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  • 101.
    Bengtsson, Mats
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Jointly optimal downlink beamforming and base station assignment2001In: 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2001. Proceedings (ICASSP '01)  (Volume:5 ), IEEE conference proceedings, 2001, p. 2961-2964Conference paper (Refereed)
    Abstract [en]

    We present an algorithm that jointly determines the optimal downlink beamformers and the optimal assignment of each mobile to a base station. The optimality criterion is based on a systems perspective; provide sufficient quality of service for all users, transmitting as little excess power as possible. Since the algorithm is centralized and requires knowledge about all the channels in the system, it may be infeasible in a practical implementation. However, it provides the ultimate benchmark in system evaluations. Numerical examples show substantial gain compared to ordinary base station assignment.

  • 102.
    Bengtsson, Mats
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Robust and constrained downlink beamforming2000In: European Signal Processing Conference, 2000, no MarchConference paper (Refereed)
    Abstract [en]

    When antenna arrays are introduced in a cellular system, one critical aspect is the design of beamformers for downlink transmission. We extend a recently proposed strategy for optimal downlink beamforming to give increased robustness to channel uncertainties and to incorporate constraints on the dynamic range. The solution can be efficiently calculated using semidefinite optimization. In a few cases, the optimal solution is given by a time-varying beamformer. We explore the performance of these modified algorithms.

  • 103.
    Bengtsson, Mats
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing.
    A generalization of weighted subspace fitting to full-rank models2001In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 49, no 5, p. 1002-1012Article in journal (Refereed)
    Abstract [en]

    The idea of subspace fitting provides a popular framework for different applications of parameter estimation and system identification. Previously, some algorithms have been suggested based on similar ideas, for a sensor array processing problem where the underlying data model is not low rank. We show that two of these algorithms (DSPE and DISPARE) fail to give consistent estimates and introduce a general class of subspace fitting-like algorithms for consistent estimation of parameters from a possibly full-rank data model. The asymptotic performance is analyzed, and an optimally weighted algorithm is derived. The result gives a lower bound on the estimation performance for any estimator based on a low-rank approximation of the linear space spanned by the sample data. We show that in general, for full-rank data models, no subspace-based method can reach the Cramer-Rao lower bound (CRB)

  • 104.
    Bengtsson, Mats
    et al.
    KTH, Superseded Departments, Signals, Sensors and Systems.
    Ottersten, Björn
    KTH, Superseded Departments, Signals, Sensors and Systems.
    Low-complexity estimators for distributed sources2000In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 48, no 8, p. 2185-2194Article in journal (Refereed)
    Abstract [en]

    In antenna array applications, the propagation environment is often more complicated than the ordinarily assumed model of plane wavefronts. Here, a low-complexity algorithm is suggested for estimating both the DOA and the spread angle of a source subject to local scattering, using a uniform linear array. The parameters are calculated from the estimates obtained using a standard algorithm such as root-MUSIC to fit a two-ray model to the data. The algorithm is shown to give consistent estimates, and the statistical performance is studied analytically and through simulations

  • 105.
    Bengtsson, Mats
    et al.
    KTH, Superseded Departments, Signals, Sensors and Systems.
    Ottersten, Björn
    KTH, Superseded Departments, Signals, Sensors and Systems.
    On Approximating a Spatially Scattered Source with Two Point Sources1998In: Proceedings Nordic Signal Processing Symposium (NORSIG'98), 1998, p. 45-48Conference paper (Other academic)
  • 106.
    Bengtsson, Mats
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Signal Processing.
    Optimal Downlink BeamformingUsing Semidefinite Optimization1999In: Proc. of 37th Annual Allerton Conference on Communication,Control, and Computing, 1999, p. 987-996Conference paper (Other academic)
    Abstract [en]

    When using antenna arrays at the base station of a cellular system, one critical aspectis the transmission strategy. An optimal choice of beamformers for simultaneous transmissionto several co-channel users must be solved jointly for all users and base stations in anarea. We formulate an optimal transmit strategy and show how the solution can be calculatedefficiently using interior point methods for semidefinite optimization. The algorithmminimizes the total transmitted power under certain constraints to guarantee a specificquality of service. The method provides large flexibility in the choice of constraints andcan be extended to be robust to channel perturbations.

