2025Activity​​​‌ reportProject-TeamMARACAS

2.1‌ Motivation

In the last‌​‌ decades, telecommunications have improved​​ human connectivity, leading to​​​‌ a seamless worldwide coverage‌ that has become indispensable‌​‌ to human activities. The​​ Internet revolution drew on​​​‌ a robust and efficient‌ multi-layer architecture ensuring end-to-end‌​‌ services. In a classical​​ network architecture, the different​​​‌ protocol layers are compartmentalized‌ and cannot easily interact.‌​‌ For instance, source coding​​ is performed at the​​​‌ application layer while channel‌ coding is performed at‌​‌ the physical (PHY) layer.​​ This multi-layer architecture blocked​​​‌ any attempt to exploit‌ low level cooperation mechanisms‌​‌ such as relaying, phy-layer​​ network coding or joint​​​‌ estimation. In recent years,‌ a major shift, often‌​‌ referred to as the​​ Internet of Things (IoT)​​​‌, was initiated toward‌ a machine-to-machine (M2M) communication‌​‌ paradigm, which is in​​ sharp contrast with classical​​​‌ centralized network architectures. The‌ IoT enables machine-based services‌​‌ exploiting a massive quantity​​ of data virtually spread​​​‌ over a complex, redundant‌ and distributed architecture. New‌​‌ usages have also appeared,​​ such as virtual reality,​​​‌ autonomous vehicles, or the‌ widespread use of machine‌​‌ learning, giving rise to​​ new classes of traffic​​​‌ with specific demands in‌ terms of reliability, latency‌​‌ and throughput. Furthermore, the​​ aforementioned classical network architecture​​​‌ based on a centralized‌ approach are gradually becoming‌​‌ outdated: with the emergence​​ of artificial intellingence (AI)​​​‌ applications often involves the‌ ability for communications network‌​‌ to process data en-route​​, networks are shifting​​​‌ away from the classical‌ “bit-pipe” paradigm to become‌​‌ distributed computing tools.

The​​ era of Internet of​​​‌ Everything deeply modifies the‌ paradigm of communication systems.‌​‌ They have to transmute​​ into reactive and adaptive​​​‌ intelligent systems, under stringent‌ QoS constraints (latency, reliability)‌​‌ where the networking service​​ is intertwined in an​​​‌ information-centric network. The associated‌ challenges are linked to‌​‌ the intimate connections between​​ communication, computation, control and​​​‌ storage. Actors, nodes or‌ agents in a network‌​‌ can be viewed as​​ forming a distributed system​​​‌ of computations—a computing network‌ .

2.2 Scientific methodology‌​‌

It is worth noting​​ that working on these​​​‌ new architectures can be‌ tackled from different perspectives,‌​‌ e.g. data management, protocol​​ design, middleware, algorithmic design...​​​‌ Our main objective in‌ Maracas is to address‌​‌ this problem from a​​​‌ communication theory perspective. Our​ background in communication theory​‌ includes information theory, estimation​​ theory, learning and signal​​​‌ processing. Our strategy relies​ on three fundamental and​‌ complementary research axes:

• Mathematical​​ modeling: information theory is​​​‌ a powerful framework suitable​ to evaluate the limits​‌ of complex systems and​​ relies on probability theory.​​​‌ We will explore new​ bounds for complex networks​‌ (multi-objective optimization, large scale,​​ complex channels,...) in association​​​‌ with other tools (stochastic​ geometry, queuing theory, learning,...)​‌
• Algorithmic design: a number​​ of theoretical results obtained​​​‌ in communication theory, despite​ their high potential are​‌ still far from a​​ practical use. We will​​​‌ thus work on exploiting​ new algorithmic techniques. Back​‌ and forth efforts between​​ theory and practice is​​​‌ necessary to identify the​ most promising opportunities. The​‌ key elements are related​​ to the exploitation of​​​‌ feedbacks, signaling and decentralized​ decisions.
• Machine learning: while​‌ learning approaches are not​​ always competitive against heavily​​​‌ optimized model-based signal processing​ algorithms often found in​‌ communications systems, they can​​ substantially outperform classical architectures​​​‌ in cases where the​ model is not or​‌ imperfectly known, which is​​ often the case when​​​‌ dealing with physical systems​ (electronics, propagation, etc).
• Experimentation​‌ and cross-layer approach: theoretical​​ results and simulation are​​​‌ not enough to provide​ proofs of concept. We​‌ will continue to put​​ efforts on experimental works​​​‌ either on our own​ (e.g. FIT/CorteXlab and SILECS)​‌ or in collaboration with​​ industries (Nokia, Orange, Thalès,...)​​​‌ and other research groups.​

While our expertise is​‌ mostly related to the​​ optimization of wireless networks​​​‌ from a communication perspective,​ the project of Maracas​‌ is to broaden our​​ scope in the context​​​‌ of Computing Networks,​ where a challenging issue​‌ is to optimize jointly​​ architectures and applications, and​​​‌ to break the classical​ network/data processing separation. This​‌ will drive us to​​ change our initial positioning​​​‌ and to really think​ in terms of information-centric​‌ networks following, e.g. 54​​, 52, 64​​​‌.

To summarize, Computing​ Networks can be described​‌ as highly distributed and​​ dynamic systems, where information​​​‌ streams consist in a​ huge number of transient​‌ data flows from a​​ huge number of nodes​​​‌ (sensors, routers, actuators, etc...)​ with computing capabilities at​‌ the nodes. These Computing​​ Networks are nothing but​​​‌ the invisible nonetheless necessary​ skeleton of cloud and​‌ fog-computing based services.

Our​​ research strategy is to​​​‌ describe these Computing Networks​ as complex large scale​‌ systems in an information​​ theory framework, but in​​​‌ association with other tools,​ such as stochastic geometry,​‌ stochastic network calculus, game​​ theory 18 or machine​​​‌ learning.

The multi-user communication​ capability is a central​‌ feature, to be tackled​​ in association with other​​​‌ concepts and to assess​ a large variety of​‌ constraints related to the​​ data (storage, secrecy,...) or​​​‌ related to the network​ (energy, self-healing,...).

The information​‌ theory literature or more​​ generally the communication theory​​​‌ literature is rich of​ appealing techniques dedicated to​‌ efficient multi-user communications: e.g.​​ physical layer network coding,​​​‌ amplify-and-forward, full-duplexing, coded caching​ at the edge, superposition​‌ coding. But despite their​​ promising performance, none of​​ these technologies play a​​​‌ central role in current‌ protocols. The reasons are‌​‌ two-fold : i) these​​ techniques are usually studied​​​‌ in an oversimplified theoretical‌ framework which neglect many‌​‌ practical aspects (feedback, quantization,...),​​ and that is not​​​‌ able to tackle large‌ scale networks and ii)‌​‌ the proposed algorithms are​​ of a high complexity​​​‌ and are not compatible‌ with the classical multi-layer‌​‌ network architecture.

