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SONATA

SONATA: an approach to make data sound better

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Telecommunications must transport data at an ever-faster pace to meet the needs of current technologies. But this data can be voluminous and difficult to transport at times. Communication channels are congested and transmission limits are reached quickly. Marios Kountouris, a telecommunications researcher at EURECOM, has recently received ERC funding to launch his SONATA project. It aims to shift the paradigm for processing information to speed up its transmission and make future networks more efficient.

“We are close to the fundamental limit for transmitting data, from one point to another,” explains Marios Kountouris, a telecommunications researcher at EURECOM. Most of the current research in this discipline focuses on how to organize complex networks and on improving the algorithms that optimize these networks. Few projects, however, focus on improving the transfer of data between transmitters and receivers. This is precisely the focus of Marios Kountouris’ SONATA project, funded by a European ERC consolidator grant.

“Telecommunications are generally based on Shannon’s information theory, which was established in the 1950s,” says the researcher. In this theory, a transmitter simply sends information through a transmission channel, which models it and transfers it to a receiver which then reconstructs it. The main obstacle to get around is the noise accompanying the signal when it passes through the transmission channel. This constraint can be overcome by algorithm-based signal processing and by increasing throughput. “This usually takes place in the same way, regardless of the message being transmitted. Back in the early days, and until recently, this was the right approach,” says the researcher.

Read more on I’MTech: Claude Shannon, a legacy transcending digital technology

Transmission speed for real-time communication

Today, there is an increasing amount of communication between machines that reason in milliseconds. “Certain messages must be transmitted quickly or they’re useless,” says Marios Kountouris. For example, in the development of autonomous cars, if the message collected relates to the detection of a pedestrian on the road so as to make the vehicle brake, it is only useful for a very short period of time. “This is what we call the age, or freshness of information, which is a very important parameter in some cases,” explains Marios Kountouris.

Yet, most transmission and reconstruction is slowed down by surplus information accompanying the message. In the previous example, if the system for detecting pedestrians is a camera that captures images with details about all the surrounding objects, a great deal of the information in the transmission and processing will not contribute to the system’s purpose. For the researcher, “the sampling, transmission and reconstruction of the message must no longer be carried out independently of another. If excess, redundant or useless data accompanies this process, there can be communication bottlenecks and security problems.”  

The semantics of messages

For real-time communication, the semantics of the message  — its meaning and usefulness— take on particular importance. Semantics make it possible to take into account the attributes of the message and adjust the format of its transmission depending on its purpose. For example, if a temperature sensor is meant to activate the heating system automatically when the room temperature is below 18° C, the attribute of the transmitted message is simply a binary breakdown of temperature: above or below 18°C.

Through the SONATA project, Marios Kountouris seeks to develop a new communication paradigm that takes the semantic value of information into account. This would make it possible to synchronize different types of information collected at the same time through various samples and make more optimal decisions. It would also significantly reduce the volume of transported data as well as the associated energy and resources required.

“The success of this project depends on establishing semantic metrics that are concrete, informative and traceable,” explains the researcher. Establishing the semantics of a message means preprocessing sampling by the transmitter depending on how it is used by the receiver. The aim is therefore to identify the most important, meaningful or useful information in order to determine the qualifying attributes of the message. “Various semantic attributes can be taken into account to obtain a conformal representation of the information, but they must be determined in advance, and we have to be careful not to implement too many attributes at once,” he says.

The goal, then, is to build communication networks with key stages for processing the semantics associated with information. First, semantic filters must be used to avoid unnecessary redundancy when collecting information. Then, semantic preprocessing must be carried out in order to associate the data with its purposes. Signal reconstruction by the receiver would also be adapted to its purposes. All this would be semantically-controlled, making it possible to orchestrate the information collected in an agile way and reuse it efficiently, which is especially important when networks become more complex.

This is a new approach from a structural perspective and would help create links between communication theory, sampling and optimal decision-making. ERC consolidator grants fund high-risk, high-reward projects that aim to revolutionize a field, which is why SONATA has received this funding. “The sonata was the most sophisticated form of classical music and was pivotal to its development. I hope that SONATA will be a major step forward in telecommunications optimization,” concludes Marios Kountouris.

By Antonin Counillon

David Gesbert, PERFUME

PERFUME: a scent of cooperation for the networks of the future

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The ERC PERFUME project, led by EURECOM researcher David Gesbert and ending in 2020, resulted in the development of algorithms for local decision making in the mobile network. This research was tested on autonomous drones, and is particularly relevant to the need for connected robotics in the post-5G world.