  • 107.
    Bengtsson, Mats
    et al.
    KTH, Superseded Departments, Signals, Sensors and Systems.
    Ottersten, Björn
    KTH, Superseded Departments, Signals, Sensors and Systems.
    Signal Waveform Estimation from Array Data in Angular Spread Environment1996In: 30:th Asilomar Conference on Signals, Systems & Computers, IEEE , 1996, p. 355-359Conference paper (Refereed)
    Abstract [en]

    We analyze different direction based signal copy algorithms for a model of angular spread caused by local scattering around each signal source. Optimal algorithms, in terms of signal to interference and noise ratio, are derived for both rapidly and slowly time varying angular spread and a low complexity an-hoc algorithm is suggested. Simulations show that these algorithms outperform traditional signal copy algorithms in terms of signalto interference and noise ratio as well as outage probability.

  • 108.
    Bengtsson, Mats
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Völcker, Björn
    KTH, Superseded Departments, Signals, Sensors and Systems.
    On the estimation of Azimuth distributions and Azimuth Spectra2001In: IEEE 54TH VEHICULAR TECHNOLOGY CONFERENCE, VTC FALL 2001, 2001, p. 1612-1615Conference paper (Refereed)
    Abstract [en]

    The increased popularity of array antennas for wireless communication, has inspired investigations of the spatio-temporal properties of the radio channel, among others the azimuthal shape of the scattering clusters. Based on a statistical analysis, we show that trying to estimate the shape of the scattering Is an ill-posed problem and that the heavy-tailed Power Azimuth Spectra reported in the literature may be an artifact stemming only from the measurement procedure.

  • 109. Berardinelli, G.
    et al.
    Zetterberg, Per
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Tonelli, O.
    Cattoni, A. F.
    Sørensen, T. B.
    Mogensen, P.
    An SDR architecture for OFDM transmission over USRP2 boards2011In: Conference Record: Asilomar Conference on Signals, Systems and Computers, 2011, p. 965-969Conference paper (Refereed)
    Abstract [en]

    The Universal Software Radio Peripheral (USRP) developed by Ettus research is emerging as one of the most promising hardware solution for building a Software Defined Radio (SDR) platform. Originally designed for supporting GNU radio, it can also be interfaced to customized C++ code, thus allowing a higher degree of flexibility in the design of the transceiver chain. In this paper we describe the implementation of a coded Orthogonal Frequency Division Multiplexing (OFDM) transceiver running over USRP2 boards. The baseband processing and the radio-frequency settings are designed for coping with a local area scenario as well as with the physical capabilities of the USRP2 boards. Moreover, a simple subcarrier blinding algorithm is proposed with the aim of compensating the common phase error in the symbol constellation due to the limited nominal accuracy of the local oscillators. Performance results show the effectiveness of the proposed architecture and settings for achieving Block Error Rate (BLER) results below 1% at 12 dB of Signal-to-Noise Ratio (SNR) without requiring a high precision reference clock.

  • 110.
    Bergman, Svante
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Lattice based linear precoding for MIMO block codes2007In: 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing, IEEE , 2007, p. 329-332Conference paper (Refereed)
    Abstract [en]

    Herein, the design of linear dispersion codes for block based multiple-input multiple-output communication systems is investigated. The receiver as well as the transmitter are assumed to have perfect knowledge of the channel, and the receiver is assumed to employ maximum likelihood detection. We propose to use linear precoding and lattice invariant operations to transform the channel matrix into a lattice with large coding gain. With appropriate approximations, it is shown that this corresponds to selecting lattices with good sphere packing properties. Lattice invariant transformations are then used to minimize the power consumption. An algorithm for this power minimization is presented along with a lower bound on the optimization. Numerical results indicate that there is a potential gain of several dB by using the method compared to channel inversion with adaptive bit loading.

  • 111.
    Bergman, Svante
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Lattice-based linear precoding for MIMO channels with transmitter CSI2008In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 56, no 7, p. 2902-2914Article in journal (Refereed)
    Abstract [en]

    Herein, the design of linear dispersion codes for multiple-input multiple-output communication systems is investigated. The receiver as well as the transmitter are assumed to have perfect knowledge of the channel, and the receiver is assumed to employ maximum likelihood detection. We propose to use linear precoding and lattice invariant operations to transform the channel matrix into a lattice generator matrix with large minimum distance separation. With appropriate approximations, it is shown that this corresponds to selecting lattices with good sphere-packing properties. Lattice invariant transformations are then used to minimize the power consumption. An algorithm for this power minimization is presented along with a lower bound on the optimization. Numerical results indicate significant gains by using the proposed method compared to channel diagonalization with adaptive bit loading.

