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... 21 Septembre 2017 : Lors de la conférence CROWNCOM 2017, le "Best paper Award" a été obtenu par Rémi Bonnefoi; Lilian Besson, Christophe Moy, Emilie Kaufmann, Jacques Palicot pour l'article intitulé :"Multi Arm Bandit Learning in IoT Networks : Learning Helps Even in Non-Stationnary Settings" ...

SCEE : Signal, Communication et Electronique Embarquée

SCEE research team (Signal, Communications and Embedded Electronics), is a team of SUPELEC integrated in IETR lab (Institute of Electronics and Telecommunications of Rennes).

SCEE research focus on science and technologies to improve future radio systems and equipments, favoring the use of easier and more performant software radio and cognitive radio technologies.
SCEE particularly aims at making research on solutions that make radio equipments being more adaptive and autonomous. This page explains this approach in more details. It is neither a software radio nor a cognitive radio overview. For more information about software radio and cognitive radio equipments design, we encourage you to read the following book:
J. Palicot et al

Radio Engineering: from Software Radio to Cognitive Radio

Cognitive cycle

Figure 1 shows a view of the simplified cognitive cycle we proposed in [1] to summarise the requirements necessary to make a cognitive radio equipment, compared to a normal radio equipment. We mean by equipment any king of wireless terminal, mobile or not (e.g. a 2G/3G mobile phone, a multi-wireless smart phone, a laptop with WiFi connectivity, a base station of NodeB, etc.).

Hence, apart from the traditional signal processing for PHY layer and higher layers, as shown in Figure 1, a cognitive radio should also be composed of:
  • 1 - A flexible platform (to summarize, here is all that concerns software radio topic) executing adaptive signal processing
  • 2 - Sensing means (an electronic sensor directly giving an electric value, or some signal processing on signals, or some information coming from the network or the user, or some internal state of the equipment itself)
  • 3 - Decision making facilities (including learning, classifying, etc.)
  • 4 - Some glue to make all this work coherently and efficiently (real-time, etc.) together: a managament architecture to be added to the pure radio processing
  • Figure 1: Simplified cognitive cycle

    Flexible platform and processing for cognitive radio

    Figure 2 shows how we have been addressing SDR (point 1 of Figure 1) in general for almost 10 years in SCEE research team. We can distinguish:
  • signal processing for SDR (PAPR issue [2][3], synchronisation [4], sample rate conversion [5], MIMO blind demodulation [6]... )
  • flexible technologies (partial reconfiguration of FPGA [7][8], ... )
  • parameterization techniques [9][10]
  • high level reconfiguration management [11][12]

  • Figure 2: Flexible platform and signal processing


    Point 2 of Figure 1 on sensing research done in SCEE team is detailled in Figure 3:
  • the sensorial radio bubble [13]
  • signal processing for sensing (cylostationnarity [14], blind standard recognition sensor [15], blind spectrum detection using compressed sensing [16], ...)
  • video sensor for cognitive radio [17]
  • taking into account sensing errors for energy detector [18]
  • Figure 3: Sensing


    Figure 4 lists the work done in the team on decision making and learning:
  • a multi-armed bandit (MAB) and upper confidence bound (UCB) approach for dynamic configuration adaptation (DCA) of cognitive radio [19]
  • a UCB approach for dynamic spectrum adaptation (DSA) [20]
  • decision making classification for CR equipments [21], whatever DCA and DSA
  • decision making under sensing uncertainty [22]
  • decision based on statistical modeling of the environment metrics
  • Figure 4: Decision making

    Cognitive management

    In order to merge coherently and efficiently all these new features with radio signal processing into an equipment, Figure 5 explains that a management architecture is required:
  • from a software radio management to a cognitive radio management [23]
  • HDCRAM metamodel [24]
  • HDCRAM as a high level design tool [25]

  • A management architecture as HDCRAM is a way to generalize already existing auto-adaptation means in a radio equipment (such as power control, adaptive filters, etc.). GSM power control for instance could be integrated in HDCRAM management. Then the idea would not be to do the same as power control has been doing for years (and in a more exepensive manner), but to share the metrucs required by power control with other entitites in the equipment. We could imagine in this simplified scenario that power control could be mixed with channel coding, constellation order adaptations and so on, which starts in current approach. And if you combine this with all other auto-adaptive aspects that could be in a radio (opportunitic spectrum access, chips power consumption real-time adaptation, etc.) there is a need for HDCRAM.
    Figure 5: Management architecture

    Example of cognitive radio: Green Cognitive Radio

    Cognitive radio is not only a about spectrum ressources optimization as it is almost always reduced in the community. We claim it goes much further even if spectrum scarcity is one major point. Figure 6 shows for instance how we consider cognitive radio could participate to radio sustainability [26] while:
  • mitigating CO2 emissions,
  • decreasing human exposure to radio waves,
  • saving spectrum ressource and decreasing spectrum pollution.

