W. Utschick

Technische Universität München, München, Bavaria, Germany

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Publications (285)212.41 Total impact

  • Source
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    ABSTRACT: This paper considers the partial decode-and-forward (PDF) strategy for the Gaussian multiple-input multiple-output (MIMO) relay channel. Unlike for the decode-and-forward (DF) strategy or point-to-point (P2P) transmission, for which Gaussian channel inputs are known to be optimal, the input distribution that maximizes the achievable PDF rate for the Gaussian MIMO relay channel has remained unknown so far. For some special cases, e.g., for relay channels where the optimal PDF strategy reduces to DF or P2P transmission, it could be deduced that Gaussian inputs maximize the PDF rate. For the general case, however, the problem has remained open until now. In this work, we solve this problem by proving that the maximum achievable PDF rate for the Gaussian MIMO relay channel is always attained by Gaussian channel inputs. Our proof relies on the channel enhancement technique, which was originally introduced by Weingarten et al. to derive the (private message) capacity region of the Gaussian MIMO broadcast channel. By combining this technique with a primal decomposition approach, we first establish that jointly Gaussian source and relay inputs maximize the achievable PDF rate for the aligned Gaussian MIMO relay channel. Subsequently, we use a limiting argument to extend this result from the aligned to the general Gaussian MIMO relay channel.
    09/2014;
  • Quan Kuang, Wolfgang Utschick, Andreas Dotzler
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    ABSTRACT: This paper studies the joint user association and resource allocation in heterogeneous networks (HetNets) from a novel perspective, motivated by and generating the idea of fractional frequency reuse. By treating the multi-cell multi-user resource allocation as resource partitioning among multiple reuse patterns, we propose a unified framework to analyze and compare a wide range of user association and resource allocation strategies for HetNets, and provide a benchmark of ultimate limit on network performance. The enabling mechanisms are a novel formulation to consider all possible patterns or any pre-defined subset of patterns and an efficient sparsity-pursuit algorithm. More importantly, in view of the fact that multi-cell resource allocation is very computational demanding, our framework provides a systematic way to trade off performance for the reduction of computational complexity by restricting the candidate patterns to a small number of feature patterns. Relying on the sparsity-pursuit capability of the proposed algorithm, we develop practical guideline to identify the feature patterns in the given HetNet. Our treatment is very general in that it covers the case where users are allowed to associate with multiple base stations and the more restrictive situation where the number of serving base stations for each user is limited to one or a given number. Numerical results show that the identified feature patterns can significantly improve the existing strategies, and jointly optimizing the user association and resource allocation indeed brings considerable gain.
    arXiv:1408.5091v1 [cs.NI]. 08/2014;
  • Samer Bazzi, Guido Dietl, Wolfgang Utschick
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    ABSTRACT: A non-iterative two-stage precoding scheme for the multiple-input-multiple-output interference channel (IC) with a large number of transmit antennas is presented. Second stage precoders are used to compress the channel state information (CSI) of interfering links, while keeping the multiplexing gain of the IC constant. First stage precoders zero-force the interference based on the compressed CSI of interfering links. In addition, a proper design of the second stage precoders forces the first stage precoders to span a reduced subspace containing the maximal direct links' power, resulting in a better zero-forcing solution in terms of sum-rate. For a fixed number of receive antennas and transmitter/receiver pairs, the required feedback amount of interfering links is constant, regardless of the number of transmit antennas. As cooperative algorithms are very sensitive to CSI errors, the proposed scheme offers an attractive solution in case CSI feedback constitutes the system bottleneck.