  • 112.
    Bernal, Thomas
    KTH, School of Electrical Engineering (EES), Signal Processing.
    A Comparison of Kalman Filtering Techniques Applied to the Alignment Problem2015Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
  • 113. Bhavani Shankar Mysore, R.
    et al.
    Ottersten, Björn
    Effect of imperfect channel estimate on the performance of MMSE receivers in multibeam satellite systems: First order analysis2014In: 2014 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT), IEEE conference proceedings, 2014Conference paper (Refereed)
    Abstract [en]

    Aggressive frequency reuse in a multibeam satellite system offers wider bandwidths per beam at the cost of increased co-channel interference. Focussing on the return link of interactive mobile satellite systems, emphasis has been laid on Minimum Mean Squared Error (MMSE) receivers at the gateway to reduce the co-channel interference arising out of aggressive reuse. Performance of such receivers have been evaluated in presence of perfect channel information and synchronization showing impressive gains in throughput. Towards bringing such receivers closer to system implementation, this work aims at understanding the effect of imperfect channel estimates on the resulting performance. In particular, utilizing first order approximations, closed-form expressions for the MMSE receiver and the resulting Mean Squared Error (MSE) have been derived. These expressions provide insight into the effect of channel, noise levels and the estimation error on performance while indicating the robustness of MMSE receiver.

  • 114.
    Björk, Marcus
    et al.
    Dept. of IT, Uppsala University.
    Gudmundson, Erik
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Barral, Joelle K.
    Stanford University.
    Stoica, Petre
    Dept. of IT, Uppsala University.
    Signal processing algorithms for removing banding artifacts in MRI2011In: 19th European Signal Processing Conference (EUSIPCO), 2011, p. 1000-1004Conference paper (Refereed)
    Abstract [en]

    In magnetic resonance imaging (MRI), the balanced steady- state free precession (bSSFP) pulse sequence has shown to be of great interest, due to its relatively high signal-to-noise ratio in a short scan time. However, images acquired with this pulse sequence suffer from banding artifacts due to off- resonance effects. These artifacts typically appear as black bands covering parts of the image and they severely degrade the image quality. In this paper, we present a fast two-step algorithm for estimating the unknowns in the signal model and removing the banding artifacts. The first step consists of rewriting the model in such a way that it becomes linear in the unknowns (this step is named Linearization for Off- Resonance Estimation, or LORE). In the second step, we use a Gauss-Newton iterative optimization with the parameters obtained by LORE as initial guesses. We name the full al- gorithm LORE-GN. Using both simulated and in vivo data, we show the performance gain associated with using LORE- GN as compared to general methods commonly employed in similar cases.

  • 115.
    Björk, Marcus
    et al.
    Dept. of IT, Uppsala University.
    Ingle, R. Reeve
    Stanford University.
    Barral, Joelle K.
    Stanford University.
    Erik, Gudmundson
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Nishimura, Dwight G.
    Stanford University.
    Stoica, Petre
    Dept. of IT, Uppsala University.
    Optimality of Equally-Spaced Phase Increments for Banding Removal in bSSFP2012In: Proceedings 20th Scientific Meeting, International Society for Magnetic Resonance in Medicine (2012), 2012, p. 3380-3380Conference paper (Refereed)
  • 116.
    Björnson, Emil
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Bengtsson, Mats
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Pareto characterization of the multicell MIMO performance region with simple receivers2012In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 60, no 8, p. 4464-4469Article in journal (Refereed)
    Abstract [en]

    We study the performance region of a general multicell downlink scenario with multiantenna transmitters, hardware impairments, and low-complexity receivers that treat interference as noise. The Pareto boundary of this region describes all efficient resource allocations, but is generally hard to compute. We propose a novel explicit characterization that gives Pareto optimal transmit strategies using a set of positive parameters-fewer than in prior work. We also propose an implicit characterization that requires even fewer parameters and guarantees to find the Pareto boundary for every choice of parameters, but at the expense of solving quasi-convex optimization problems. The merits of the two characterizations are illustrated for interference channels and ideal network multiple-input multiple-output (MIMO).