Maracas addresses​​ these questions, leveraging on​​​‌ its past outstanding experience‌ from wireless network design.‌​‌

The aim of Maracas​​ is to push from​​​‌ theory to practice a‌ fully cross-layer design of‌​‌ Computing Networks , based​​ on multi-user communication principles​​​‌ relying mostly on information‌ theory, signal processing, estimation‌​‌ theory, game theory and​​ optimization. We refer to​​​‌ all these tools under‌ the umbrella of communication‌​‌ theory .

As such,​​ the Maracas project goes​​​‌ much beyond wireless networks.‌ The Computing Networks paradigm‌​‌ applies to a wide​​ variety or architectures including​​​‌ wired networks, smart grids,‌ nanotechnology based networks. One‌​‌ Maracas research axis will​​ be devoted to the​​​‌ identification of new research‌ topics or scenarios where‌​‌ our algorithms and mathematical​​ models could be useful.​​​‌

3.1‌ General description

As presented‌​‌ in the first section,​​ Computing Networks is a​​​‌ concept generalizing the study‌ of multi-user systems under‌​‌ the communication perspective. This​​ problematic is partly addressed​​​‌ in the aforementioned references.‌ Optimizing Computing Networks relies‌​‌ on exploiting simultaneously multi-user​​ communication capabilities, in the​​​‌ one hand, and storage‌ and computing resources in‌​‌ the other hand. Such​​ optimization needs to cope​​​‌ with various constraints such‌ as energy efficiency or‌​‌ energy harvesting, delays, reliability​​ or network load.

The​​​‌ notion of reliability (used‌ in MARACAS acronym) is‌​‌ central when considered in​​ the most general sense:​​​‌ ultimately, the reliability of‌ a Computing Network measures‌​‌ its capability to perform​​ its intended role under​​​‌ some confidence interval. Figure‌ 1 represents the most‌​‌ important performance criteria to​​ be considered to achieve​​​‌ reliable communications. These metrics‌ fit with those considered‌​‌ in 5G and beyond​​ technologies 61.

On​​​‌ the theoretical side, multi-user‌ information theory is a‌​‌ keystone element. It is​​ worth noting that classical​​​‌ information theory focuses on‌ the power-bandwith tradeoff usually‌​‌ referred as Energy Efficiency-Spectral​​ Efficiency (EE-SE) tradeoff (green​​​‌ arrow on 1).‌ However, the other constraints‌​‌ can be efficiently introduced​​ by using a non-asymptotic​​​‌ formulation of the fundamental‌ limits 60, 62‌​‌ and in association with​​ other tools devoted to​​​‌ the analysis of random‌ processes (queuing theory, ...).‌​‌

MARACAS aims at studying​​ Computing Networks from a​​​‌ communication point of view,‌ using the foundations of‌​‌ information theory in association​​ with other theoretical tools​​​‌ related to estimation theory‌ and probability theory.

In‌​‌ particular, MARACAS combines techniques​​ from communication and information​​​‌ theory with statistical signal‌ processing, control theory, game‌​‌ theory and machine learning.​​ Wireless networks is the​​​‌ emblematic application for MARACAS,‌ but other scenarios are‌​‌ appealing for us, such​​ as molecular communications, smart​​​‌ grids or smart buildings.‌

Several teams at Inria‌​‌ address computing networks, but​​​‌ working on this problem​ with an emphasis on​‌ communication aspects is unique​​ within Inria.

This figure​​​‌ illustrates the four most​ important metrics allowing to​‌ evaluate wireless communication systems​​

The​‌ complexity of Computing Networks​​ comes first from the​​​‌ high dimensionality of the​ problem: i) thousands of​‌ nodes, each with up​​ to tens setting parameters​​​‌ and ii) tens variable​ objective functions to be​‌ minimized/maximized.

In addition, the​​ necessary decentralization of the​​​‌ decision process, the non​ stationary behavior of the​‌ network itself (mobility, ON/OFF​​ Switching) and of the​​​‌ data flows, and the​ necessary reduction of costly​‌ feedback and signaling (channel​​ estimation, topology discovering, medium​​​‌ access policies...) are additional​ features that increase the​‌ problem complexity.

The original​​ positioning of MARACAS holds​​​‌ in his capability to​ address three complementary challenges​‌ :

1. to develop a​​ sound mathematical framework inspired​​​‌ by information theory.
2. to​ design algorithms, achieving performance​‌ close to these limits.​​
3. to test and validate​​​‌ these algorithms on experimental​ testbeds.

3.2 Research program​‌

This figure illustrates the​​ MARACAS organization around 4​​​‌ research axes

Our​‌ research is organized in​​ 4 research axes:

• Axis​​​‌ 1 - Fundamental Limits​ of Reliable Communication Systems​‌: Information theory is​​ revisited to integrate reliability​​​‌ in the wide sense.​ The non-asymptotic theory which​‌ made progress recently and​​ attracted a lot of​​​‌ interest in the information​ theory community is a​‌ good starting point. But​​ for addressing computing network​​​‌ in a wide sense,​ it is necessary to​‌ go back to the​​ foundation of communication theory​​​‌ and to derive new​ results, e.g. for non​‌ Gaussian channels 6 of​​ for multi-constrained systems 17​​​‌.

  This also means​ revisiting the fundamental estimation-detection​‌ problem 63 in a​​ general multi-criteria, multi-user framework​​​‌ to derive tractable and​ meaningful bounds.

  As mentioned​‌ in the introduction, Computing​​ Networks also relies on​​​‌ a data-centric vision, where​ transmission, storage and processing​‌ are jointly optimized. The​​ strategy of caching at​​​‌ the edge51 proposed​ for cellular networks shows​‌ the high potential of​​ considering simultaneously data and​​​‌ network properties. MARACAS is​ willing to extend his​‌ skills on source coding​​ aspects to tackle with​​​‌ a data-oriented modeling of​ Computing Networks.

• Axis​‌ 2 - Algorithms and​​ protocols: Our second​​​‌ objective is to elaborate​ new algorithms and protocols​‌ able to achieve or​​ at least to approach​​​‌ the aforementioned fundamental limits.​ While the exploration of​‌ fundamental limits is helpful​​ to determine the most​​​‌ promising strategies (e.g. relaying,​ cooperation, interference alignment) to​‌ increase system performance, the​​ transformation of these degrees​​​‌ of freedom into real​ protocols is a non​‌ trivial issue. One reason​​ is the exponentially growing​​​‌ complexity of multi-user communication​ strategies, with the number​‌ of users, due to​​ the necessity of some​​​‌ coordination, feedback and signaling.​ The general problem is​‌ a decentralized and dynamic​​ multi-agents multi-criteria optimization problem​​​‌ and the general formulation​ is a non-linear and​‌ non-convex large scale problem.​​

  The conventional research direction​​ aims at reducing the​​​‌ complexity by relaxing some‌ constraints or by reducing‌​‌ the number of degrees​​ of freedom. For instance,​​​‌ topology interference management is‌ a seducing model used‌​‌ to reduce feedback needs​​ in decentralized wireless networks​​​‌ leading to original and‌ efficient algorithms 66,‌​‌ 53.