    2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM); 06/2014
  • M. Riemensberger, W. Utschick
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    ABSTRACT: We propose a new model for the wireless broadcast advantage based on a polymatroid structure. This model is a generalization of the predominating hypergraph model. The polymatroid structure yields a general max-flow min-cut characterization of multicast rate regions, which applies to a large variety of channel, physical layer, and medium access models. It includes the state-of-the-art hypergraph flow regions with lossless and lossy hyperarcs, i.e., Shannon rate models and packet erasure networks. Additionally, it generalizes to various other rate regions, e.g., the cut-set outer bounds for networks of a large variety of independent broadcast channels, including networks of independent Gaussian multiple-input multiple-output channels, and the capacity regions for networks of independent deterministic broadcast channels, which can in general not be modeled by the hypergraph flow model. We propose a dual decomposition approach for network utility optimization problems on the polymatroid broadcast flow region, which subsumes existing dual decomposition approaches based on lossless and lossy hypergraph flow regions. Our approach significantly simplifies the decomposition, especially for lossy hypergraph models in packet erasure networks, by fully exploiting the inherent polymatroid structure of the wireless broadcast. Additionally, it can be directly used to fully characterize and evaluate the cut-set bounds for networks of independent broadcast channels with polymatroid structure without previous knowledge about the relevant cuts.
    IEEE Transactions on Information Theory 01/2014; 60(1):443-460. · 2.62 Impact Factor
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    ABSTRACT: For Gaussian multiple-input multiple-output (MIMO) relay channels with partial decode-and-forward, the optimal type of input distribution is still an open question in general. Recent research has revealed that in some other scenarios with unknown optimal input distributions (e.g., interference channels), improper (i.e., noncircular) Gaussian distributions can outperform proper (circular) Gaussian distributions. In this paper, we show that this is not the case for partial decode-and-forward in the Gaussian MIMO relay channel with Gaussian transmit signals, i.e., we show that a proper Gaussian input distribution is the optimal one among all Gaussian distributions. In order to prove this property, an innovation covariance matrix is introduced, and a decomposition is performed by considering the optimization over this matrix as an outer problem. A key point for showing optimality of proper signals then is a reformulation that reveals that one of the subproblems is equivalent to a sum rate maximization in a two-user MIMO broadcast channel under a sum covariance constraint, for which the optimality of proper signals can be shown.
    IEEE Transactions on Signal Processing 01/2014; 62(12):3153-3164. · 2.81 Impact Factor
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    ABSTRACT: This paper presents a comparative study of algorithms for jointly optimizing beamformers and receive filters in an interference network, where each node may have multiple antennas, each user transmits at most one data stream, and interference is treated as noise. We focus on techniques that seek good suboptimal solutions by means of iterative and distributed updates. Those include forward-backward iterative algorithms (max-signal-to-interference-plus-noise ratio (SINR) and interference leakage), weighted sum mean-squared error (MSE) algorithms, and interference pricing with incremental signal-to-noise ratio (SNR) adjustments. We compare their properties in terms of convergence and information exchange requirements, and then numerically evaluate their sum rate performance averaged over random (stationary) channel realizations. The numerical results show that the max-SINR algorithm achieves the maximum degrees of freedom (i.e., supports the maximum number of users with near-zero interference) and exhibits better convergence behavior at high SNRs than the weighted sum MSE algorithms. However, it assumes fixed power per user and achieves only a single point in the rate region whereas the weighted sum MSE criterion gives different points. In contrast, the incremental SNR algorithm adjusts the beam powers and deactivates users when interference alignment is infeasible. Furthermore, that algorithm can provide a slight increase in sum rate, relative to max-SINR, at the cost of additional iterations.
    IEEE Transactions on Signal Processing 07/2013; 61(13):3476-3489. · 2.81 Impact Factor
  • Christoph Hellings, Stephan Herrmann, Wolfgang Utschick
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    ABSTRACT: Even though parallel multiple-input multiple-output (MIMO) broadcast channels are known to be separable from an information theoretic point of view, performing separate encoding and decoding on each of the parallel channels has been shown to be potentially suboptimal in broadcast channels with linear transceivers. In this paper, we show that suboptimality of such a carrier-noncooperative transmission also occurs in broadcast channels with zero-forcing and quality of service constraints if time-sharing is not allowed. The proof is given by constructing a minimal example and identifying a rate tuple that is achievable using carrier-cooperative zero-forcing with a certain sum power but requires a higher sum power with carrier-noncooperative zero-forcing. This observation is of practical relevance since zero-forcing without time-sharing is a popular assumption in the design of low-complexity optimization algorithms.
