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David Gesbert

Publications and source records attributed to David Gesbert.

At least 109 records · Page 6Linked to original sources

Degrees of Freedom of Certain Interference Alignment Schemes with Distributed CSIT

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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CSI Sharing Strategies for Transmitter Cooperation in Wireless Networks

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.

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On the Degrees of Freedom of the K-User Time Correlated Broadcast Channel with Delayed CSIT

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 α, where α=1 (resp. α=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 Kα-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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The DoF of Network MIMO with Backhaul Delays

We consider the problem of downlink precoding for Network (multi-cell) MIMO networks where Transmitters (TXs) are provided with imperfect Channel State Information (CSI). Specifically, each TX receives a delayed channel estimate with the delay being specific to each channel component. This model is particularly adapted to the scenarios where a user feeds back its CSI to its serving base only as it is envisioned in future LTE networks. We analyze the impact of the delay during the backhaul-based CSI exchange on the rate performance achieved by Network MIMO. We highlight how delay can dramatically degrade system performance if existing precoding methods are to be used. We propose an alternative robust beamforming strategy which achieves the maximal performance, in DoF sense. We verify by simulations that the theoretical DoF improvement translates into a performance increase at finite Signal-to-Noise Ratio (SNR) as well.

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A Coordinated Approach to Channel Estimation in Large-scale Multiple-antenna Systems

This paper addresses the problem of channel estimation in multi-cell interference-limited cellular networks. We consider systems employing multiple antennas and are interested in both the finite and large-scale antenna number regimes (so-called "massive MIMO"). Such systems deal with the multi-cell interference by way of per-cell beamforming applied at each base station. Channel estimation in such networks, which is known to be hampered by the pilot contamination effect, constitute a major bottleneck for overall performance. We present a novel approach which tackles this problem by enabling a low-rate coordination between cells during the channel estimation phase itself. The coordination makes use of the additional second-order statistical information about the user channels, which are shown to offer a powerful way of discriminating across interfering users with even strongly correlated pilot sequences. Importantly, we demonstrate analytically that in the large-number-of-antennas regime, the pilot contamination effect is made to vanish completely under certain conditions on the channel covariance. Gains over the conventional channel estimation framework are confirmed by our simulations for even small antenna array sizes.

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Degrees of Freedom of Time Correlated MISO Broadcast Channel with Delayed CSIT

We consider the time correlated multiple-input single-output (MISO) broadcast channel where the transmitter has imperfect knowledge on the current channel state, in addition to delayed channel state information. By representing the quality of the current channel state information as P^-α for the signal-to-noise ratio P and some constant α \geq 0, we characterize the optimal degree of freedom region for this more general two-user MISO broadcast correlated channel. The essential ingredients of the proposed scheme lie in the quantization and multicasting of the overheard interferences, while broadcasting new private messages. Our proposed scheme smoothly bridges between the scheme recently proposed by Maddah-Ali and Tse with no current state information and a simple zero-forcing beamforming with perfect current state information.

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Precoding Methods for MISO Broadcast Channel with Delayed CSIT

Recent information theoretic results suggest that precoding on the multi-user downlink MIMO channel with delayed channel state information at the transmitter (CSIT) could lead to data rates much beyond the ones obtained without any CSIT, even in extreme situations when the delayed channel feedback is made totally obsolete by a feedback delay exceeding the channel coherence time. This surprising result is based on the ideas of interference repetition and alignment which allow the receivers to reconstruct information symbols which canceling out the interference completely, making it an optimal scheme in the infinite SNR regime. In this paper, we formulate a similar problem, yet at finite SNR. We propose a first construction for the precoder which matches the previous results at infinite SNR yet reaches a useful trade-off between interference alignment and signal enhancement at finite SNR, allowing for significant performance improvements in practical settings. We present two general precoding methods with arbitrary number of users by means of virtual MMSE and mutual information optimization, achieving good compromise between signal enhancement and interference alignment. Simulation results show substantial improvement due to the compromise between those two aspects.

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Degrees of Freedom of the Network MIMO Channel With Distributed CSI

In this work, we discuss the joint precoding with finite rate feedback in the so-called network MIMO where the TXs share the knowledge of the data symbols to be transmitted. We introduce a distributed channel state information (DCSI) model where each TX has its own local estimate of the overall multi-user MIMO channel and must make a precoding decision solely based on the available local CSI. We refer to this channel as the DCSI-MIMO channel and the precoding problem as distributed precoding. We extend to the DCSI setting the work from Jindal for the conventional MIMO Broadcast Channel (BC) in which the number of Degrees of Freedom (DoFs) achieved by Zero Forcing (ZF) was derived as a function of the scaling in the logarithm of the Signal-to-Noise Ratio (SNR) of the number of quantizing bits. Particularly, we show the seemingly pessimistic result that the number of DoFs at each user is limited by the worst CSI across all users and across all TXs. This is in contrast to the conventional MIMO BC where the number of DoFs at one user is solely dependent on the quality of the estimation of his own feedback. Consequently, we provide precoding schemes improving on the achieved number of DoFs. For the two-user case, the derived novel precoder achieves a number of DoFs limited by the best CSI accuracy across the TXs instead of the worst with conventional ZF. We also advocate the use of hierarchical quantization of the CSI, for which we show that considerable gains are possible. Finally, we use the previous analysis to derive the DoFs optimal allocation of the feedback bits to the various TXs under a constraint on the size of the aggregate feedback in the network, in the case where conventional ZF is used.