  Another emerging​​ research direction relies on​​​‌ using machine learning techniques‌ 47 as a natural‌​‌ evolution of cognitive radio​​ based approaches. Machine learning​​​‌ in the wide sense‌ is not new in‌​‌ radio networks, but the​​ most important works in​​​‌ the past were devoted‌ to reinforcement learning approaches.‌​‌ The use of deep​​ learning (DL) is much​​​‌ more recent, with two‌ important issues : i)‌​‌ identifying the right problems​​ that really need DL​​​‌ algorithms and ii) providing‌ extensive data sets from‌​‌ simulation and real experiments.​​ Our group started to​​​‌ work on this topic‌ in association with Nokia‌​‌ in the joint research​​ lab. As we are​​​‌ not currently expert in‌ deep learning, our primary‌​‌ objective is to identify​​ the strategic problems and​​​‌ to collaborate in the‌ future with Inria experts‌​‌ in DL, and in​​ the long term to​​​‌ contribute not only to‌ the application of these‌​‌ techniques, but also to​​ improve their design according​​​‌ to the constraints of‌ computing networks.

• Axis 3‌​‌ - Experimental validation :​​ With the rapid evolution​​​‌ of network technologies, and‌ their increasing complexity, experimental‌​‌ validation is necessary for​​ two reasons: to get​​​‌ data, and to validate‌ new algorithms on real‌​‌ systems.

  MARACAS activity leverages​​ on the FIT/CorteXlab platform​​​‌ (http://www.cortexlab.fr/), and‌ our strong partnerships with‌​‌ leading industry including Nokia​​ Bell Labs, Orange labs,​​​‌ Sigfox or Sequans. Beyond‌ the platform itself which‌​‌ offers a worldwide unique​​ and remotely accessible testbed​​​‌ , MARACAS also develops‌ original experimentations exploiting the‌​‌ reproducibility, the remote accessibility,​​ and the deployment facilities​​​‌ to produce original results‌ at the interface of‌​‌ academic and industrial research​​ 2, 8.​​​‌ FIT/CorteXlab uses the GNU‌ Radio environment to evaluate‌​‌ new multi-user communication systems.​​

  Our experimental work is​​​‌ developed in collaboration with‌ other Inria teams especially‌​‌ in the Rhone-Alpes centre​​ but also in the​​​‌ context of the future‌ SILECS project which will‌​‌ implement the convergence between​​ FIT and Grid'5000 infrastructures​​​‌ in France, in cooperation‌ with European partners and‌​‌ infrastructures. SILECS is a​​ unique framework which will​​​‌ allow us to test‌ our algorithms, to generate‌​‌ data, as required to​​ develop a data-centric approach​​​‌ for computing networks.

  Last‌ but not least, software‌​‌ radio technologies are leaving​​ the confidentiality of research​​​‌ laboratories and are made‌ available to a wide‌​‌ public market with cheap​​ (few euros) programmable equipment,​​​‌ allowing to setup non‌ standard radio systems. The‌​‌ existence of home-made and​​ non official radio systems​​​‌ with legacy ones could‌ prejudice the deployment of‌​‌ Internet of things. Developing​​ efficient algorithms able to​​​‌ detect, analyse and control‌ the spectrum usage is‌​‌ an important issue. Our​​ research on FIT/CorteXlab will​​​‌ contribute to this know-how.‌

• Axis 4 - Other‌​‌ application fields : Even​​​‌ if the wireless network​ context is still challenging​‌ and provides interesting problems,​​ MARACAS targets to broaden​​​‌ its exploratory playground from​ an application perspective. We​‌ are looking for new​​ communication systems, or simply​​​‌ other multi-user decentralized systems,​ for which the theory​‌ developed in the context​​ of wireless networks can​​​‌ be useful. Basically, MARACAS​ might address any problem​‌ where multi-agents are trying​​ to optimize their common​​​‌ behavior and where the​ communication performance is critical​‌ (e.g. vehicular communications, multi-robots​​ systems, cyberphysical systems). Following​​​‌ this objective, we already​ studied the problem of​‌ missing data recovery in​​ smart grids 10 and​​​‌ the original paradigm of​ molecular communications 5.​‌

  Of course, the objective​​ of this axis is​​​‌ not to address random​ topics but to exploit​‌ our scientific background on​​ new problems, in collaboration​​​‌ with other academic teams​ or industry. This is​‌ a winning strategy to​​ develop new partnerships, in​​​‌ collaboration with other Inria​ teams.

4.1 5G, 6G, and​​ beyond

The fifth generation​​​‌ (5G) broadens the usage​ of cellular networks but​‌ requires new features, typically​​ very high rates, high​​​‌ reliability, ultra low latency,​ for immersive applications, tactile​‌ internet, M2M communications.

From​​ the technical side, new​​​‌ elements such as millimeter​ waves, massive MIMO, massive​‌ access are under evaluation.​​ The initial 5G standard​​​‌ finalized in 2019, is​ finally not really disruptive​‌ with respect to the​​ 4G and the clear​​​‌ breakthrough is not there​ yet. The ideal network​‌ architecture for billions of​​ devices in the general​​​‌ context of Internet of​ Things, is not well​‌ established and the debate​​ still exists between several​​​‌ proposals such as NB-IoT,​ Sigfox, Lora. We are​‌ developing a deep understanding​​ of these techniques, in​​​‌ collaboration with major actors​ (Orange Labs, Nokia Bell​‌ Labs, Sequans, Sigfox) and​​ we want to be​​​‌ able to evaluate, to​ compare and to propose​‌ evolutions of these standards​​ with an independent point​​​‌ of view.

This is​ why we are interested​‌ in developing partnerships with​​ major industries, access providers​​​‌ but also with service​ providers to position our​‌ research in a joint​​ optimization of the network​​​‌ infrastructure and the data​ services, from a theoretical​‌ perspective as well as​​ from experimentation.

4.2 Energy​​​‌ sustainability

The energy footprint​ and from a more​‌ general perspective, the sustainability​​ of wireless cellular networks​​​‌ and wireless connectivity is​ somehow questionable.

We develop​‌ our models and analysis​​ with a careful consideration​​​‌ of the energy footprint​ : sleeping modes, power​‌ adaptation, interference reduction, energy​​ gathering, ... many techniques​​​‌ can be optimized to​ reduce the energetic impact​‌ of wireless connectivity. In​​ a computing networks approach,​​​‌ considering simultaneously transmission, storage​ and computation constraints may​‌ help to reduce drastically​​ the overall energy footprint.​​​‌

4.3 Smart building, smart​ cities, smart environments

Smart​‌ environments rely on the​​ deployment of many sensors​​​‌ and actuators allowing to​ create interactions between the​‌ twinned virtual and real​​ worlds. These smart environments​​​‌ (e.g. smart building) are​ for us an ideal​‌ playground to develop new​​ models based on information​​ theory and estimation theory​​​‌ to optimize the network‌ architecture including storage, transmission,‌​‌ computation at the right​​ place.