  • One point is to consider power consumption as a metric for radio devices optimization and consequently merge power consumption with the other parameters to be optimized using cognitive engines in radio equipments and networks.
    Cognitive Radio will make radio domain know the same "revolution" that car industry made sevral years ago, e.g. adding control and intelligence to better use resources and respect the environment, both in terms of sustainability and security [28].
    Bringing progress to people, improving their confidence in this technological field, and dissipating their fears of radio evolution is instrumental in providing the radio domain with a good prospect in the 21st century [29].
    Figure 6: Green Cognitive Radio


    [1] Loïg GODARD, Christophe MOY, Jacques PALICOT, "An Executable Meta-Model of a Hierarchical and Distributed Architecture Management for the Design of Cognitive Radio Equipments", Annals of Telecommunications, Special issue on Cognitive Radio, vol. 64, pp.463-482, number 7-8, Aug. 2009

    [2] Sidkieta ZABRE, Jacques PALICOT, Yves LOUET, Christophe MOY, Christian LEREAU, "Carrier per Carrier Analysis of SDR Signals Power Ratio", SDR Forum Technical Conference’06, Orlando (USA), November 2006
    Paper PDF version
    Slides PDF version

    [3] Anh-Tai HO, Jean-François HELARD, Youssef NASSER, Yves LOUET, "PAPR Reduction Approach Based on Channel Estimation Pilots for Next Generations Broadcasting Systems", International Journal of Digital Multimedia Broadcasting, vol. 2011, Article ID 365896, 17 pages, 2011. doi:10.1155/2011/365896

    [4] Adel METREF, Daniel Le GUENNEC, Jacques PALICOT, "A Carrier Recovery loop for Cognitive Radio Applications", Circuits, Systems and Signal Processing Journal (CSSP), Volume 30, Issue 4, 2011, Pages 847-870

    [5] Jacques PALICOT, Daniel Le GUENNEC, Christophe MOY, "Transmitter/Receiver Digital Front End", chapter 8 of "Radio Engineering: from Software Radio to Cognitive Radio", Wiley ISTE, 2011

    [6] Steredenn DAUMONT, Daniel Le GUENNEC, "Exploitation of the redundancy induced by Alamouti coding for MIMO signals’ blind demodulation", Signal Processing, Elsevier, Octobre 2011, 10 pages, doi:10.1016/j.sigpro.2011.09.012

    [7] Julien DELORME, Amor NAFKHA, Pierre LERAY, Christophe MOY, “New OPBHWICAP interface for real-time Partial reconfiguration of FPGA”, International Conference on ReConFigurable Computing and FPGAs, ReConFig'09, Cancun, Mexico, 9-11 Dec 2009
    Paper PDF version
    Slides PDF version

    [8] Pierre LERAY, Amor NAFKHA, Christophe MOY, "Implementation Scenario for Teaching Partial Reconfiguration of FPGA” 6th International Workshop on Reconfigurable Communication Centric Systems-on-Chip (ReCoSoC), Montpellier, France, June 20 – 22, 2011
    Paper PDF version
    Slides PDF version

    [9] Virgilio RODRIGUEZ, Christophe MOY, Jacques PALICOT, "Install or invoke?: The optimal trade-off between performance and cost in the design of multi-standard reconfigurable radios", Wiley Wireless Communications and Mobile Computing Journal Special Issue on Cognitive Radio, Software Defined Radio And Adaptive Wireless Systems, Issue Edited by Hüseyin Arslan, Joseph Mitola III, Volume 7, Issue 9 , Pages 1143 – 1156, Nov. 2007

    [10] Malek NAOUES, Dominique NOGUET, Laurent ALAUS, Yves LOUET, "A common operator for FFT and FEC decoding", Microprocessors and Microsystems, 19 August 2011, ISSN 0141-9331

    [11] Jean-Philippe DELAHAYE, Pierre LERAY, Christophe MOY, Jacques PALICOT, "Managing Dynamic Partial Reconfiguration on Heterogeneous SDR Platforms", SDR Forum Technical Conference’05, Anaheim (USA), November 2005
    Paper PDF version
    Slides PDF version

    [12] Stéphane LECOMTE, Samuel GUILLOUARD, Christophe MOY, Pierre LERAY, Philippe SOULARD, "A co-design methodology based on Model Driven Architecture for Real Time Embedded systems", Mathematical and Computer Modelling Journal, publication in 2010
    Paper PDF version

