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Smart Device Communication: A paradigm for high PERformance FUture Mobile nEtworking

Periodic Reporting for period 3 - PERFUME (Smart Device Communication: A paradigm for high PERformance FUture Mobile nEtworking)

Reporting period: 2018-10-01 to 2020-03-31

"Overview of the action's implementation for this reporting period


This report details the technical achievements realized duing the first half of the ERC Advanced project PERFUME. Conforming to the planned studies in the workplan, the results fall within three main areas, whose significance is briefly recalled below.

WP 1: Fundamental limits for future coordinated wireless networks

This first area concerns the development of information theoretic methods for decentralized device coordinated communications.
This area gives a fundamental layer to the as planned in the DoW. It is mathematically rooted and serves multiple key purposes: Let us understand fundamental limits of communication performance, and expose new enabling analytic tools that play an important role in building systems that near those limits.


WP2: Smart device communication methods for the future Mobile Internet

2.1 Coordinated communication methods for 5G and beyond
The third area concerns the development of decentralized coordination mechanisms within the context of 5G mobile standards, i.e. using the 5G system assumptions as design contraints. The objective there is to allow for short-to-mid term exploitation of the novel system concepts pushed in the project.

2.2: Communications for dynamic and moving networks

PERFUME pushing the development of algorithms and methods for the case where devices are both mobile and acting with some level of autonomy. A crucial case for this study is the case where radio devices are equipped on aerial devices, such as UAV (unmanned aerial devices). PERFUME proposal has pioneered this concept with a few other groups in 2014 at the time of the proposal. In 2018, large segment of wireless communication research is dedicated to UAV-aided networks as well as network-aided UAVs.

In this context, PERFUME is envisioning the use of flying robots (autonomous drones) that are fully integrated with wireless network equipment in a number of scenarios. Flying relays or flying base stations can enable better and faster response in disaster recovery scenarios (after earthquakes or floods). They can also be used for intelligent IoT data collection, in monitoring smart cities and smart agriculture. Another use case is intelligent transport systems (ITS) where flying connect devices can be used in network-assisted autonomous driving scenarios.

WP3: Experimental and prototyping development

As part of this research program on autonomous decision-making wireless flying devices, PERFUME has been developing prototypes for ""autonomous aerial cellular relay robots"". These are custom-built aerial robots (a.k.a. UAV or micro-drones) which use machine learning algorithms designed in the context of PERFUME to self-optimize their parameters for improving overall radio network performance. An example lies in the optimization of their own position in 3D at all times based on selected radio measurements. At the radio-optimized positions, the autonomous AUV acts as a cellular relay which is capable of providing application-layer enhanced (LTE, 5G) connectivity to mobile users carrying off-the-shelf commercial terminals. The communication layers builds on algorithms leveraging the world's leading opensource implementation of cellular LTE (OpenAirInterface), developed at EURECOM's Communications Systems Department.
The prototyping development track has made interesting progress and result, bootstrapping into the theoretical part of the project.



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Results by Key Areas:

WP 1: Fundamental limits for future coordinated wireless networks

Results in this area rely on the exploitation of fundamental enabling tools, which are namely information theory as well as machine learning. Note that machine learning represents a quickly growing trend within wireless communication network design. While unforeseen at the time of submission of the project, The PI and his team, especially Paul de Kerret have played a pioneering role in this area, enhancing PERFUME visibility along the way.
Details are now given on the results, first on information theoretic results, then on machine learning results.


Based on the use of information theoretic tools, we have developed several algorithms for Robust Precoding for Transmitter Cooperation with imperfect CSIT Sharing.These algorithms allow to build robustness in the problem of decentralize decision making when different transmitters are endowed with different estimated from the radio environment.

We also highlighted the value of hierarchical information exchange, whereby an order is established among the transmitters in such a way that a given transmitter has access not only to its local channel estimate but also to the estimates available at the less informed transmitters. We propose naive, locally robust, and globally robust suboptimal strategies for the joint precoding design based on regularized zero forcing.



Application of Machine Learning to Team Decision problems

The PERFUME team was an early contributor and pioneer to the field of machine learning for decentralized decision making under uncertainties. We conducted fundamental studies in this area which raised the visibility of our project in the scoentific community. In particular we introduced the new concept of Team Deep Neural Networks.



WP2: Smart device communication methods for the future Mobile Internet



2.1 Coordinated communication methods for 5G and beyond

A) Location-Aided Beam Alignment in mmWave communications

Among the enabling technologies for 5G wireless networks, millimeter wave (mmWave) communication offers the chance to deal with the bandwidth shortage affecting wireless carriers. Beam alignement is known to be a bottleneck in this area when mmwave devices are equipped with many antennas.

In PERFUME we have introduced a robust beam alignment framework in order to exhibit resilience with respect to the noise present in the position information obtained at the BS and the UE, in a single-user scenario.
The effectiveness of the robust beam alignment procedure, compared with classical designs, has been verified on simulation settings with varying location information accuracies.

B) Beam Alignment in multiuser mmWave communications

In the multi-user uplink case, a wrong beam choice might result in irreducible inter-user interference at the BS side. Indeed, the reduced number of digital chains might not always allow to resolve the residual multi-user interference which remains after the analog beamforming stage. Simple analog UE beam selection can be designed so as to enable the analog receive beam on the BS side to discriminate for interference. Hence an algorithm was design that allows for improved treatment of interference at the BS side and in turn leads to greater spectral efficiencies.



2.2: Communications for dynamic and moving networks


Theory and algorithm of autonomous placement for flying radio devices

PERFUME conducted analysis and algorithm design in the area of autonomous placement and path planing for a flying radio device. The assumption of Lineof-sight (LoS) channels or the use of simple statistical blocking models (i.e. modeling the LoS probability) has proved an excellent way to derive early insights into the problem and to allow for closed-form average performance analysis. Unfortunately, the simplified or probabilistic nature of such approaches limit our ability to guarantee performance in an actual on-field UAV deployment. F
PERFUME is planned to continue ahead with the three main axis of the projects, namely pushing for new fundamental tools from information theory, statistics and machine learning. Secondly the application of such tools in the derivation of implementatble methods for future wireless networks. Thirdly, a subset of the tools are to be tried with live experiments at the cross-road between communication and robotics as this has proved so far a success both to gain visibility and to attract talented researchers in the team.

this aspect is reinforeced from the fact that a major player in the wireless networking industry (Huawei) has declared on-demand moving Base Stations to be one of its axis of future 6G development.

In the latter, a substantial challenge for the time ahead will be the development of coordination for multi-UAV-aided wireless networks where multiple drones need to perform on line coordinatio to optimize communication services to ground users. Up to our knowledge, this aspects have so far been considered challenging and few results exist so far. Coordination methods in both the offline and the online frameworks will be considered.