Our work can​​​‌ be seen as the‌ invisible side of cloud/edge‌​‌ computing. In collaboration with​​ other teams expert in​​​‌ distributed computing or middleware‌ (typically at CITI lab,‌​‌ with the Dynamid team​​ of Frédéric Le Mouel)​​​‌ and in the framework‌ of the chaire SPIE/ICS-INSA‌​‌ Lyon, we want to​​ optimize the mechanisms associated​​​‌ to these technologies :‌ in a multi-constrained approach,‌​‌ we want to design​​ new distributed algorithms appropriate​​​‌ for large scale smart‌ environments.

From a larger‌​‌ perspective we are interested​​ on various applications where​​​‌ the communication aspects play‌ an important role in‌​‌ multi-agent systems and target​​ to process large sets​​​‌ of data. Our contribution‌ to the development of‌​‌ TousAntiCovid falls into this​​ area.

4.4 Machine learning​​​‌ based radio

During the‌ first 6G wireless meeting‌​‌ which was held in​​ Lapland, Finland in March​​​‌ 2019, machine learning (ML)‌ was clearly identified as‌​‌ one of the most​​ promising breakthroughs for future​​​‌ 6G wireless systems expected‌ to be in use‌​‌ around 2030 (SNS​​ 6G IA Horizon Europe​​​‌). The research community‌ is entirely leveraging the‌​‌ international ML tsunami. We​​ strongly believe that the​​​‌ paradigm of wireless networks‌ is moving toward to‌​‌ a new era. Our​​ view is supported by​​​‌ the fact that artificial‌ Intelligence (AI) in wireless‌​‌ communications is not new​​ at all. The telecommunications​​​‌ industry has been seeking‌ for 20 years to‌​‌ reduce the operational complexity​​ of communication networks in​​​‌ order to simplify constraints‌ and to reduce costs‌​‌ on deployments. This obviously​​ relies on data-driven techniques​​​‌ allowing the network to‌ self-tune its own parameters.‌​‌ Over the successive 3GPP​​ standard releases, more and​​​‌ more sophisticated network control‌ has been introduced. This‌​‌ has supported increasing flexibility​​ and further self-optimization capabilities​​​‌ for radio resource management‌ (RRM) as well as‌​‌ for network parameters optimization.​​

We target the following​​​‌ key elements :

• Obtaining‌ data from experimental scenarios,‌​‌ at the lowest level​​ (baseband I/Q signals) in​​​‌ multi-user scenarios (based upon‌ FIT/CorteXlab).
• Developing a‌​‌ framework and algorithms for​​ deep learning based radio.​​​‌
• Developing new reinforcement learning‌ techniques in high dimensional‌​‌ state-action spaces.
• Developing self-supervised​​ learning methods for statistical​​​‌ processing of long-term propagation‌ data (channel state information).‌​‌
• Embedding NN structures on​​ radio devices (FPGA or​​​‌ m-controllers) and in FIT/CorteXlab.‌
• Evaluating the gap between‌​‌ these algorithms and fundamental​​ limits from information theory.​​​‌
• Building an application scenario‌ in a smart environment‌​‌ to experiment a fully​​ cross-layer design (e.g. within​​​‌ a smart-building context, how‌ could a set of‌​‌ object could learn their​​ protocols efficiently ?).

4.5​​​‌ Molecular communications

Many communication‌ mechanisms are based on‌​‌ acoustic or electromagnetic propagation;​​ however, the general theory​​​‌ of communication is much‌ more widely applicable. One‌​‌ recent proposal is molecular​​ communication, where information is​​​‌ encoded in the type,‌ quantity, or time or‌​‌ release of molecules. This​​ perspective has interesting implications​​​‌ for the understanding of‌ biochemical processes and also‌​‌ chemical-based communication where other​​​‌ signaling schemes are not​ easy to use (e.g.,​‌ in mines). Our work​​ in this area focuses​​​‌ on two aspects: (i)​ the fundamental limits of​‌ communication (i.e., how much​​ data can be transmitted​​​‌ within a given period​ of time); and (ii)​‌ signal processing strategies which​​ can be implemented by​​​‌ circuits built from chemical​ reaction-diffusion systems.

A novel​‌ perspective introduced within our​​ work is the incorporation​​​‌ of coexistence constraints. That​ is, we consider molecular​‌ communication in a crowded​​ biochemical environment where communication​​​‌ should not impact pre-existing​ behavior of the environment.​‌ This has lead to​​ new connections with communication​​​‌ subject to security constraints​ as well as the​‌ stability theory of stochastic​​ chemical reaction-diffusion systems and​​​‌ systems of partial differential​ equations which provide deterministic​‌ approximations.

5.1 Footprint​​​‌ of research activities

Considering​ our research activities, most​‌ of our works are​​ based on theoretical works​​​‌ or simulations. We may​ be concerned with the​‌ following aspects:

• Experimental works:​​ to reduce the energy​​​‌ footprint of CorteXlab, all​ equipments are connected on​‌ Electronic Power Switches (EPS)​​ with remote access. These​​​‌ equipments can be turned​ on only when an​‌ experiment is underway.
• Computer​​ sustainability: we generally use​​​‌ computers for at least​ 5 years, and require​‌ extended warranty contracts (5​​ to 7 years) at​​​‌ the time of purchase.​
• Travelling represents an important​‌ part of our ${\mathrm{CO}}_2$ footprint. We strive​​​‌ to avoid frequent long-distance​ trips and encouraging extended​‌ stays including multiple research​​ interactions in the same​​​‌ geographical area during trips​ involving long flights.

5.2​‌ Impact of research results​​

We strive to design​​​‌ high-rate, high-QoS wireless protocols​ under stringent energy consumption​‌ contraints. Our research area​​ includes solutions allowing to​​​‌ remove batteries from certain​ devices (zero-energy devices), as​‌ well as energy-efficient approaches​​ which can potentially reduce​​​‌ the ${\mathrm{CO}}_2$ footprint​ of future networks. However​‌ we acknowledge that the​​ problem of energy consumption​​​‌ of communication networks is​ often ill-posed, since many​‌ results produced in our​​ scientific community merely focus​​​‌ on improving energy efficiency​ without taking rebound effects​‌ into account.

In the​​ future, we will contribute​​​‌ to better understanding large​ scale impact of new​‌ communication technologies, and to​​ investigate how innovation can​​​‌ help reducing the energy​ footprint, and may help​‌ to build a greener​​ world.

6.1 Federated​ Learning

Participants: Malcolm Egan​‌, Jean-Marie Gorce,​​ Tan Khiem Huynh.​​​‌

A central topic in​ MARACAS during 2025 was​‌ federated learning. This work​​ was primarily carried out​​​‌ in the context of​ the Inria Challenges FedMalin​‌ and Learn-Net, and focused​​ on both the convergence​​​‌ theory and applications in​ wireless communication networks. A​‌ key result published in​​ NeurIPS 2025 established a​​​‌ general convergence theory for​ federated learning with Markovian​‌ data sources 33.​​ In the context of​​​‌ the Inria Learn-Net Challenge,​ MARACAS also organized a​‌ workshop for PhD students​​ on federated learning.

6.2​​​‌ Channel Charting

Participants: Maxime​ Guillaud, Mohamed El​‌ Mehdi Makhlouf, Anil​​ Kumar.