  • 117.
    Björnson, Emil
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Hammarwall, David
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Beamforming utilizing channel norm feedback in multiuser MIMO systems2007In: IEEE Workshop on Signal Processing Advances in Wireless Communications, IEEE , 2007, Vol. SPAWC, p. 1-5Conference paper (Refereed)
    Abstract [en]

    The problem of beamforming and rate estimation in a multi-user downlink multiple-input multiple-output (MIMO) system with limited feedback and statistical channel information at the transmitter is considered. In order to exploit the spatial properties of the channel, the norm of the channel to each receive antenna is computed. We propose to feed back the largest norm to the transmitter and derive the conditional second and fourth order channel moments in order to design the downlink beamforming weights. Similar approaches have previously been presented for multi-user multiple-input single-output (MISO) systems. Herein, these techniques are generalized to MIMO systems, by either antenna selection or receive beamforming at the receiver. Two eigenbeamforming strategies are proposed and shown to outperform opportunistic beamforming, based on similar feedback information.

  • 118.
    Björnson, Emil
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Hammarwall, David
    Ericsson Research, Stockholm, Sweden.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Exploiting Quantized Channel Norm Feedback Through Conditional Statistics in Arbitrarily Correlated MIMO Systems2009In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 57, no 10, p. 4027-4041Article in journal (Refereed)
    Abstract [en]

    In the design of narrowband multi-antenna systems, a limiting factor is the amount of channel state information (CSI) available at the transmitter. This is especially evident in multi-user systems, where the spatial user separability determines the multi-plexing gain, but it is also important for transmission-rate adaptation in single-user systems. To limit the feedback load, the unknown and multi-dimensional channel needs to be represented by a limited number of bits. When combined with long-term channel statistics, the norm of the channel matrix has been shown to provide substantial CSI that permits efficient user selection, linear precoder design, and rate adaptation. Herein, we consider quantized feedback of the squared Frobenius norm in a Rayleigh fading environment with arbitrary spatial correlation. The conditional channel statistics are characterized and their moments are derived for both identical, distinct, and sets of repeated eigenvalues. These results are applied for minimum mean square error (MMSE) estimation of signal and interference powers in single- and multi-user systems, for the purpose of reliable rate adaptation and resource allocation. The problem of efficient feedback quantization is discussed and an entropy-maximizing framework is developed where the post-user-selection distribution can be taken into account in the design of the quantization levels. The analytic results of this paper are directly applicable in many widely used communication techniques, such as space-time block codes, linear precoding, space division multiple access (SDMA), and scheduling.

  • 119.
    Björnson, Emil
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Hammarwall, David
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Zakhour, Randa
    Institut Eurécom, 2229 route des crêtes, BP 193, F-06560, Sophia Antipolis, France.
    Bengtsson, Mats
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Gesbert, David
    Institut Eurécom, 2229 route des crêtes, BP 193, F-06560, Sophia Antipolis, France.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Feedback design in multiuser MIMO systems using quantization splitting and hybrid instantaneous/statistical channel information2008In: ICT-MobileSummit 2008 Conference Proceedings / [ed] Paul Cunningham and Miriam Cunningham, IIMC International Information Management Corporation , 2008, , p. 8Conference paper (Refereed)
    Abstract [en]

    In the design of next generation multiuser communication systems, multiple antenna transmission is an essential part providing spatial multiplexing gain and allowing efficient use of resources. A major limiting factor in the resource allocation is the amount of channel state information (CSI) available at the transmitter, particularly in multiuser systems where the feedback from each user terminal must be limited. To this effect we propose two independent approaches for an efficient representation of the channel in multiuser MIMO systems. In the first approach, channel quantization is considered where the total number of feedback bits is limited. A resource allocation scheme is proposed where the available rate is split between the scheduling phase, where all users feed back a coarse CSI quantization, and the precoding phase where the selected receivers refine their CSI. The optimum splitting of the available feedback rate provides a large increase in performance and even simple heuristic splitting gives a noticeable advantage. In the second approach, we exploit a combination of instantaneous and statistical channel information. For spatially correlated Rayleigh and Ricean channels, it is shown that the CSI to large extent can be represented by the channel norm when the long-term channel statistics are known. Within a minimum mean square error (MMSE) estimation framework, feedback of a few bits of the quantized channel norm is sufficient to perform efficient resource allocation and achieve performance close to that of full CSI.