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The DoF Region of the Multiple-Antenna Time Correlated Interference Channel with Delayed CSIT

We consider the time-correlated multiple-antenna interference channel where the transmitters have (i) delayed channel state information (CSI) obtained from a latency-prone feedback channel as well as (ii) imperfect current CSIT, obtained e.g. from prediction on the basis of these past channel samples. We derive the degrees of freedom (DoF) region for the two-user multiple-antenna interference channel under such conditions. The proposed DoF achieving scheme exploits a particular combination of the space-time alignment protocol designed for fully outdated CSIT feedback channels (initially developed for the broadcast channel by Maddah-Ali et al, later extended to the interference channel by Vaze et al. and Ghasemi et al.) together with the use of simple zero-forcing (ZF) precoders. The essential ingredient lies in the quantization and feedback of the residual interference left after the application of the initial imperfect ZF precoder. Our focus is on the MISO setting albeit extensions to certain MIMO cases are also considered.

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On the Degrees of Freedom of time correlated MISO broadcast channel with delayed CSIT

We consider the time correlated MISO broadcast channel where the transmitter has partial knowledge on the current channel state, in addition to delayed channel state information (CSI). Rather than exploiting only the current CSI, as the zero-forcing precoding, or only the delayed CSI, as the Maddah-Ali-Tse (MAT) scheme, we propose a seamless strategy that takes advantage of both. The achievable degrees of freedom of the proposed scheme is characterized in terms of the quality of the current channel knowledge.

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Towards Optimal CSI Allocation in Multicell MIMO Channels

In this work, we consider the joint precoding across K transmitters (TXs), sharing the knowledge of the user's data symbols to be transmitted towards K single-antenna receivers (RXs). We consider a distributed channel state information (DCSI) configuration where each TX has its own local estimate of the overall multiuser MIMO channel. The focus of this work is on the optimization of the allocation of the CSI feedback subject to a constraint on the total sharing through the backhaul network. Building upon the Wyner model, we derive a new approach to allocate the CSI feedback while making efficient use of the pathloss structure to reduce the amount of feedback necessary. We show that the proposed CSI allocation achieves good performance with only a number of CSI bits per TX which does not scale with the number of cooperating TXs, thus making the joint transmission from a large number of TXs more practical than previously thought. Indeed, the proposed CSI allocation reduces the cooperation to a local scale, which allows also for a reduced allocation of the user's data symbols. We further show that the approach can be extended to a more general class of channel: the exponentially decaying channels, which model accuratly the cooperation of TXs located on a one dimensional space. Finally, we verify by simulations that the proposed CSI allocation leads to very little performance losses.

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Interference Two-Way Relay Channel with Three End-nodes

In this paper, we study a communication system consisting of three end-nodes, e.g. a single transceiver base station (BS), one transmitting and one receiving user equipments (UEs), and a common two-way relay node (RN) wherein the full-duplex BS transmits to the receiving UE in downlink direction and receives from the transmitting UE in uplink direction with the help of the intermediate full-duplex RN. We call this system model as interference two-way relay channel (ITWRC) with three end-nodes. Information theoretic bounds corresponding this system model are derived and analyzed so as to better understand the potentials of exploiting RN in future communication systems. Specifically, achievable rate regions corresponding to decode-and-forward (DF) relaying with and without rate splitting, and partial-DF and compress-and-forward (pDF+CF) relaying strategies are derived.

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Optimized data sharing in multicell MIMO with finite backhaul capacity

This paper addresses cooperation in a multicell environment where base stations (BSs) wish to jointly serve multiple users, under a constrained-capacity backhaul. We point out that for finite backhaul capacity a trade-off between sharing user data, which allows for full MIMO cooperation, and not doing so, which reduces the setup to an interference channel but also requires less overhead, emerges. We optimize this trade-off by formulating a rate splitting approach in which non-shared data (private to each transmitter) and shared data are superposed. We derive the corresponding achievable rate region and obtain the optimal beamforming design for both shared and private symbols. We show how the capacity of the backhaul can be used to determine how much of the user data is worth sharing across multiple BSs, particularly depending on how strong the interference is.

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Balancing Egoism and Altruism on MIMO Interference Channel

This paper considers the so-called multiple-input-multiple-output interference channel (MIMO-IC) which has relevance in applications such as multi-cell coordination in cellular networks as well as spectrum sharing in cognitive radio networks among others. We consider a beamforming design framework based on striking a compromise between beamforming gain at the intended receiver (Egoism) and the mitigation of interference created towards other receivers (Altruism). Combining egoistic and altruistic beamforming has been shown previously in several papers to be instrumental to optimizing the rates in a multiple-input-single-output interference channel MISO-IC (i.e. where receivers have no interference canceling capability). Here, by using the framework of Bayesian games, we shed more light on these game-theoretic concepts in the more general context of MIMO channels and more particularly when coordinating parties only have channel state information (CSI) of channels that they can measure directly. This allows us to derive distributed beamforming techniques. We draw parallels with existing work on the MIMO-IC, including rate-optimizing and interference-alignment precoding techniques, showing how such techniques may be improved or re-interpreted through a common prism based on balancing egoistic and altruistic beamforming. Our analysis and simulations currently limited to single stream transmission per user attest the improvements over known interference alignment based methods in terms of sum rate performance in the case of so-called asymmetric networks.