Progress has​​ been made on multiple​​​‌ aspects of the work‌ on Channel Charting: we‌​‌ published the MOCSID dataset​​ 36, developed a​​​‌ new weak supervision approach‌ leveraging Doppler effect 35‌​‌, and extended our​​ work to charting in​​​‌ the presence of a‌ reflective intelligent surface 37‌​‌. We co-organized a​​ Workshop on Privacy in​​​‌ Wireless Communications in collaboration‌ with the CHASER project.‌​‌

6.3 Risk-Aware Data Compression​​

Participants: Malcolm Egan.​​​‌

A key question for‌ modern communication systems is‌​‌ how to tailor communication​​ strategies for specific tasks,​​​‌ often known as goal-oriented‌ or semantic communications. During‌​‌ 2025, in the context​​ of the PEPR Réseau​​​‌ du futur and the‌ ANR JCJC TCDTP projects,‌​‌ a new framework was​​ established for goal-oriented communications​​​‌ which accounted for the‌ risk associated with extreme‌​‌ events. A risk-aware framework​​ was developed in detail​​​‌ for fixed-length source coding‌ with risk measure distortion‌​‌ constraints, with fundamental information​​ theoretic limits established in​​​‌ 32. This framework‌ was also utilized for‌​‌ the design of goal-oriented​​ vector quantization schemes where​​​‌ the goal is imperfectly‌ specified in 24.‌​‌

6.4 Information-Theoretic Limits of​​ Broadcast Channels

Participants: Malcolm​​​‌ Egan, Jean-Marie Gorce‌.

A core information-theoretic‌​‌ model is the broadcast​​ channel, which plays a​​​‌ key role in understanding‌ downlink communication channels. In‌​‌ 26 with collaborators at​​ Princeton University, we established​​​‌ a finite blocklength characterization‌ in the presence of‌​‌ heterogeous delay constraints, which​​ captures scenarios where coding​​​‌ is applied to multiple‌ messages that arrive at‌​‌ different times.

7.1 Latest software​​ developments

7.2​​ New platforms

Participants: Pascal​​​‌ Girard, Jean-Marie Gorce​, Maxime Guillaud,​‌ Mathieu Imbert, Cyrille​​ Morin, Léonardo Sampaio​​​‌ Cardoso.

7.2.1 FIT/CorteXlab​ toward integration in SLICES/Europe​‌

FIT (Future Internet of​​ Things) was a french​​​‌ Equipex (Équipement d'excellence) built​ to develop an experimental​‌ facility, a federated and​​ competitive infrastructure with international​​ visibility and a broad​​​‌ panel of customers. FIT‌ is composed of four‌​‌ main parts: a Network​​ Operations Center (FIT NOC),​​​‌ a set of IoT‌ test-beds (FIT IoT-Lab), a‌​‌ set of wireless test-beds​​ (FIT-Wireless) which includes the​​​‌ FIT/CorteXlab platform managed by‌ MARACAS team, and finally‌​‌ a set of Cloud​​ test-beds (FIT-Cloud). In 2014​​​‌ the construction of the‌ room was done and‌​‌ SDR nodes have been​​ installed in the room:​​​‌ 42 industrial PCs (Aplus‌ Nuvo-3000E/P), 22 NI radio‌​‌ boards (usrp ) and​​ 18 Nutaq boards (PicoSDR,​​​‌ 2x2 and 4X4) can‌ be programmed remotely, from‌​‌ internet now.

As the​​ FIT project development phase​​​‌ ended in 2019 ,‌ CorteXlab has seen continued‌​‌ usage as well as​​ further developments. FIT/CorteXlab has​​​‌ been used by both‌ INSA and the European‌​‌ GNU Radio Days for​​ both lectures and tutorials.​​​‌ Several scientific measurements campaigns‌ have taken place in‌​‌ the FIT/CorteXlab experimentation room​​ and are under works​​​‌ at the moment.

photography‌ showing the CorteXlab plateform‌​‌

In 2024, CorteXlab​​​‌ became a part of‌ the SLICES-FR programm funded‌​‌ by PEPR NF/PC 10​​ PLATEFORMS, in coordination with​​​‌ Raymond Knopp from Eurecom,‌ and Walid Dabbous from‌​‌ the team DIANA, Inria​​ Sophia. This PEPR funding​​​‌ is aimed at platform‌ rejuvenation to keep the‌​‌ platform relevant and up​​ to date for research.​​​‌

Preparation for the rejuvenation‌ happened throughout 2025 with‌​‌ supporting software developpment and​​ preparation of new hardware​​​‌ installation, culminating with an‌ order of most of‌​‌ the computing hardware in​​ december. The new deployment​​​‌ is expected in the‌ first half of 2026.‌​‌

7.3 Open data

8.1​​ Axis 1 : Foundations​​​‌ of communication theory

Participants:​ Malcolm Egan, Jean-Marie​‌ Gorce, Maxime Guillaud​​.

In this axis,​​​‌ we addressed the following​ problems :

8.2 Axis 2 :​‌ Algorithms for MU networks​​

Participants: Malcolm Egan,​​​‌ Jean-Marie Gorce, Claire​ Goursaud, Maxime Guillaud​‌, Cyrille Morin,​​ Leonardo Sampaio.

9.1 Bilateral contracts​​​‌ with industry

Participants: Malcolm‌ Egan, Jean-Marie Gorce‌​‌.

We have currently​​ involved in the following​​​‌ partnerships:

1. Inria-Nokia Bell Labs‌ common lab : Jean-Marie‌​‌ Gorce (until march 2025),​​ then Malcolm Egan ,​​​‌ lead the challenge Learnnet‌ [2024-2028].
2. Challenge FedMalin :‌​‌ Jean-Marie Gorce , Malcolm​​ Egan and Tan Khiem​​​‌ Huynh are involved in‌ this challenge.

9.2 Bilateral‌​‌ grants with industry

Participants:​​ Fabrice Dupuy, Malcolm​​​‌ Egan, Jean-Marie Gorce‌, Claire Goursaud,‌​‌ Claire Mesny, Shanglin​​ Yang.

1. CIFRE with​​​‌ Orange Labs (2022-2025) on‌ passive TAG aided localization‌​‌ with zero-energy-devices anchors. This​​ work is adressed by​​​‌ Mr Shanglin Yang (PhD‌ student), defended in Dec‌​‌ 2025. He is co-supervised​​ by Jean-Marie Gorce and​​​‌ Guillaume Villemaud from the‌ team Rhodes, CITI. The‌​‌ objective was to design​​ an optimal code for​​​‌ a passive TAG, with‌ its optimal detector (in‌​‌ Bayesian sens). The proposed​​ solution has been demonstrated​​​‌ in SLICES/CorteXlab.
2. CIFRE with‌ Orange Labs (2022-2025) on‌​‌ quantum algorithms for networks.​​ This project is developed​​​‌ in the PhD of‌ Fabrice Dupuy. The aim‌​‌ of the funded thesis​​ was to pave the​​​‌ way for building a‌ quantum network. The objective‌​‌ was to determine which​​ protocols and algorithms are​​​‌ suitable for the quantum‌ network (i.e. when the‌​‌ transmitted data is quantum),​​ depending on the repeaters​​​‌ and links performances. The‌ thesis had to be‌​‌ stopped due to the​​ student health issues, but​​​‌ has been renewed with‌ a new student (Claire‌​‌ MESNY, PhD starting end​​ of 2024).
3. SPIE ICS​​​‌ Chaire (2022-2025) - 2nd‌ phase: A funded postdoc‌​‌ studied communication strategies to​​ support predictive maintenance systems.​​​‌ A funded PhD (in‌ collaboration with Dynamid and‌​‌ Agora) is currently investigating​​ energy efficient training strategies​​​‌ for DNNs.

