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David Gesbert, winner of the 2021 IMT-Académie des Sciences Grand Prix

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EURECOM researcher David Gesbert is one of the pioneers of Multiple-Input Multiple-Output (MIMO) technology, used nowadays in many wireless communication systems. He contributed to the boom in WiFi, 3G, 4G and 5G technology, and is now exploring what could be the 6G of the future. In recognition of his body of work, Gesbert has received the IMT-Académie des Sciences Grand Prix.

“I’ve always been interested by research in the field of telecommunications. I was fascinated by the fact that mathematical models could be converted into algorithms used to make everyday objects work,” declares David Gesbert, researcher and specialist in wireless telecommunications systems at EURECOM. Since he completed his studies in 1997, Gesbert has been working on MIMO, a telecommunications system that was created in the 1990s. This technology makes it possible to transfer data streams at high speeds, using multiple transmitters and receivers (such as telephones) in conjunction. Instead of using a single channel to send information, a transmitter can use multiple spatial streams at the same time. Data is therefore transferred more quickly to the receiver. This spatialized system represents a breaking point with previous modes of telecommunication, like the Global System for Mobile Communications (GSM).

It has proven to be an important innovation, as MIMO is now broadly used in WiFi systems and several generations of mobile telephone networks, such as 4G and 5G. After receiving his PhD from École Nationale Supérieure des Télécommunications in 1997, Gesbert completed two years of postdoctoral research at Stanford University. He joined the telecommunications laboratory directed by Professor Emeritus Arogyaswami Paulraj, an engineer who worked on the creation of MIMO. In the early 2000s, the two scientists, accompanied by two students, launched the start-up Iospan Wireless. This was where they developed the first high-speed wireless modem using MIMO-OFDM technology.

OFDM: Orthogonal Frequency-Division Multiplexing

OFDM is a process that improves communication quality by dividing a high-debit data stream into many low-debit data streams. By combining this mechanism with MIMO, it is possible to transfer data at high speeds while making the information generated by MIMO more robust against radio distortion. “These features make it great for use in deploying telecommunications systems like 4G or 5G,” adds the researcher.  

In 2001, Gesbert moved to Norway, where he taught for two years as adjunct professor in the IT department at the University of Oslo. One year later, he published an article in which he described that complex propagation environments favor the functioning of MIMO. “This means that the more obstacles there are in a place, the more the waves generated by the antennas are reflected. The waves therefore travel different paths and interference is reduced, which leads to more efficient data transfer. In this way, an urban environment in which there are many buildings, cars, and other objects will be more favorable to MIMO than a deserted area,” explains the telecommunications expert.  

In 2003, he joined EURECOM, where he became a professor and five years later, head of the Mobile Communications department. There, he has continued his work aiming to improve MIMO. His research has shown him that base stations — also known as relay antennas — could be useful to improve the performance of this mechanism. By using antennas from multiple relay stations far apart from each other, it would be possible to make them work together and produce a giant MIMO system. This would help to eliminate interference problems and optimize the circulation of data streams. Research is still being performed at present to make this mechanism usable.

MIMO and robots

In 2015, Gesbert obtained an ERC Advanced Grant for his PERFUME project. The initiative, which takes its name from high PERfomance FUture Mobile nEtworking, is based on the observation that “the number of receivers used by humans and machines is currently rising. Over the next few years, these receivers will be increasingly connected to the network,” emphasizes the researcher. The aim of PERFUME is to exploit the information resources of receivers so that they work in cooperation, to improve their performance. The MIMO principle is at the heart of this project: spatializing information and using multiple channels to transmit data. To achieve this objective, Gesbert and his team developed base stations attached to drones. These prototypes use artificial intelligence systems to communicate between one another, in order to determine which bandwidth to use or where to place themselves to give a user optimal network access. Relay drones can also be used to extend radio range. This could be useful, for example, if someone is lost on a mountain, far from relay antennas, or in areas where a natural disaster has occurred and the network infrastructure has been destroyed.

As part of this project, the EURECOM professor and his team have performed research into decision-making algorithms. This has led them to develop artificial neuron networks to improve decision-making processes performed by the receivers or base stations desired to cooperate together. With these neuron networks, the devices are capable of quantifying and exploiting the information held by each of them. According to Gesbert, “this will allow receivers or stations with more information to correct flaws in receivers with less. This idea is a key takeaway from the PERFUME project, which finished at the end of 2020. It indicates that to cooperate, agents like radio receivers or relay stations make decisions based on sound data, which sometimes has to be rejected to let themselves be guided by decisions from agents with access to better information than them. It is a surprising result, and a little counterintuitive.”

Towards the 6th generation of mobile telecommunications technology

“Nowadays, two major areas are being studied concerning the development of 6G,” announces Gesbert. The first relates to ways of making networks more energy efficient by reducing the number of times that transmissions take place, by restricting the amount of radio waves emitted and reducing interference. One solution to achieve these objectives is to use artificial intelligence. “This would make it possible to optimize resource allocation and use radio waves in the best way possible,” adds the expert.

The second concerns applications of radio waves for purposes other than communicating information. One possible use for the waves would be to produce images. Given that when a wave is transmitted, it reflects off a large number of obstacles, artificial intelligence could analyze its trajectory to identify the position of obstacles and establish a map of the receiver’s physical environment. This could, for example, help self-driving cars determine their environment in a more detailed way. With 5G, the target precision for locating a position is around a meter, but 6G could make it possible to establish centimeter-level precision, which is why these radio imaging techniques could be useful. While this 6th-generation mobile telecommunications network will have to tackle new challenges, such as the energy economy and high-accuracy positioning, it seems clear that communication spatialization and MIMO will continue to play a fundamental role.

Rémy Fauvel

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