A survey on vehicle-to-vehicle propagation channels

By Andreas F. Molisch, Fredrik Tufvesson, Johan Karedal, Christoph F. Mecklenbräuker. IEEE wireless communications, 2009

449 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/bc8072a3ef7b6fc6ca4fda3a3b89d98db9c77b96

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In Electrical and Electronic Engineering

Citations in the corpus

Challenges Toward Wireless Communications for High-Speed Railway (2014, background): “It is randomly time varying: its identifiability from the measurements, the statistical characterization, and the modeling is rather challenging [80], [81].”
Path Loss Modeling for Vehicle-to-Vehicle Communications (2011, background): “However, as recently pointed out in [ 10 ], there is still a lack of results regarding many important channel parameters.”
A Vision of C-V2X: Technologies, Field Testing, and Challenges With Chinese Development (2020, background): “Accordingly, the radio channel of vehicular networks generally has the following special characteristics [28, 29, 30, 31]: large and time-varying Doppler shifts, deep fading (i.e., presence of “worse than Rayleigh” fading in a significant percentage of cases), as well as the non-stationarity…”
A Survey of 5G Channel Measurements and Models (2018, background): “Because of the unique propagation conditions, V2V channels exhibit very different propagation characteristics compared to the cellular communication channels [16].”
Infotainment and road safety service support in vehicular networking : From a communication perspective $ (2010, background): “Due to high mobility of vehicles, communication channels are susceptible to fast fading, whereby reliable links cannot be guaranteed [98].”
Federated Learning in Vehicular Edge Computing: A Selective Model Aggregation Approach (2020, background): “But the lower and upper bounds are different in urban, suburban, and highway [29].”