10.1 International‌​‌ initiatives

10.2​​​‌ International research visitors

10.3 European initiatives

10.4​‌ National initiatives

11.1 Promoting scientific​ activities

11.2 Teaching​​ - Supervision - Juries​​​‌ - Educational and pedagogical‌ outreach

Maracas members are‌​‌ teaching regularly at the​​ telecommunications department of INSA​​​‌ Lyon. We deliver courses‌ with strong connections with‌​‌ our research activity. The​​ main ones are:

• Bachelor​​​‌ : L Cardoso -‌ Electromagnetism and Wave Physics,‌​‌ 104 eqTD, L2, First​​ Cycle Dept, INSA Lyon,​​​‌ France.
• Bachelor : L‌ Cardoso - Mathematics for‌​‌ Engineering, 60h eqTD, L1,​​ First Cycle Dept, INSA​​​‌ Lyon, France.
• Bachelor :‌ L Cardoso, C Goursaud,‌​‌ K. Zagalo - Digital​​ Communications, 80h eqTD, L3,​​​‌ Telecommunications dept, INSA Lyon,‌ France.
• Bachelor : L‌​‌ Cardoso, C Goursaud, Research​​ projetcs - 32h eqTD,​​​‌ L3, Telecommunications dept, INSA‌ Lyon, France.
• Master :‌​‌ K. Zagalo, JM Gorce​​ (until April 25) -​​​‌ Advanced Digital Communications, 64h‌ eqTD, M1, Telecommunications dept,‌​‌ INSA Lyon, France.
• Master​​ : K. Zagalo -​​​‌ Networks Performance Evaluation, 14h‌ eqTD, M1, Telecommunications dept,‌​‌ INSA Lyon, France.
• Master​​ : L Cardoso, K​​​‌ Zagalo - Radio Access‌ Networks, 32h eqTD, M1,‌​‌ Telecommunications dept, INSA Lyon,​​ France.
• Master : C​​​‌ Goursaud - Communications Systems,‌ 32h eqTD, M1, Telecommunication‌​‌
• Master : C Goursaud​​ - Quantum Algorithms Projects,​​​‌ 32h eqTD, M2, Telecommunications‌ dept, INSA Lyon, France.‌​‌

Maracas members (M Guillaud,​​ C Goursaud, C Morin)​​​‌ also gave a 3‌ days teaching course for‌​‌ industrial professionals on wireless​​ systems planification.