  • 120.
    Björnson, Emil
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. Linköping University, Sweden.
    Hoydis, Jakob
    Kountouris, Marios
    Debbah, Merouane
    Massive MIMO Systems With Non-Ideal Hardware: Energy Efficiency, Estimation, and Capacity Limits2014In: IEEE Transactions on Information Theory, ISSN 0018-9448, E-ISSN 1557-9654, Vol. 60, no 11, p. 7112-7139Article in journal (Refereed)
    Abstract [en]

    The use of large-scale antenna arrays can bring substantial improvements in energy and/or spectral efficiency to wireless systems due to the greatly improved spatial resolution and array gain. Recent works in the field of massive multiple-input multiple-output (MIMO) show that the user channels decorrelate when the number of antennas at the base stations (BSs) increases, thus strong signal gains are achievable with little interuser interference. Since these results rely on asymptotics, it is important to investigate whether the conventional system models are reasonable in this asymptotic regime. This paper considers a new system model that incorporates general transceiver hardware impairments at both the BSs (equipped with large antenna arrays) and the single-antenna user equipments (UEs). As opposed to the conventional case of ideal hardware, we show that hardware impairments create finite ceilings on the channel estimation accuracy and on the downlink/uplink capacity of each UE. Surprisingly, the capacity is mainly limited by the hardware at the UE, while the impact of impairments in the large-scale arrays vanishes asymptotically and interuser interference (in particular, pilot contamination) becomes negligible. Furthermore, we prove that the huge degrees of freedom offered by massive MIMO can be used to reduce the transmit power and/or to tolerate larger hardware impairments, which allows for the use of inexpensive and energy-efficient antenna elements.

  • 121.
    Björnson, Emil
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Jorswieck, Eduard
    Dresden University of Technology, Communications Theory, Communications Laboratory, Dresden, Germany.
    Optimal Resource Allocation in Coordinated Multi-Cell Systems2013Book (Refereed)
    Abstract [en]

    The use of multiple antennas at base stations is a key component in the design of cellular communication systems that can meet high-capacity demands in the downlink. Under ideal conditions, the gain of employing multiple antennas is well-recognized: the data throughput increases linearly with the number of transmit antennas if the spatial dimension is utilized to serve many users in parallel. The practical performance of multi-cell systems is, however, limited by a variety of nonidealities, such as insufficient channel knowledge, high computational complexity, heterogeneous user conditions, limited backhaul capacity, transceiver impairments, and the constrained level of coordination between base stations.

    This tutorial presents a general framework for modeling different multi-cell scenarios, including clustered joint transmission, coordinated beamforming, interference channels, cognitive radio, and spectrum sharing between operators. The framework enables joint analysis and insights that are both scenario independent and dependent.

    The performance of multi-cell systems depends on the resource allocation; that is, how the time, power, frequency, and spatial resources are divided among users. A comprehensive characterization of resource allocation problem categories is provided, along with the signal processing algorithms that solve them. The inherent difficulties are revealed: (a) the overwhelming spatial degrees-of-freedom created by the multitude of transmit antennas; and (b) the fundamental tradeoff between maximizing aggregate system throughput and maintaining user fairness. The tutorial provides a pragmatic foundation for resource allocation where the system utility metric can be selected to achieve practical feasibility. The structure of optimal resource allocation is also derived, in terms of beamforming parameterizations and optimal operating points.

    This tutorial provides a solid ground and understanding for optimization of practical multi-cell systems, including the impact of the nonidealities mentioned above. The Matlab code is available online for some of the examples and algorithms in this tutorial.

    Note: The supplementary Matlab Code is available at http://dx.doi.org/10.1561/0100000069_supp

  • 122.
    Björnson, Emil
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. Alcatel-Lucent Chair on Flexible Radio, Supélec, France.
    Jorswieck, Eduard
    Dresden University of Technology, Communications Theory, Communications Laboratory, Dresden, Germany.
    Optimal Resource Allocation in Coordinated Multi-Cell Systems: Matlab Code2013Report (Other academic)
    Abstract [en]

    This is the documentation of the Matlab code supplement to the monograph "Optimal Resource Allocation in Coordinated Multi-Cell Systems" by Emil Björnson and Eduard Jorswieck; see [1] for the full publication details.

