D. Gesbert

Massachusetts Institute of Technology, Cambridge, Massachusetts, United States

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Publications (261)237.44 Total impact

  • Xinping Yi, David Gesbert
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    ABSTRACT: Interference networks with no channel state information at the transmitter (CSIT) except for the knowledge of the connectivity graph have been recently studied under the topological interference management (TIM) framework. In this paper, we consider a similar problem with topological knowledge but in a distributed broadcast channel setting, i.e. a network where transmitter cooperation is enabled. We show that the topological information can also be exploited in this case to strictly improve the degrees of freedom (DoF) as long as the network is not fully connected, which is a reasonable assumption in practice. Achievability schemes based on selective graph coloring, interference alignment, and hypergraph covering, are proposed. Together with outer bounds built upon generator sequence, the concept of compound channel settings, and the relation to index coding, we characterize the symmetric DoF for so-called regular networks with constant number of interfering links, and identify the sufficient and/or necessary conditions for the arbitrary network topologies to achieve a certain amount of symmetric DoF.
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    ABSTRACT: In this work, we consider a wireless network with K cooperating transmitters (TXs) serving jointly K receivers (RXs). Due to the practical limitations of the backhaul network, it is relevant to consider a setting where each TX receives its own imperfect estimate of the multi-user channel state, denoted as the distributed channel state information (CSI) setting. We focus in this work on a particular distributed CSI configuration called hierarchical CSI configuration in which the TXs can be ordered by increasing level of CSI. This scenario is particularly relevant for future networks with heterogeneous backhaul where the TXs connected with a weak backhaul link will receive only a coarse estimate while the TXs with a stronger backhaul will have a more accurate CSI. In that scenario, we formulate the optimal precoding as a team decision problem. Solving optimally this problem is extremely challenging such that we propose a heuristic approach allowing to obtain a simple, yet efficient and practical, precoding algorithm. The proposed precoding algorithm exploits the hierarchical structure of the CSI to make the transmission more robust to the imperfect CSI knowledge at the TXs.
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    ABSTRACT: This paper considers the problem of interference control in networks where base stations signals are coherently combined (aka network MIMO). Building on an analogy with so-called massive MIMO, we show how second-order statistical properties of channels can be exploited when the massive MIMO array corresponds in fact to many antennas randomly spread over a two-dimensional network. Based on the classical one-ring model, we characterize the low-rankness of channel covariance matrices and show the rank is related to the scattering radius. The application of the low-rankness property to channel estimation's denoising and low complexity interference filtering is highlighted.
    ICASSP 2014; 05/2014
  • Qianrui Li, David Gesbert, Nicolas Gresset
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    ABSTRACT: This paper considers the problem of transmitter (TX) cooperation with distributed channel state information (CSI), where two or more transmitters seek to jointly precode messages while communicating over a rate-limited coordination link. Specifically we address a so-called master-slave scenario where one master (M-) TX is endowed with perfect CSI while K slave (S-) TXs have zero prior CSI information. We are interested in possible strategies for how the M-TX may efficiently guide the S-TXs over the coordination links so as to maximize the network's figure of merit. Strategies related to communicating quantized CSI or quantized precoding decisions are described and compared. Optimal and sub-optimal low complexity approaches are shown, exhibiting gains over conventional methods.
    ICASSP 2014 - 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP); 05/2014
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    ABSTRACT: In this paper, the problem of optimal power allocation in Cognitive Radio (CR) Multiple Input Multiple Output (MIMO) systems is treated. The focus is on providing limited feedback solutions aiming at maximizing the secondary system rate subject to a constraint on the average interference caused to primary communication. The limited feedback solutions are obtained by reducing the information available at secondary transmitter (STx) for the link between STx and the secondary receiver (SRx) as well as by limiting the level of available information at STx that corresponds to the link between the STx and the primary receiver PRx. Monte Carlo simulation results are given that allow to quanitfy the performance achieved by the proposed algorithms.
  • Rajeev Gangula, david gesbert, deniz gunduz
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    ABSTRACT: In this work, we consider the optimization of feedback in a point-to-point MISO channel with an energy harvesting (EH) receiver (RX). The RX is interested in feeding back the channel state to the transmitter (TX) to help improve the transmission rate, yet must spend the harvested energy wisely to do so. The objective is to maximize the throughput by a deadline, subject to EH constraints at the RX. The throughput metric considered is an upper bound on the ergodic capacity of beamforming with limited feedback. The optimization problem is shown to be concave and a simple algorithm for obtaining the optimal feedback bit allocation policy is devised. Numerical results show that the optimal feedback policy obtained for the modified problem outperforms the naive scheme for the original problem.
