This research focuses on ultra-reliable low-latency Vehicle-to-Anything (V2X) communications. We envision a system architecture and processing algorithms for the alignment of highly collimated V2X beams based either on millimeter-Wave (mmW) or Free-Space Optics (FSO). A sensor aided beam tracking strategy based on distributed processing of sensor data is used to counteract the detrimental effect of dynamics, guaranteeing a seamless communication. Sensor data are mutually exchanged among vehicles to estimate their kinematics, increasing the self-situational awareness and providing a geometrical description of the line-of-sight link between transceivers. Highly directional mmW and/or FSO communications are shown to be promising candidates for multiGbps V2X communications even in high mobility scenarios if supported by an adequate architecture and advanced processing techniques.

Cooperative beam tracking by multi-sensor data fusion in V2X networks

M. Brambilla;L. Combi;A. Matera;D. Tagliaferri;M. Nicoli;U. Spagnolini
2019

Abstract

This research focuses on ultra-reliable low-latency Vehicle-to-Anything (V2X) communications. We envision a system architecture and processing algorithms for the alignment of highly collimated V2X beams based either on millimeter-Wave (mmW) or Free-Space Optics (FSO). A sensor aided beam tracking strategy based on distributed processing of sensor data is used to counteract the detrimental effect of dynamics, guaranteeing a seamless communication. Sensor data are mutually exchanged among vehicles to estimate their kinematics, increasing the self-situational awareness and providing a geometrical description of the line-of-sight link between transceivers. Highly directional mmW and/or FSO communications are shown to be promising candidates for multiGbps V2X communications even in high mobility scenarios if supported by an adequate architecture and advanced processing techniques.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/1120326
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