 ◽  
Author(s):  
Harold J. Kushner
Keyword(s):  
Mobile Communications ◽  
Time Varying ◽  
Communications Networks ◽  
And Control ◽  
Time Varying Channels

scholarly journals Sensors and Communication Simulation for Unmanned Traffic Management

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 927
Author(s):  
David Carramiñana ◽  
Iván Campaña ◽  
Luca Bergesio ◽  
Ana M. Bernardos ◽  
Juan A. Besada
Keyword(s):  
Mobile Communications ◽  
Traffic Management ◽  
System Level ◽  
Service Architecture ◽  
Surveillance Network ◽  
Communications Networks ◽  
Agent Based ◽  
Definition Of ◽  
And Control ◽  
Information Streams

Unmanned traffic management (UTM) systems will become a key enabler to the future drone market ecosystem, enabling the safe concurrent operation of both manned and unmanned aircrafts. Currently, these systems are usually tested by performing real scenarios that are costly, limited, hardly scalable, and poorly repeatable. As a solution, in this paper we propose an agent-based simulation platform, implemented through a micro service architecture, which may simulate UTM information sources, such as flight plans, telemetry messages, or tracks from a surveillance network. The final objective of this simulator is to use these information streams to perform a system-level evaluation of UTM systems both in the pre-flight and in-flight stages. The proposed platform, with a focus on simulation of communications and sensors, allows to model UTM actors’ behaviors and their interactions. In addition, it also considers the manual definition of events to simulate unexpected behaviors/events (contingencies), such as communications failures or pilots’ actions. In order to validate our architecture, we implemented a simulator that considers the following actors: drones, pilots, ground control stations, surveillance networks, and communications networks. This platform enables the simulation of the drone trajectory and control, the C2 (command and control) link, drone detection by surveillance sensors, and the communication of all agents by means of a mobile communications network. Our results show that it is possible to truthfully recreate complex scenarios using this simulator, mitigating the disadvantages of real testbeds.

Fragmental weight-conservation combining scheme for statistical signal transmissions under fast time-varying channels

2020 ◽  
Vol 17 (1) ◽  
pp. 118-128
Author(s):  
Xingwei Wang ◽  
Ting Zhou ◽  
Tianheng Xu ◽  
Songlin Feng ◽  
Honglin Hu ◽  
...  
Keyword(s):  
Fast Time ◽  
Time Varying ◽  
Time Varying Channels

Robustness Over Time-Varying Channels in DNN-HMM ASR Based Human-Robot Interaction

2017 ◽  
Author(s):  
José Novoa ◽  
Jorge Wuth ◽  
Juan Pablo Escudero ◽  
Josué Fredes ◽  
Rodrigo Mahu ◽  
...  
Keyword(s):  
Human Robot Interaction ◽  
Time Varying ◽  
Robot Interaction ◽  
Time Varying Channels ◽  
Over Time
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