    Global Conference on Signal and Information Processing (GlobalSIP), 2013 IEEE, Austin; 12/2013
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    Haifan Yin, David Gesbert
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    ABSTRACT: This paper considers the problem of interference control in multi-cell interference-limited cellular networks. We address systems employing multiple antennas combining when the number of these antennas is allowed to grow large (massive regime). We consider both the cases of co-located massive arrays and distributed antenna settings. We are interested in both the problems of channel estimation with pilot reuse and spatial filter design and aim at improving interference rejection performance by exploiting second-order statistical properties. In previous work, it was demonstrated that massive MIMO channel covariance matrices exhibit a useful finite rank property that can be modeled via the angular spread of multipath at a MIMO uniform linear array. We show here that the property extends to certain non-uniform linear arrays, and more surprisingly, to two dimensional distributed large scale arrays, although the rank model is different in the distributed setting. In particular our model exhibits the dependence of the signal subspace's richness on the scattering radius around the user terminal. The results suggest simple schemes for channel estimation's denoising and low complexity interference filtering which find an application in multi-cell cooperative networks.
    IEEE Journal of Selected Topics in Signal Processing 10/2013; 8(5). · 3.63 Impact Factor
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    ABSTRACT: In this paper, the problem of the coexistence of two multiple-antenna wireless links is addressed in a cognitive radio scenario. The novelty brought by our setup is three-fold: First we consider a more realistic rate target constraint at the primary receiver instead of the less meaningful maximum interference temperature, second we propose a limited channel state information (CSI) structure whereby transmitters only have access to partly instantaneous feedback (i.e., about the direct channels) and partly statistical feedback (i.e., about the interference channels). Third, we formulate a distributed decision making scenario, by which channel information is not shared among primary and secondary transmitters. Instead, a transmitter must make a precoding decision based on local CSI only. The problem is recast as a team decision theoretic problem and the optimal precoders are obtained by solving semidefinite programs (SDPs). A distributed algorithm is derived and compared with classical precoding solutions and gains are illustrated over a range of scenarios.
    PIMRC 2013, IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), September 8-11, 2013, London, UK; 09/2013
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    ABSTRACT: In this work, we consider the use of interference alignment (IA) in a MIMO interference channel (IC) under the assumption that each transmitter (TX) has access to channel state information (CSI) that generally differs from that available to other TXs. This setting is referred to as distributed CSIT. In a setting where CSI accuracy is controlled by a set of power exponents, we show that in the static 3-user MIMO square IC, the number of degrees-of-freedom (DoF) that can be achieved with distributed CSIT is at least equal to the DoF achieved with the worst accuracy taken across the TXs and across the interfering links. We conjecture further that this represents exactly the DoF achieved. This result is in strong contrast with the centralized CSIT configuration usually studied (where all the TXs share the same, possibly imperfect, channel estimate) for which it was shown that the DoF achieved at receiver (RX) i is solely limited by the quality of its own feedback. This shows the critical impact of CSI discrepancies between the TXs, and highlights the price paid by distributed precoding.
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    Dataset: JSAC.bib
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    Paul de Kerret, David Gesbert
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    ABSTRACT: In this work, we study the problem of the optimal dissemination of channel state information (CSI) among K spatially distributed transmitters (TXs) jointly cooperating to serve K receivers (RXs). One of the particularities of this work lies in the fact that the CSI is distributed in the sense that each TX obtains its own estimate of the global multi-user MIMO channel with no further exchange of information being allowed between the TXs. Although this is well suited to model the cooperation between non-colocated TXs, e.g., in cellular Coordinated Multipoint (CoMP) schemes, this type of setting has received little attention so far in the information theoretic society. We study in this work what are the CSI requirements at every TX, as a function of the network geometry, to ensure that the maximal number of degrees-of-freedom (DoF) is achieved, i.e., the same DoF as obtained under perfect CSI at all TXs. We advocate the use of the generalized DoF to take into account the geometry of the network in the analysis. Consistent with the intuition, the derived DoF maximizing CSI allocation policy suggests that TX cooperation should be limited to a specific finite neighborhood around each TX. This is in sharp contrast with the conventional (uniform) CSI dissemination policy which induces CSI requirements that grow unbounded with the network size. The proposed CSI allocation policy suggests an alternative to clustering which overcomes fundamental limitations such as (i) edge interference and (ii) unbounded increase of the CSIT requirements with the cluster size. Finally, we show how finite neighborhood CSIT exchange translates into finite neighborhood message exchange so that finally global interference management is possible with only local cooperation
    IEEE Transactions on Information Theory 02/2013; · 2.65 Impact Factor
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    Paul de Kerret, David Gesbert
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    ABSTRACT: Multiple-antenna "based" transmitter (TX) cooperation has been established as a promising tool towards avoiding, aligning, or shaping the interference resulting from aggressive spectral reuse. The price paid in the form of feedback and exchanging channel state information (CSI) between cooperating devices in most existing methods is often underestimated however. In reality, feedback and information overhead threatens the practicality and scalability of TX cooperation approaches in dense networks. Hereby we addresses a "Who needs to know what?" problem, when it comes to CSI at cooperating transmitters. A comprehensive answer to this question remains beyond our reach and the scope of this paper. Nevertheless, recent results in this area suggest that CSI overhead can be contained for even large networks provided the allocation of feedback to TXs is made non-uniform and to properly depend on the network's topology. This paper provides a few hints toward solving the problem.