    This documentation is distributed along with the code package mentioned above. The package contains Matlab implementations of many of the algorithms described in [1]. The use of these algorithms is exemplified by Matlab scripts (m-files) that generate some of the figures shown in the monograph. The algorithms are briefly described in Section 5 and the selected example figures are described and shown in Section 6. Please note that the all channel vectors are generated randomly as Rayleigh fading in these examples, thus this code package is not able to reproduce exactly the same curves as was shown in the monograph.

  • 123.
    Björnson, Emil
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Jorswieck, Eduard A.
    Dresden University of Technology (TUD), Germany.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Impact of Spatial Correlation and Precoding Design in OSTBC MIMO Systems2010In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 9, no 11, p. 3578-3589Article in journal (Refereed)
    Abstract [en]

    The impact of transmission design and spatial correlation on the symbol error rate (SER) is analyzed for multi-antenna communication links. The receiver has perfect channel state information (CSI), while the transmitter has either statistical or no CSI. The transmission is based on orthogonal space-time block codes (OSTBCs) and linear precoding. The precoding strategy that minimizes the worst-case SER is derived for the case when the transmitter has no CSI. Based on this strategy, the intuitive result that spatial correlation degrades the SER performance is proved mathematically. In the case when the transmitter knows the channel statistics, the correlation matrix is assumed to be jointly-correlated (a generalization of the Kronecker model). The eigenvectors of the SER-optimal precoding matrix are shown to originate from the correlation matrix and the remaining power allocation is a convex problem. Equal power allocation is SER-optimal at high SNR. Beamforming is SER-optimal at low SNR, or for increasing constellation sizes, and its optimality range is characterized. A heuristic low-complexity power allocation is proposed and evaluated numerically. Finally, it is proved analytically that receive-side correlation always degrades the SER. Transmit-side correlation will however improve the SER at low to medium SNR, while its impact is negligible at high SNR.

  • 124.
    Björnson, Emil
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Jorswieck, Eduard
    Dresden University of Technology, Germany.
    Debbah, Merouane
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Multiobjective Signal Processing Optimization: The way to balance conflicting metrics in 5G systems2014In: IEEE signal processing magazine (Print), ISSN 1053-5888, E-ISSN 1558-0792, Vol. 31, no 6, p. 14-23Article in journal (Refereed)
    Abstract [en]

    The evolution of cellular networks is driven by the dream of ubiquitous wireless connectivity: any data service is instantly accessible everywhere. With each generation of cellular networks, we have moved closer to this wireless dream; first by delivering wireless access to voice communications, then by providing wireless data services, and recently by delivering a Wi-Fi-like experience with wide-area coverage and user mobility management. The support for high data rates has been the main objective in recent years [1], as seen from the academic focus on sum-rate optimization and the efforts from standardization bodies to meet the peak rate requirements specified in IMT-Advanced. In contrast, a variety of metrics/objectives are put forward in the technological preparations for fifth-generation (5G) networks: higher peak rates, improved coverage with uniform user experience, higher reliability and lower latency, better energy efficiency (EE), lower-cost user devices and services, better scalability with number of devices, etc. These multiple objectives are coupled, often in a conflicting manner such that improvements in one objective lead to degradation in the other objectives. Hence, the design of future networks calls for new optimization tools that properly handle the existence of multiple objectives and tradeoffs between them.

  • 125.
    Björnson, Emil
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Kountouris, Marios
    Bengtsson, Mats
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Receive Combining vs. Multi-Stream Multiplexing in Downlink Systems With Multi-Antenna Users2013In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 61, no 13, p. 3431-3446Article in journal (Refereed)
    Abstract [en]

    In downlink multi-antenna systems with many users, the multiplexing gain is strictly limited by the number of transmit antennas and the use of these antennas. Assuming that the total number of receive antennas at the multi-antenna users is much larger than, the maximal multiplexing gain can be achieved with many different transmission/reception strategies. For example, the excess number of receive antennas can be utilized to schedule users with effective channels that are near-orthogonal, for multi-stream multiplexing to users with well-conditioned channels, and/or to enable interference-aware receive combining. In this paper, we try to answer the question if the data streams should be divided among few users (many streams per user) or many users (few streams per user, enabling receive combining). Analytic results are derived to show how user selection, spatial correlation, heterogeneous user conditions, and imperfect channel acquisition (quantization or estimation errors) affect the performance when sending the maximal number of streams or one stream per scheduled user-the two extremes in data stream allocation. While contradicting observations on this topic have been reported in prior works, we show that selecting many users and allocating one stream per user (i.e., exploiting receive combining) is the best candidate under realistic conditions. This is explained by the provably stronger resilience towards spatial correlation and the larger benefit from multi-user diversity. This fundamental result has positive implications for the design of downlink systems as it reduces the hardware requirements at the user devices and simplifies the throughput optimization.