Now that 5G is here, who’s thinking about what comes next? The team working with David Gesbert, a researcher specializing in wireless communication systems at EURECOM, has just completed its ERC PERFUME project on this subject. So what will wireless networks look like by 2030? While 5G is based on the centralization of calculations in the cloud, the networks of the future will require, on the contrary, a distributed network. By this, we mean the emergence of a more cooperative network. “In the future, the widespread use of robotic objects and devices to perform autonomous tasks will increase the need for local decision making, which is difficult in a centralized system,” says Gesbert. Nevertheless, the objective remains the same: optimizing the quality of the network. This is especially important since the increase in connected devices may cause more interference and therefore affect the quality of the information exchanged.

Why decentralize decision making on the network?

Under 5G, every device that is connected to the network can send measurements to the cloud. The cloud has a very high computing capacity, enabling it to process an immeasurable amount of data, before sending instructions back to devices (a tablet, cell phone, drone, etc.). However, these information transfers take time, which is a very valuable commodity for connected robotics applications or critical missions. Autonomous vehicles, for example, must make instant decisions in critical situations. “In the context of real-time applications, the response speed of the network must be optimized. Decentralizing decisions closer to the base stations is precisely the solution that was studied in our PERFUME project,” explains David Gesbert. As 5G is not yet equipped to meet this constraint, we have to introduce new evolutions of the standard.

EURECOM’s researchers are thus relying on cooperation and coordination of the computing capabilities of local terminals such as our cell phones. By exchanging information, these terminals could coordinate in the choice of their power and transmission frequency, which would limit the interference that would limit the flow rates, for example. They would no longer focus solely on their local operations, but would participate in the overall improvement of the quality of the network. A team effort that would manifest itself at the user level by sending files faster or providing better image quality during a video call. However, although possible, this collaboration remains difficult to implement.

Towards more cooperative wireless networks

Distributed networks pose a major problem: access to information from one device to another is incomplete. “Our problem of exchanging information locally can be compared to a soccer team playing blindfolded. Each player only has access to a noisy piece of information and doesn’t know where the other team members are in their attempt to score the goal together”, says David Gesbert. Researchers then develop so-called robust decision-making algorithms. Their objective? To allow a set of connected devices to process this noisy information locally. “Networks have become too complicated to be optimized by conventional mathematical solutions, and they are teeming with data. This is why we have designed algorithms based on signal processing but also on machine learning,” continues the researcher.

These tools were then tested in a concrete 5G network context in partnership with Ericsson. “The objective was for 5G cells to coordinate on the choice of directional beams of MIMO (multi-input multi-output) antennas to reduce interference between them,” says the researcher. These smart antennas, deployed as part of 5G, are increasingly being installed on connected devices. They perform “beamforming”, which means that they direct a radio signal in a specific direction – rather than in all directions – thus improving the efficiency of the signal. These promising results have opened the door to large-scale tests on connected robotics applications, the other major focus of the ERC project. EURECOM has thus experimented with certain algorithms on autonomous drones.

Drones at the service of the network?

Following a disaster such as an avalanche, a tsunami or an earthquake, part of the ground network infrastructure may be destroyed and access to the network may be cut off. It would then be possible to replicate a temporary network architecture on site using a fleet of drones serving as air relays. On the EURECOM campus, David Gesbert’s team has developed prototypes of autonomous drones connected to 5G. These determine a strategic flight position and their respective positions in order to solve network access problems for users on the ground. The drones then move freely and recalculate their optimal placement according to the user’s position.  This research notably received the prize for the best 2019 research project, awarded by the Provence-Alpes-Côte d’Azur region’s Secure Communicating Solutions cluster.

This solution could be considered in the context of rescue missions and geolocalization of missing persons. However, several challenges need to be addressed for this method to develop. Indeed, current regulations prohibit the theft of autonomous aircraft. In addition, they have a flight time of about 30 minutes, which is still too short to offer sustainable solutions.

“This research is also adapted to issues relating to autonomous cars, adds David Gesbert. For example, when two vehicles arrive at an intersection, a protocol for coordination must be put in place to ensure that the vehicles cross the intersection as quickly as possible and with the lowest likelihood of collision.” In addition, medicine and connected factories would also be targets for application of distributed networks. As for the integration of this type of standard in the future 6G, it will depend on the interests of industrial players in the years to come.

By Anaïs Culot

Learn more about the ERC PERFUME project