    IEEE Wireless Communications 02/2013; · 6.52 Impact Factor
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    Paul de Kerret, Xinping Yi, David Gesbert
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    ABSTRACT: The Degrees of Freedom (DoF) of a K-User MISO Broadcast Channel (BC) is studied when the Transmitter (TX) has access to a delayed channel estimate in addition to an imperfect estimate of the current channel. The current estimate could be for example obtained from prediction applied on past estimates, in the case where feedback delay is within the coherence time. Building on previous recent works on this setting with two users, the estimation error of the current channel is characterized by its scaling as P at the exponent \alpha, where \alpha=1 (resp. \alpha=0) corresponds to an estimate being essentially perfect (resp. useless) in terms of DoF. In this work, we contribute to the characterization of the DoF region in such a setting by deriving an outerbound for the DoF region and by providing an achievable DoF region. The achievable DoF is obtained by developing a new alignment scheme, called the K\alpha-MAT scheme, which builds upon both the principle of the MAT alignment scheme from Maddah-Ali and Tse and Zero-Forcing to achieve a larger DoF when the delayed CSIT received is correlated with the instantaneous channel state.
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    ABSTRACT: The uplink of the two-user multiple-antenna interference channel is considered and the optimal (in the ergodic rate sense) beamforming (BF) problem is posed and solved. Specifically, a feedback scenario is studied whereby a base station (BS) is allowed to estimate the instantaneous channel vector information from the users it serves, but not from out-of-cell interference users. That is to say, only statistical information can be obtained regarding the interference. In contrast with most previous works, the motivation behind the presumed feedback scenario is the compliance with current cellular network standards. For this scenario, we derive new expressions for the ergodic user rates. Exploiting the derived expressions, the optimal, with respect to ergodic rate maximization, receive BF vectors are found in closed form. Finally, new user scheduling schemes are proposed, which exploit the derived BF solution and allow an efficient use of combined instantaneous and statistical information.
    VTC 2013-Spring, IEEE 77th Vehicular Technology Conference, 2-5 June 2013, Dresden, Germany; 01/2013
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    ABSTRACT: This work considers the benefits of allowing spectrum sharing among co-located wireless service providers operating in the same multicell network. Although spectrum sharing was shown to be valuable in some scenarios where the created interference can be eliminated, the benefits have not clearly shown for multicell networks with aggressive reuse. We explore this question and show that spectrum sharing is preferred for just a certain subset of the users defined by their distance from the serving bases, while beyond this distance, an orthogonal division of resources between operators gives better results. The claims are backed with theoretical analysis matching our simulations
    Vehicular Technology Conference (VTC Spring), 2013 IEEE 77th; 01/2013
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    ABSTRACT: In this paper, two new power policies (PPs), namely the Rate Maximization Policy (RMP) and the Rate-Bound Maximization Policy (RBMP), for Cognitive Radio (CR) systems are developed based on an expected rate maximization criterion. Both policies are designed such as to satisfy a constraint related to the average interference caused by the CR network to primary communication. The key novelty here is that the proposed PPs take into account the existence of limited (hybrid) channel feedback, where the direct secondary channel is known instantaneously while the interference caused by the primary transmission to the secondary receiver is only known statistically. The optimal policy (RMP) is characterized, and a low complexity algorithm is presented that allows for its efficient and accurate implementation. The two policies are compared and RMP is shown to lead to substantial energy consumption savings at equal rate performance.