11.3 Popularization‌​‌

12.1 Major publications​‌

• 1 articleB. C.​​Bayram Cevdet Akdeniz,​​​‌ M.Malcolm Egan and​ B. Q.Bao Quoc​‌ Tang. Equilibrium Signaling:​​ Molecular Communication Robust to​​​‌ Geometry Uncertainties.IEEE​ Transactions on Communications69​‌2February 2020,​​ 752 - 765HAL​​​‌DOI
• 2 articleG.​ C.George C. Alexandropoulos​‌, P.Paul Ferrand​​, J.-M.Jean-Marie Gorce​​​‌ and C. B.Constantinos​ B. Papadias. Advanced​‌ coordinated beamforming for the​​ downlink of future LTE​​​‌ cellular networks.IEEE​ Communications Magazine547​‌Arxiv: 16 pages, 6​​ figures, accepted to IEEE​​​‌ Communications MagazineJuly 2016​, 54 - 60​‌HALDOIback to​​ text
• 3 articleM.​​​‌Mauro De Freitas,​ M.Malcolm Egan,​‌ L.Laurent Clavier,​​ A.Alban Goupil,​​​‌ G. W.Gareth W.​ Peters and N.Nourddine​‌ Azzaoui. Capacity Bounds​​ for Additive Symmetric $$ -Stable​​​‌ Noise Channels.IEEE​ Transactions on Information Theory​‌638August 2017​​, 5115-5123HALDOI​​​‌
• 4 articleM.Malcolm​ Egan, L.Laurent​‌ Clavier, C.Ce​​ Zheng, M.Mauro​​​‌ De Freitas and J.-M.​Jean-Marie Gorce. Dynamic​‌ Interference for Uplink SCMA​​ in Large-Scale Wireless Networks​​​‌ without Coordination.EURASIP​ Journal on Wireless Communications​‌ and Networking20181​​August 2018, 1-14​​​‌HALDOI
• 5 article​M.Malcolm Egan,​‌ V.Valeria Loscrì,​​ T. Q.Trung Q​​​‌ Duong and M. D.​Marco Di Renzo.​‌ Strategies for Coexistence in​​ Molecular Communication.IEEE​​​‌ Transactions on NanoBioscience18​1January 2019,​‌ 51-60HALDOIback​​ to text
• 6 inproceedings​​​‌M.Malcolm Egan,​ S.Samir Perlaza and​‌ V.Vyacheslav Kungurtsev.​​ Capacity sensitivity in additive​​​‌ non-gaussian noise channels.​2017 IEEE International Symposium​‌ on Information Theory (ISIT)​​IEEE2017, 416--420​​​‌back to text
• 7​ articleY.Yasser Fadlallah​‌, O.Othmane Oubejja​​, S.Sarah Kamel​​​‌, P.Philippe Ciblat​, M.Michele Wigger​‌ and J.-M. S.Jean-Marie​​ S Gorce. Cache-Aided​​​‌ Polar Coding: From Theory​ to Implementation.IEEE​‌ Journal on Selected Areas​​ in Information TheoryNovember​​​‌ 2021, 1-17HAL​DOI
• 8 articleY.​‌Yasser Fadlallah, A.​​ M.Antonia M. Tulino​​​‌, D.Dario Barone​, G.Giuseppe Vettigli​‌, J.Jaime Llorca​​ and J.-M.Jean-Marie Gorce​​​‌. Coding for Caching​ in 5G Networks.​‌IEEE Communications Magazine55​​2February 2017,​​​‌ 106 - 113HAL​DOIback to text​‌
• 9 articleP.Paul​​ Ferrand, M.Maxime​​​‌ Guillaud, C.Christoph​ Studer and O.Olav​‌ Tirkkonen. Wireless Channel​​ Charting: Theory, Practice, and​​​‌ Applications.IEEE Communications​ Magazine2023HALDOI​‌
• 10 articleC.Cristian​​ Genes, I.Iñaki​​ Esnaola, S.Samir​​​‌ Perlaza, L. F.‌Luis F Ochoa and‌​‌ D.Daniel Coca.​​ Robust Recovery of Missing​​​‌ Data in Electricity Distribution‌ Systems.IEEE Transactions‌​‌ on Smart Grid2018​​back to text
• 11​​​‌ inproceedingsJ.-M.Jean-Marie Gorce‌, Y.Yasser Fadlallah‌​‌, J.-M.Jean-Marc Kelif​​, H. V.H​​​‌ Vincent Poor and A.‌Azeddine Gati. Fundamental‌​‌ limits of a dense​​ iot cell in the​​​‌ uplink.Modeling and‌ Optimization in Mobile, Ad‌​‌ Hoc, and Wireless Networks​​ (WiOpt), 2017 15th International​​​‌ Symposium onIEEE2017‌, 1--6
• 12 article‌​‌C.Claire Goursaud and​​ J.-M.Jean-Marie Gorce.​​​‌ Dedicated networks for IoT‌ : PHY / MAC‌​‌ state of the art​​ and challenges.EAI​​​‌ endorsed transactions on Internet‌ of ThingsOctober 2015‌​‌HALDOI
• 13 article​​M.Mathieu Goutay,​​​‌ F. A.Fayçal Ait‌ Aoudia, J.Jakob‌​‌ Hoydis and J.-M. S.​​Jean-Marie S Gorce.​​​‌ Machine Learning for MU-MIMO‌ Receive Processing in OFDM‌​‌ Systems.IEEE Journal​​ on Selected Areas in​​​‌ CommunicationsJune 2021HAL‌DOI
• 14 articleT.‌​‌ C.Trang C Mai​​, M.Malcolm Egan​​​‌, T. Q.Trung‌ Q Duong and M.‌​‌Marco Di Renzo.​​ Event Detection in Molecular​​​‌ Communication Networks with Anomalous‌ Diffusion.IEEE Communications‌​‌ Letters216February​​ 2017, 1249 -​​​‌ 1252HALDOI
• 15‌ articleY.Yuqi Mo‌​‌, M.-T.Minh-Tien Do​​, C.Claire Goursaud​​​‌ and J.-M.Jean-Marie Gorce‌. Up-Link Capacity Derivation‌​‌ for Ultra-Narrow-Band IoT Wireless​​ Networks.International Journal​​​‌ of Wireless Information Networks‌243June 2017‌​‌, 300-316HALDOI​​
• 16 thesisC.Cyrille​​​‌ Morin. Deep learning‌ based approaches for detection‌​‌ in physical layer wireless​​ multiple access.Université​​​‌ de LyonJuly 2021‌HAL
• 17 inproceedingsS.‌​‌Samir Perlaza, A.​​Ali Tajer and H.​​​‌ V.H Vincent Poor‌. Simultaneous Energy and‌​‌ Information Transmission: A Finite​​ Block-Length Analysis.IEEE​​​‌ International Workshop on Signal‌ Processing Advances in Wireless‌​‌ Communications2018back to​​ text
• 18 articleV.​​​‌Victor Quintero, S.‌Samir Perlaza, I.‌​‌Iñaki Esnaola and J.-M.​​Jean-Marie Gorce. Approximate​​​‌ Capacity Region of the‌ Two-User Gaussian Interference Channel‌​‌ with Noisy Channel-Output Feedback​​.IEEE Transactions on​​​‌ Information Theory647‌Part of this work‌​‌ was presented at the​​ IEEE International Workshop on​​​‌ Information Theory (ITW), Cambridge,‌ United Kingdom, September 2016‌​‌ and IEEE International Workshop​​ on Information Theory (ITW),​​​‌ Jeju Island, Korea, October,‌ 2015. Parts of this‌​‌ work appear in INRIA​​ Technical Report Number 0456,​​​‌ 2015, and INRIA Research‌ Report Number 8861.July‌​‌ 2018, 5326-5358HAL​​DOIback to text​​​‌
• 19 articleM. E.‌Mohamed El Amine Seddik‌​‌, M.Maxime Guillaud​​ and R.Romain Couillet​​​‌. When Random Tensors‌ meet Random Matrices.‌​‌The Annals of Applied​​ Probability341AFebruary​​​‌ 2024HALDOI
• 20‌ inproceedingsM. E.Mohamed‌​‌ El Amine Seddik,​​ M.Malik Tiomoko,​​​‌ A.Alexis Decurninge,‌ M.Maxim Panov and‌​‌ M.Maxime Guillaud.​​​‌ Learning from Low Rank​ Tensor Data: A Random​‌ Tensor Theory Perspective.​​Proceedings of Machine Learning​​​‌ Research, vol. 216Thirty-Ninth​ Conference on Uncertainty in​‌ Artificial IntelligencePittsburgh, PA​​ (USA), United StatesJuly​​​‌ 2023HAL
• 21 article​Y.Yi Yu,​‌ L.Lina Mroueh,​​ D.Diane Duchemin,​​​‌ C.Claire Goursaud,​ G.Guillaume Vivier,​‌ J.-M.Jean-Marie Gorce and​​ M.Michel Terré.​​​‌ Adaptive Multi-Channels Allocation in​ LoRa Networks.IEEE​‌ Access82020,​​ 214177-214189HALDOI

