Enhancing communication efficiency for drones and IoT

The Internet of Things (IoT) is a system in which data is transferred between physical objects, with smart IoT devices continuing to appear in smart homes, medical devices and urban infrastructure. At the same time, the workload also increases, making it necessary to provide a reliable and fast connection for these devices and to create new protocols and connection schemes.

Now, mathematicians from RUDN University, together with colleagues from Egypt and Saudi Arabia, have proposed a solution — to use LiFi technology for the Internet of Things. This is a method of transmitting data using visible light, in which LEDs act as a ‘router’. The research findings were published in the journal Electronics. The researchers from RUDN University have also proposed a way to calculate the probability of a connection break and how to improve the reliability of the 5G/6G connection for drones. These research findings were published in Sensors.

Ammar Muthanna, PhD, Junior Researcher at RUDN University, said that the Internet of Things has become widespread, from automated cars and wearable devices to smart homes and cities, with connectivity now a vital component of IoT. “We have developed a network using LiFi. It provides dense deployment, increases the reliability and availability of the connection, and also reduces delays,” Muthanna said.

The researchers have proposed a new scheme for deploying IoT; unlike the traditional scheme, it has two additional layers between the router and the end device. The first layer is distributed edge computing. These are ‘clouds’ that are not located on a remote server, but next to the end user. The second layer is LiFi. To test the new circuit, mathematicians conducted a simulation experiment. The test model included 12 LiFi access points and 30 end devices, with all of them located in an area measuring 16 by 12 metres. The devices had to perform a total of 100 heterogeneous tasks, which corresponded to real applications. Compared to a conventional network when WiFi is used, the new scheme reduced the time taken to establish the connection by 48%. Resources were used 14% more and productivity increased by 67%.

“The introduction of LiFi allows you to provide an Internet of Things network. The proposed network is based on real applications. The two-tier model of edge computing improves system availability by more than 1.5 times compared to the traditional structure. At the same time, the connection costs are approximately two times lower,” Muthanna said.

Unmanned aerial vehicles (UAVs) were originally used for military purposes, but their scope has since widened. They are now used for rescue operations or emergency management and can also perform the function of repeaters. UAVs must therefore transmit a large amount of information quickly and efficiently. The next generation networks — 5G and 6G — can satisfy such a request. They work on New Radio technology with a wavelength of millimetre range. However, such waves have a drawback — any object can be an obstacle for them and break the connection.

Vyacheslav Begishev, PhD and Associate Professor at RUDN University, said that UAVs are expected to use 5G/6G networks, with the new NR technology operating in the millimetre frequency range to support services such as video surveillance. However, Begishev notes that buildings can get in the way of direct connection between base stations and UAVs, leading to connection failures.

To address the issue, mathematicians at RUDN University calculated the probability of blockage by an obstacle. It was possible to express it through the parameters of the deployed system — the width of the streets, the height of the stations and the height of the UAV flight. The mathematicians conducted numerical experiments and found out which parameter affects the reliability of the connection more than others and how it can be improved.

One possible way to reduce the probability of a break is to place base stations on the roofs of buildings, with the mathematicians showing that the station located on the roof is approximately equal in efficiency to 6–12 ground stations. The exact estimate will be different for each system depending on the given parameters. Most of all, the probability of a drop was affected by the width of the street. For example, a width of 20 metres reduced the likelihood of blockage by 50% compared to a width of 10 metres, all other things being equal.

“We foresee two areas of application of the proposed model. The first concerns cases where it is necessary to use simple models to determine the probability of blocking. In addition, the model can be used to estimate the required base station density for a given blocking probability. Moreover, the accuracy of the model increases with an increase in the deployment area. That is, it can be applied to large urban areas,” said Konstantin Samuilov, Doctor of Science in Technical Sciences, Director of the Institute of Applied Mathematics and Telecommunications at RUDN University.

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