A pre-existing 4G network infrastructure could help drivers make safe decisions in or near accidents.

An important factor in vehicle-related accidents is the lack of information and if drivers are aware of their surroundings and road conditions, more accidents could end up avoided.

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On top of that, as driverless cars begin to gain momentum, improvements will be needed to ensure vehicles receive the correct information.

A key question is how high-quality data can end up shared by an Intelligent Transportation System (ITS) to help drivers in emergency situations.

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That is where research conducted by the University of Bristol Communication Systems & Networks (CSN) Group, in collaboration with the Université Blaise Pascal in France, comes into play.

The research suggests a cost-effective solution to this problem is for city-owned base stations to form a single frequency network (SFN) that can enable drivers to have the information they need to make safe decisions in or near accidents.

In order to ensure transmissions are reliable, tight bounds on the outage probability would need to develop when the SFN ends up overlaid on an existing cellular network.

The researchers also discuss an extremely efficient transmission power allocation algorithm that, for the situations outlined, can reduce the total immediate SFN transmission power by up to 20 times compared to a static uniform power allocation solution. That would be important when base stations rely on an off-grid power source, such as batteries.

“Obtaining high-quality sensor information is critical in vehicle emergencies,” said Dr. Andrea Tassi, senior research associate in wireless connectivity for autonomous vehicles from the Department of Electrical and Electronic Engineering and CSN Group, which led the research. “We have shown that our proposed power allocation model can help to significantly reduce the transmission power of the proposed network while target signal-to-noise and interference ratio (SINR) outage constraints are met. With cars receiving reliable information, our research could improve road safety in future intelligent transportation systems.”

The University’s CSN Group is part of the Innovate UK-funded projects, VENTURER and FLOURISH, and is playing a leading role in connectivity for automotive applications.

A paper on the subject won the “Best Paper Award” at the international conference Signal Processing, Telecommunications & Computing (SigTelCom) 2017, supported by IEEE, Newton Fund and British Council.

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