    Personal Indoor and Mobile Radio Communications (PIMRC), 2013 IEEE 24th International Symposium on; 01/2013
  • P. de Kerret, J. Hoydis, D. Gesbert
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    ABSTRACT: We consider in this work the problem of determining the number of feedback bits which should be used to quantize the channel state information (CSI) in a broadcast channel (BC) with K transmit antennas (or equivalently K single-antenna transmitters (TXs)) and K single-antenna receivers (RXs). We focus on an extension of the conventional centralized CSI at the TX (CSIT) model, where instead of having a single channel estimate, or quantized version, perfectly shared by all the TX antennas, each TX receives its own estimate of the global multiuser channel. This CSIT configuration, denoted as distributed CSIT, is particularly suited to model the joint transmission from TXs which are not colocated. With centralized CSIT, a very important design guideline for the feedback link was provided by Jindal [Trans. Inf. Theory 2006] by providing a sufficient feedback rate to ensure that the rate loss stays below a maximum value. In the distributed CSIT setting, additional errors occur and the design guidelines for the centralized case are no longer valid. Consequently, we obtain a new relation between the rate loss and the number of feedback bits. Interestingly, the feedback rate derived in the distributed CSIT setting is roughly K log2(K) bits larger than its counterpart in the centralized case. This highlights the critical impact of the CSIT distributedness over the performance.
    Signal Processing Advances in Wireless Communications (SPAWC), 2013 IEEE 14th Workshop on; 01/2013
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    ABSTRACT: Pilot contamination is known to severely limit the performance of large-scale antenna (“massive MIMO”) systems due to degraded channel estimation. This paper proposes a twofold approach to this problem. First we show analytically that pilot contamination can be made to vanish asymptotically in the number of antennas for a certain class of channel fading statistics. The key lies in setting a suitable condition on the second order statistics for desired and interference signals. Second we show how a coordinated user-to-pilot assignment method can be devised to help fulfill this condition in practical networks. Large gains are illustrated in our simulations for even small antenna array sizes.
    ICC 2013, IEEE International Conference on Communications, 9-13 June 2013, Budapest, Hungary; 01/2013
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    ABSTRACT: The two-user Multiple-Input Multiple-Output (MIMO) broadcast channel (BC) with arbitrary antenna configuration is considered, in which the transmitter obtains (i) delayed channel state information (CSI) from a latency-prone feedback channel as well as (ii) imperfect current CSI, e.g., from prediction based on these past channel samples. The degrees of freedom (DoF) region under such a setting is fully characterized as a function of a prediction quality exponent. This work extends prior work, previously limited to MISO, to fully general antenna settings. An intriguing by-product of our results is to reveal the benefits of dealing with an asymmetric multi-user MIMO configuration (i.e., one in which terminals do not have the same number of antennas) in the case of non-perfect CSIT (e.g., caused by feedback delays or limited preciseness).
    Information Theory Proceedings (ISIT), 2013 IEEE International Symposium on; 01/2013

Publication Stats

8k Citations
237.44 Total Impact Points


  • 2011
    • Massachusetts Institute of Technology
      Cambridge, Massachusetts, United States
    • Vienna University of Technology
      • Institute of Telecommunications
      Wien, Vienna, Austria
  • 2006–2011
    • University of Nice-Sophia Antipolis
      Nice, Provence-Alpes-Côte d'Azur, France
  • 2010
    • KTH Royal Institute of Technology
      • ACCESS Linnaeus Centre
      Stockholm, Stockholm, Sweden
  • 1995–2009
    • France Télécom
      Lutetia Parisorum, Île-de-France, France
  • 2008
    • Philips
      Eindhoven, North Brabant, Netherlands
    • University of Texas at Austin
      Austin, Texas, United States
    • Purdue University
      • School of Electrical and Computer Engineering
      West Lafayette, IN, United States
    • Institut de France
      Lutetia Parisorum, Île-de-France, France
  • 2006–2008
    • Institut Mines-Télécom
      • Department of Mobile Communications
      Biot, Provence-Alpes-Cote d'Azur, France
  • 2005–2008
    • Norwegian University of Science and Technology
      • Department of Electronics and Telecommunications (IET)
      Trondheim, Sor-Trondelag Fylke, Norway
  • 2002–2008
    • University of Oslo
      • Department of Informatics
      Oslo, Oslo, Norway
    • University of Illinois, Urbana-Champaign
      • Coordinated Science Laboratory
      Urbana, IL, United States
  • 2007
    • Tai Sophia Institute
      Maryland City, Maryland, United States
    • CTTC Catalan Telecommunications Technology Centre
      Barcino, Catalonia, Spain
  • 2004
    • University Graduate Center at Kjeller (UNIK)
      Kristiania (historical), Oslo County, Norway
  • 1997–2002
    • Stanford University
      • Information Systems Laboratory
      Stanford, CA, United States
  • 2000
    • Mountain View Pharmaceuticals, Inc.
      Menlo Park, California, United States
  • 1999
    • University of Leuven
      Louvain, Flanders, Belgium