    IEEE Transactions on Signal Processing 06/2013; 61(12):3021-3027. · 2.81 Impact Factor
  • L. Gerdes, L. Weiland, W. Utschick
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    ABSTRACT: In this paper, we consider achievable rates for the Gaussian multiple-input multiple-output (MIMO) relay channel that can be obtained with the relay using the partial decode-and-forward scheme. The partial decode-and-forward strategy allows to optimize the amount of information the relay has to decode and can hence be seen as a generalization of the decode-and-forward strategy, where the relay must decode the entire source message. Since we cannot determine the maximal achievable partial decode-and-forward rate, we propose a suboptimal approach that is based on zero-forcing the interference the relay would suffer from the part of the source signal that it is not required to decode. For this purpose, a zero-forcing receive filter is introduced at the relay. We then show that, if the receive filter is fixed, standard convex optimization techniques can be used to evaluate the best rate our suboptimal partial decode-and-forward scheme can achieve. Simulation results demonstrate that the coding scheme we propose significantly outperforms the decode-and-forward scheme and/or approximates the cut-set bound for different network scenarios.
    Communications (ICC), 2013 IEEE International Conference on; 01/2013
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    ABSTRACT: We focus on a linear beamformer design in the downlink with statistical channel state information (CSI) at the transmitter, where the users' ergodic rates are balanced. Simplifying the fading channels to given vectors with random scalar factors, which is a good approximation for rural mobile or satellite communications (SatCom), the stochastic model mismatch is kept small albeit the ergodic rate structure now allows for adapting the perfect CSI balancing algorithms. Although there is no equivalent signal-to-interference-and-noise-ratio (SINR) reformulation for the ergodic constraints, tight inner approximations with SINR structure are found. Based on this observation, a locally optimal sequential approximation strategy is proposed and a fixed point based implementation is provided that requires only few iterations.
    Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on; 01/2013
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    ABSTRACT: In this work the problem of utility-based multiuser scheduling is considered in a fading environment. The goal is to make use of the multi-user diversity while still guaranteeing short-term fairness. The performance of a scheduler is captured by a utility function. Based on the utility function and assuming statistical knowledge of the time-varying channel the optimization problem for the optimal scheduler can be formulated. Based on the optimal scheduler various simplifications are proposed which use estimations of future system states. Simulations show the performance gain compared to state-of-the-art methods. Index Terms ?? opportunistic scheduling, predictive scheduling, multi-user diversity.
    Systems, Communication and Coding (SCC), Proceedings of 2013 9th International ITG Conference on; 01/2013
  • Christoph Hellings, Wolfgang Utschick
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    ABSTRACT: Optimization of transmit strategies with linear transceivers in multiple-input multiple-output (MIMO) broadcast channels generally leads to nonconvex problems, which cannot be solved efficiently in a globally optimal manner. Instead, it is necessary to resort to suboptimal algorithms. In this paper, we evaluate the application of a gradient descent algorithm for the optimization of the energy efficiency in such a system. Since the quality of the obtained locally optimal solutions depends on the initialization, a successive stream allocation is introduced and combined with the gradient algorithm. Comparison with a globally optimal reference algorithm for the special case of single receive antennas shows that the obtained solutions are close to the global optimum. For the MIMO case, the energy per bit achievable with dirty paper coding, which is a lower bound for the case of linear transceivers, is used as benchmark, and good performance of the gradient-based methods is shown for MIMO systems as well.
    Personal Indoor and Mobile Radio Communications (PIMRC), 2013 IEEE 24th International Symposium on; 01/2013
  • C. Hellings, W. Utschick
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    ABSTRACT: Proper Gaussian signals have been shown to be optimal in multiple-input multiple-output (MIMO) broadcast channels from an information theoretic point of view, i.e., capacity can be achieved with a strategy that transmits circularly symmetric complex Gaussian signals. In this work, we show that optimality of proper Gaussian signals does not necessarily hold if the transmit strategy is restricted to widely linear transceivers. The proof is performed by identifying a rate tuple that is achievable in a certain set of channels with widely linear transceivers and improper Gaussian signals, but lies outside the achievable rate region for widely linear transceivers and proper Gaussian signals.
    Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on; 01/2013
  • C. Hellings, W. Utschick
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    ABSTRACT: We consider the minimization of the energy per bit (or, equivalently, the maximization of the energy efficiency) in multiple-input multiple-output (MIMO) broadcast channels with rate balancing constraints for fairness between users, and we propose a framework to find the globally optimal energy-efficient solution, which relies on dirty paper coding (DPC). The main idea is to introduce a continuous, differentiable, and concave optimal rate function, which transforms the problem into a convex-concave fractional program in one scalar variable. This not only allows an efficient solution, but also an intuitive interpretation of the method as well as the possibility to extend the method to related problems. In numerical simulations, we compare the energy efficiency with and without fairness constraints.
    Signal Processing Advances in Wireless Communications (SPAWC), 2013 IEEE 14th Workshop on; 01/2013
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    ABSTRACT: We address the linear precoder design problem based on chance constrained quality-of-service (QoS) power minimization in the vector broadcast channel (BC). We divide the problem into a two step optimization that separates the precoder design from the power allocation. For the power allocation, we propose a map that fits into the framework of standard interference functions. Therefore, we can compute the optimal power allocation for given beamformers and detect whether a tuple of beamformers is feasible. This allows us to test conservative and non-conservative approaches for the beamformer design, e.g., a design based on a rank-one channel approximation is used. Numerical results show that the approximation is adequate for the non-conservative calculation approach, i.e., the postprocessing power allocation is capable of compensating for the suboptimal beamforming. Thereby, a wider range of rate targets is achieved than with the conservative beamformer designs.
    Signal Processing Advances in Wireless Communications (SPAWC), 2013 IEEE 14th Workshop on; 01/2013
  • L. Weiland, L. Gerdes, W. Utschick
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    ABSTRACT: In this paper, we consider achievable partial decode-and-forward (PDF) rates for the Gaussian multiple-input multiple-output (MIMO) relay channel. The PDF scheme generalizes the decode-and-forward (DF) scheme as it allows to optimize the amount of information that is transmitted in cooperation with the relay. For the Gaussian channel case, the optimal channel inputs for the PDF scheme are unknown, and even if Gaussian channel inputs are used, the resulting optimization problem (OP) is non-convex. Thus, suboptimal approaches are necessary in order to efficiently evaluate PDF rates. In this paper, we apply the so-called Inner Approximation Algorithm (IAA). By successively refining an approximation of the original OP, we are able to evaluate PDF rates by solving a sequence of convex OPs. Our simulation results show that these suboptimal PDF rates are able to outperform the rates achieved by point-to-point (P2P) transmission and the DF scheme. For scenarios where the source is equipped with more antennas than the relay, the suboptimal PDF rates even approach the cut-set bound (CSB).
    Signal Processing Advances in Wireless Communications (SPAWC), 2013 IEEE 14th Workshop on; 01/2013
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    ABSTRACT: For the vector broadcast channel (BC), the case of erroneous channel state information (CSI) at the receiver is considered. Employing a well established lower bound for the mutual information with Gaussian signaling, a rate balancing problem is formulated where the rates of the different users are maximized under a transmit power constraint, but the rates of the different users have fixed ratios. A duality w.r.t. the signal-to-interference-and-noise ratio (SINR) between the vector BC with erroneous receiver CSI and an appropriately constructed vector multiple access channel (MAC) is established. Based on the observation that an interference function can be defined in the dual vector MAC that is standard, an iterative algorithm can be found for an appropriately formulated quality-of-service (QoS) optimization that is used for solving the balancing problem.
    Information Sciences and Systems (CISS), 2013 47th Annual Conference on; 01/2013
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    ABSTRACT: In this paper we propose an end-to-end feedback mechanism for intra-session random linear network coding with opportunistic routing in wireless packet networks with lossy links. We focus on bidirectional network coding, i.e., forward and reverse flows between two nodes are coded together, which is key for efficient utilization of the wireless medium as it allows intermediate nodes to relay traffic in both directions with a single transmission. We analyze the performance in terms of decoding and acknowledgement times in a three-node network when nodes are fully backlogged. The results are compared to the theoretic lower bound obtained by solving the network's flow formulation. In addition, we derive symmetric injection rates from the these results which the network should be able to sustain. The evolution of source backlogs and decoding/acknowledgement over time are simulated, demonstrating that backlogs remain bounded. The insight gained will help in developing a generalized feedback model for coded wireless mesh networks, which is to the best of our knowledge an open problem.