    [13] Jacques PALICOT, Christophe MOY, Rachid HACHEMANI, "Multilayer sensors for the Sensorial Radio Bubble", Physical Communication 2 (2009), pp151-165, may 2009

    [14] Mohamed GHOZZI, François MARX, Mischa DOHLER, Jacques PALICOT, Cyclostationarity-Based Test for Detection of Vacant Frequency Bands, IEEE Crowncom'06, 8-10 June 2006, Mykonos, Greece
    Paper PDF version

    [15] Rachid HACHEMANI, Jacques PALICOT, Christophe MOY, "A New Standard Recognition Sensor for Cognitive Radio Terminal", EUSIPCO'07, Poznan, Pologne, 3-7 septembre 2007

    [16] Ziad KHALAF, Amor NAFKHA, Jacques PALICOT, "Blind Spectrum Detector for Cognitive Radio using Compressed Sensing", IEEE GLOBECOM 5-9 December 2011, Houston, Texas, USA

    [17] Amor NAFKHA, Renaud SEGUIER, Jacques PALICOT, Christophe MOY, Jean-Philippe DELAHAYE, “A Reconfigurable BaseBand Transmitter for Adaptive Image Coding“, IST Mobile and Wireless Communications Summit'07, 1-5 July 2007, Budapest, Hungary
    Paper PDF version

    [18] Wassim JOUINI, "Energy Detection Limits under Log-Normal Approximated Noise Uncertainty", Signal Processing Letters, Volume 18, Issue 7, Pages: 423-426, July 2011 ; DOI:10.1109/LSP.2011.2155649

    [19] Wassim JOUINI, Damien ERNST, Christophe MOY, Jacques PALICOT, "Multi-Armed Bandit Based Policies for Cognitive Radio’s Decision Making Issues", 3rd conference on Signal Circuits and Systems, Jerba, Tunisia, 6-8 November 2009
    Paper PDF version

    [20] Wassim JOUINI, Damien ERNST, Christophe MOY, Jacques PALICOT, "Upper confidence bound based decision making strategies and dynamic spectrum access", International Conference on Communications, ICC’10, Cape Town, South Africa, 26-29 May 2010
    Paper PDF version

    [21] Wassim JOUINI, Christophe MOY, Jacques PALICOT, “Decision making for cognitive radio equipment: analysis of the first 10 years of exploration", EURASIP Journal on Wireless Communications and Networking 2012, 2012:26.

    [22] Wassim JOUINI, Christophe MOY, Jacques PALICOT, "Upper Confidence Bound Algorithm for Opportunistic Spectrum Access with Sensing Errors", CrownCom'11, 1-3 June 2011, Osaka, Japan

    [23] Loïg GODARD, Christophe MOY, Jacques PALICOT, "From a Configuration Management to a Cognitive Radio Management of SDR Systems", CrownCom'06, 8-10 June 2006, Mykonos, Greece
    Paper PDF version

    [24] Loig GODARD, Christophe MOY, Jacques PALICOT,"An Executable Meta-Model of a Hierarchical and Distributed Architecture Management for the Design of Cognitive Radio Equipments", Annals of Telecommunications, Special issue on Cognitive Radio, vol. 64, pp.463-482, number 7-8, Aug. 2009

    [25] Christophe MOY, "High-Level Design Approach for the Specification of Cognitive Radio Equipments Management APIs", Journal of Network and Systems Management, Special Issue on Management Functionalities for Cognitive Wireless Networks and Systems, Springer Editions, vol. 18, number 1, pp. 64-96, Mar. 2010, DOI: 10.1007/s10922-009-9151-3
    Paper PDF version

    [26] Jacques PALICOT, "Cognitive Radio: An Enabling Technology for the Green Radio Communications Concept," IWCMC'09, Leipzig, Germany June 2009

    [27] Navin MICHAEL, Christophe MOY, Prasad VINOD, Jacques PALICOT “Area-Power Trade-offs for Flexible Filtering in Green Radios”, Journal of Communications and Networks, Vol. 12, Num. 2, pp. 158-167, 30 April 2010

    [28] Jacques PALICOT, "How to Optimize The Spectrum: The Oil Experience", XXX URSI General Assembly,august 2011, Istanbul, Turkey

    [29] Jacques PALICOT, "Cross-Layer Sensors for Green Cognitive Radio", Annals of Telecommunications, DOI: 10.1007/s12243-012-0292-0

    Mise à jour : le 28/11/2012 15:11