12.2​​​‌ Publications of the year​

12.3 Cited publications

• 45​​​‌ techreportC.Charbel Abdel​ Nour, C.Cédric​‌ Adjih, K.Karine​​ Amis, X.Xavier​​​‌ Begaud, M.Matthieu​ Crussière, A.Antoine​‌ Durant, M.Marco​​ Di Renzo, C.​​​‌Catherine Douillard, H.​Hajar El Hassani,​‌ J.Joumana Farah,​​ I.Inbar Fijalkow,​​​‌ D.Davy Gaillot,​ J.-M.Jean-Marie Gorce,​‌ C.Claire Goursaud,​​ M.M. Guillaud,​​​‌ D.Didier Le Ruyet​, M.Mabrouk Asma​‌, P.Pascal Paganini​​, D.-K. G.Dang-Kièn​​​‌ Germain Pham, B.​Balakrishna Prabhu, G.​‌Ghaya Rekaya Ben Othman​​, E. P.Eric​​​‌ Pierre Simon and R.​Rafik Zayani. Deliverable​‌ D1 - Technical Report​​ NF-PERSEUS 2023.CEA​​​‌ - Commissariat à l'énergie​ atomique et aux énergies​‌ alternativesApril 2024,​​ 1-86HALback to​​​‌ text
• 46 inproceedingsA.​Anthony Bardou and T.​‌Thomas Begin. Inspire:​​ Distributed bayesian optimization for​​​‌ improving spatial reuse in​ dense wlans.Proceedings​‌ of the 25th International​​ ACM Conference on Modeling​​​‌ Analysis and Simulation of​ Wireless and Mobile Systems​‌2022, 133--142back​​ to text
• 47 article​​​‌S.Sebastian Dörner,​ S.Sebastian Cammerer,​‌ J.Jakob Hoydis and​​ S.Stephan ten Brink​​​‌. Deep learning based​ communication over the air​‌.IEEE Journal of​​ Selected Topics in Signal​​​‌ Processing1212018​, 132--143back to​‌ text
• 48 unpublishedM.​​Malcolm Egan. Fixed-Length​​​‌ Lossy Compression with Distortion​ Risk Measure Constraints.​‌May 2024, working​​ paper or preprintHAL​​​‌back to text
• 49​ articleP.Paul Ferrand​‌, M.Maxime Guillaud​​, C.Christoph Studer​​​‌ and O.Olav Tirkkonen​. Wireless Channel Charting:​‌ Theory, Practice, and Applications​​.IEEE Communications Magazine​​6162023,​​​‌ 124-130DOIback to‌ text
• 50 articleM.‌​‌ I.Muhammad Idham Habibie​​, C.Claire Goursaud​​​‌ and J.Jihad Hamie‌. Quantum Minimum Searching‌​‌ Algorithms for Active User​​ Detection in Wireless IoT​​​‌ Networks.IEEE Internet‌ of Things Journal11‌​‌12June 2024,​​ 22603-22615HALDOIback​​​‌ to text
• 51 article‌ M. G.Mohammad G‌​‌ Khoshkholgh, K.Keivan​​ Navaie, K. G.​​​‌Kang G Shin,‌ V.VCM Leung and‌​‌ H.Halim Yanikomeroglu.​​ Caching or No Caching​​​‌ in Dense HetNets? arXiv‌ preprint arXiv:1901.11068 2019 back‌​‌ to text
• 52 article​​S.Songze Li,​​​‌ M. A.Mohammad Ali‌ Maddah-Ali, Q.Qian‌​‌ Yu and A. S.​​A Salman Avestimehr.​​​‌ A fundamental tradeoff between‌ computation and communication in‌​‌ distributed computing.IEEE​​ Transactions on Information Theory​​​‌6412018,‌ 109--128back to text‌​‌
• 53 articleW.Wei​​ Liu, S.Shuyang​​​‌ Xue, J.Jiandong‌ Li and L.Lajos‌​‌ Hanzo. Topological Interference​​ Management for Wireless Networks​​​‌.IEEE Access6‌2018, 76942--76955back‌​‌ to text
• 54 article​​Y.Yuyi Mao,​​​‌ C.Changsheng You,‌ J.Jun Zhang,‌​‌ K.Kaibin Huang and​​ K. B.Khaled B​​​‌ Letaief. A survey‌ on mobile edge computing:‌​‌ The communication perspective.​​IEEE Communications Surveys &​​​‌ Tutorials1942017‌, 2322--2358back to‌​‌ text
• 55 inproceedingsG.​​Guillaume Marthe, C.​​​‌Claire Goursaud and L.‌Laurent Clavier. Enabling‌​‌ Low-Power Signature Recognition for​​ the IoT with SLIF​​​‌ neurons.EUSIPCO 2024‌ - 32nd European conference‌​‌ on signal processingLyon,​​ FranceAugust 2024,​​​‌ 1-5HALback to‌ text
• 56 phdthesisG.‌​‌Guillaume Marthe. Neurones​​ à impulsion pour les​​​‌ communications sans fil.‌INSA lyonNovember 2024‌​‌HALback to text​​
• 57 inproceedingsR.Romain​​​‌ Piron and C.Claire‌ Goursaud. Hybrid Grover‌​‌ search for AUD on​​ a NISQ device.​​​‌EUSIPCO 2024 - 32nd‌ European signal processing conference‌​‌Lyon, FranceAugust 2024​​, 1-5HALback​​​‌ to textback to‌ text
• 58 inproceedingsR.‌​‌Romain Piron and C.​​Claire Goursaud. Quantum​​​‌ Annealing for Active User‌ Detection in NOMA Systems‌​‌.ACSSC 2024 -​​ 58th Asilomar Conference on​​​‌ Signals, Systems, and Computers‌Pacific Grove (CA), United‌​‌ StatesOctober 2024,​​ 1-5HALback to​​​‌ textback to text‌
• 59 inproceedingsR.Romain‌​‌ Piron and C.Claire​​ Goursaud. Scheduling Quantum​​​‌ Annealing for Active User‌ Detection in a NOMA‌​‌ Network.Fifth IEEE​​ International Conference on Quantum​​​‌ Computing and Engineering (QCE‌ 2024), IEEEIEEEMontréal‌​‌ (Québec), CanadaSeptember 2024​​HALback to text​​​‌back to text
• 60‌ articleY.Yury Polyanskiy‌​‌, H. V.H​​ Vincent Poor and S.​​​‌Sergio Verdú. Channel‌ coding rate in the‌​‌ finite blocklength regime.​​IEEE Transactions on Information​​​‌ Theory5652010‌, 2307back to‌​‌ text
• 61 articleJ.​​J. Sachs, L.​​​‌ A.L. A. A.‌ Andersson, J.J.‌​‌ Araújo, C.C.​​​‌ Curescu, J.J.​ Lundsjö, G.G.​‌ Rune, E.E.​​ Steinbach and G.G.​​​‌ Wikström. Adaptive 5G​ Low-Latency Communication for Tactile​‌ InternEt Services.Proceedings​​ of the IEEE107​​​‌2Feb 2019,​ 325-349back to text​‌
• 62 articleV. Y.​​Vincent YF Tan.​​​‌ Asymptotic estimates in information​ theory with non-vanishing error​‌ probabilities.Foundations and​​ Trends®112014,​​​‌ 1--184back to text​
• 63 inproceedingsG.Gonzalo​‌ Vazquez-Vilar, A. G.​​Albert Guillen i Fabregas​​​‌, T.Tobias Koch​ and A.Alejandro Lancho​‌. Saddlepoint approximation of​​ the error probability of​​​‌ binary hypothesis testing.​2018 IEEE International Symposium​‌ on Information Theory (ISIT)​​IEEE2018, 2306--2310​​​‌back to text
• 64​ inproceedingsQ.Qifa Yan​‌, S.Sheng Yang​​ and M.Michele Wigger​​​‌. Storage, computation, and​ communication: A fundamental tradeoff​‌ in distributed computing.​​2018 IEEE Information Theory​​​‌ Workshop (ITW)IEEE2018​, 1--5back to​‌ text
• 65 inproceedingsS.​​Shanglin Yang, Y.​​​‌Yohann Benedic, D.-T.​Dinh-Thuy Phan-Huy, J.-M.​‌Jean-Marie Gorce and G.​​Guillaume Villemaud. Indoor​​​‌ Localization of Smartphones Thanks​ to Zero-Energy-Devices Beacons.​‌2024 18th European Conference​​ on Antennas and Propagation​​​‌ (EuCAP)Submitted to EUCAP​ 2024Glasgow, United Kingdom​‌March 2024HALDOI​​back to text
• 66​​​‌ articleX.Xinping Yi​ and G.Giuseppe Caire​‌. Topological interference management​​ with decoded message passing​​​‌.IEEE Transactions on​ Information Theory645​‌2018, 3842--3864back​​ to text