    Personal Indoor and Mobile Radio Communications (PIMRC), 2013 IEEE 24th International Symposium on; 01/2013
  • C. Hellings, M. Joham, W. Utschick
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    ABSTRACT: The use of proper, i.e., circularly symmetric, complex Gaussian signals for all users is known to be optimal in broadcast channels with proper complex Gaussian noise from an information theoretic point of view, i.e., they are employed in the capacity-achieving strategy. However, such proper per-user transmit signals are not necessarily optimal for problems with quality-of-service (QoS) constraints if the transmit strategy is restricted to widely linear transceivers without time-sharing. This is shown by deriving the QoS feasibility region of the multiple-input multiple-output broadcast channel with improper Gaussian per-user transmit signals and widely linear transceivers.
    IEEE Signal Processing Letters 01/2013; 20(11):1134-1137. · 1.67 Impact Factor
  • C. Guthy, W. Utschick, M.L. Honig
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    ABSTRACT: We analyze the achievable sum rate of the Gaussian MIMO broadcast channel. We first consider Multiple-Input Single-Output (MISO) channels and derive the large system limit of the sum capacity as the number of users and transmit antennas go to infinity with a fixed ratio. We then consider Multiple-Input Multiple-Output (MIMO) broadcast channels and fix the number of users and let the number of transmit and receive antennas tend to infinity with fixed ratio. As in this case an asymptotic expression for sum capacity is hard to obtain, we evaluate the large system sum rate corresponding to successive zero-forcing beamforming with Dirty-Paper Coding. The analysis gives a lower bound on the large system sum capacity, which is numerically observed to be quite close. In addition, large system analysis is applied to estimate the relatively small performance losses with respect to sum capacity of successive zero-forcing beamforming with and without Dirty-Paper Coding in finite MISO systems.
    IEEE Journal on Selected Areas in Communications 01/2013; 31(2):149-159. · 3.12 Impact Factor
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    ABSTRACT: We consider wireless multihop networks with intrasession network coding and advanced physical layer techniques. In particular, we study the influence of multiuser decoding at receivers on the network utility maximization problem. To this end, we combine the polymatroid broadcast function model with the Gaussian compound multiple access channel (MAC) to model the information flow when multiple receivers decode messages from multiple transmitters. For this model, we formulate a network utility maximization problem and use a dual decomposition approach to separate the polymatroid flow subproblem, the scheduling and decoding assignment subproblem, and the compound MAC physical layer subproblem. The polymatroid flow and the compound MAC subproblems can be significantly simplified by exploiting their inherent polymatroid structure. For the scheduling and decoding assignment problem, we discuss the optimal solution, which results in an exhaustive search, and a simple greedy heuristic. In numerical simulations, we show a significant gain in network utility due to the advanced receiver capabilities compared to simple receivers.
    Systems, Communication and Coding (SCC), Proceedings of 2013 9th International ITG Conference on; 01/2013

Publication Stats

2k Citations
212.41 Total Impact Points

Institutions

  • 1999–2014
    • Technische Universität München
      • • Department of Signal Processing Methods
      • • Department of Circuit Theory and Signal Processing
      München, Bavaria, Germany
  • 2011
    • Mondragon Unibertsitatea
      Mondragón, Basque Country, Spain
  • 2005–2011
    • DOCOMO Euro-Labs
      München, Bavaria, Germany
  • 2010
    • German Aerospace Center (DLR)
      • Institute of Communications and Navigation
      Köln, North Rhine-Westphalia, Germany
  • 2009
    • Northwestern University
      • Department of Electrical Engineering and Computer Science
      Evanston, IL, United States
  • 2008
    • University of Oulu
      • Centre for Wireless Communications (CWC)
      Uleoborg, Oulu, Finland
  • 2007
    • University of A Coruña
      • Department of Electronics and Systems
      La Corogne, Galicia, Spain
  • 2006
    • Fraunhofer Heinrich-Hertz-Institute HHI
      Berlín, Berlin, Germany
  • 2004
    • The Hong Kong University of Science and Technology
      Chiu-lung, Kowloon City, Hong Kong