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Balancing Egoism and Altruism on the Interference Channel: The MIMO case

This paper considers the so-called MIMO interference channel. This situation has relevance in applications such as multi-cell coordination in cellular networks as well as spectrum sharing in cognitive radio networks among others. We address the design of precoding (i.e. beamforming) vectors at each sender with the aim of striking a compromise between beamforming gain at the intended receiver (Egoism) and the mitigation of interference created towards other receivers (Altruism). Combining egoistic and altruistic beamforming has been shown previously to be instrumental to optimizing the rates in a MISO interference channel (i.e. where receivers have no interference canceling capability) . Here we explore these game-theoretic concepts in the more general context of MIMO channels and using the framework of Bayesian games, allowing us to derive (semi-)distributed precoding techniques. We draw parallels with existing work on the MIMO interference channel, including rate-optimizing and interference-alignement precoding techniques, showing how such techniques may be improved and re-interpretated through a common prism based on balancing egoistic and altruistic beamforming.

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Combining Training and Quantized Feedback in Multi-Antenna Reciprocal Channels

The communication between a multiple-antenna transmitter and multiple receivers (users) with either a single or multiple-antenna each can be significantly enhanced by providing the channel state information at the transmitter (CSIT) of the users, as this allows for scheduling, beamforming and multiuser multiplexing gains. The traditional view on how to enable CSIT has been as follows so far: In time-division duplexed (TDD) systems, uplink (UL) and downlink (DL) channel reciprocity allows the use of a training sequence in the UL direction, which is exploited to obtain an UL channel estimate. This estimate is in turn recycled in the next downlink slot. In frequency-division duplexed (FDD) systems, which lack the UL and DL reciprocity, the CSIT is provided via the use of a dedicated feedback link of limited capacity between the receivers and the transmitter. In this paper, we focus on TDD systems and put this classical approach in question. In particular, we show that the traditional TDD setup above fails to fully exploit the channel reciprocity in its true sense. In fact, we show that the system can benefit from a combined CSIT acquisition strategy mixing the use of limited feedback and that of a training sequence. This combining gives rise to a very interesting joint estimation and detection problem for which we propose two iterative algorithms. An outage rate based framework is also developed which gives the optimal resource split between training and feedback. We demonstrate the potential of this hybrid combining in terms of the improved CSIT quality under a global training and feedback resource constraint.

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Asymptotic Capacity and Optimal Precoding in MIMO Multi-Hop Relay Networks

A multi-hop relaying system is analyzed where data sent by a multi-antenna source is relayed by successive multi-antenna relays until it reaches a multi-antenna destination. Assuming correlated fading at each hop, each relay receives a faded version of the signal from the previous level, performs linear precoding and retransmits it to the next level. Using free probability theory and assuming that the noise power at relaying levels-- but not at destination-- is negligible, the closed-form expression of the asymptotic instantaneous end-to-end mutual information is derived as the number of antennas at all levels grows large. The so-obtained deterministic expression is independent from the channel realizations while depending only on channel statistics. Moreover, it also serves as the asymptotic value of the average end-to-end mutual information. The optimal singular vectors of the precoding matrices that maximize the average mutual information with finite number of antennas at all levels are also provided. It turns out that the optimal precoding singular vectors are aligned to the eigenvectors of the channel correlation matrices. Thus they can be determined using only the known channel statistics. As the optimal precoding singular vectors are independent from the system size, they are also optimal in the asymptotic regime.

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Asymptotic Capacity and Optimal Precoding Strategy of Multi-Level Precode & Forward in Correlated Channels

We analyze a multi-level MIMO relaying system where a multiple-antenna transmitter sends data to a multipleantenna receiver through several relay levels, also equipped with multiple antennas. Assuming correlated fading in each hop, each relay receives a faded version of the signal transmitted by the previous level, performs precoding on the received signal and retransmits it to the next level. Using free probability theory and assuming that the noise power at the relay levels - but not at the receiver - is negligible, a closed-form expression of the end-to-end asymptotic instantaneous mutual information is derived as the number of antennas in all levels grow large with the same rate. This asymptotic expression is shown to be independent from the channel realizations, to only depend on the channel statistics and to also serve as the asymptotic value of the end-to-end average mutual information. We also provide the optimal singular vectors of the precoding matrices that maximize the asymptotic mutual information : the optimal transmit directions represented by the singular vectors of the precoding matrices are aligned on the eigenvectors of the channel correlation matrices, therefore they can be determined only using the known statistics of the channel matrices and do not depend on a particular channel realization.

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