  • 126.
    Björnson, Emil
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. SUPELEC, France.
    Matthaiou, Michail
    Debbah, Mérouane
    Circuit-aware design of energy-efficient massive MIMO systems2014In: ISCCSP 2014 - 2014 6th International Symposium on Communications, Control and Signal Processing, Proceedings, 2014, p. 101-104Conference paper (Refereed)
    Abstract [en]

    Densification is a key to greater throughput in cellular networks. The full potential of coordinated multipoint (CoMP) can be realized by massive multiple-input multiple-output (MIMO) systems, where each base station (BS) has very many antennas. However, the improved throughput comes at the price of more infrastructure; hardware cost and circuit power consumption scale linearly/affinely with the number of antennas. In this paper, we show that one can make the circuit power increase with only the square root of the number of antennas by circuit-aware system design. To this end, we derive achievable user rates for a system model with hardware imperfections and show how the level of imperfections can be gradually increased while maintaining high throughput. The connection between this scaling law and the circuit power consumption is established for different circuits at the BS.

  • 127.
    Björnson, Emil
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    A Framework for Training-Based Estimation in Arbitrarily Correlated Rician MIMO Channels With Rician Disturbance2010In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 58, no 3, p. 1807-1820Article in journal (Refereed)
    Abstract [en]

    In this paper, we create a framework for training-based channel estimation under different channel and interference statistics. The minimum mean square error (MMSE) estimator for channel matrix estimation in Rician fading multi-antenna systems is analyzed, and especially the design of mean square error (MSE) minimizing training sequences. By considering Kronecker-structured systems with a combination of noise and interference and arbitrary training sequence length, we collect and generalize several previous results in the framework. We clarify the conditions for achieving the optimal training sequence structure and show when the spatial training power allocation can be solved explicitly. We also prove that spatial correlation improves the estimation performance and establish how it determines the optimal training sequence length. The analytic results for Kronecker-structured systems are used to derive a heuristic training sequence under general unstructured statistics. The MMSE estimator of the squared Frobenius norm of the channel matrix is also derived and shown to provide far better gain estimates than other approaches. It is shown under which conditions training sequences that minimize the non-convex MSE can be derived explicitly or with low complexity. Numerical examples are used to evaluate the performance of the two estimators for different training sequences and system statistics. We also illustrate how the optimal length of the training sequence often can be shorter than the number of transmit antennas.

  • 128.
    Björnson, Emil
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Exploiting long-term statistics in spatially correlated multi-user MIMO systems with quantized channel norm feedback2008In: 2008 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, IEEE , 2008, p. 3117-3120Conference paper (Refereed)
    Abstract [en]

    In wireless multiple antenna and multi-user systems, the spatial dimensions may be exploited to increase the performance by means of antenna gain, spatial diversity, and multi-user diversity. A limiting factor in such systems is the channel information required by the transmitter to control the intra-cell interference. Herein, the properties of spatially correlated channels with long-term statistical information at the transmitter and fixed-rate feedback of the quantized Euclidean channel norm are analyzed using a spectral subspace decomposition framework. A spatial division multiple access scheme is proposed with interference suppression at the receiver and joint scheduling and zero-forcing beamforming at the transmitter. Closed-form expressions for first and second order moments of the feedback conditional channel statistics are derived. It is shown that only a few bits of feedback are required to achieve reliable rate estimation and weighted sum-rate maximization.

  • 129.
    Björnson, Emil
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Training-based Bayesian MIMO channel and channel norm estimation2009In: 2009 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1- 8, PROCEEDINGS, IEEE , 2009, p. 2701-2704Conference paper (Refereed)
    Abstract [en]

    Training-based estimation of channel state information in multi-antenna systems is analyzed herein. Closed-form expressions for the general Bayesian minimum mean square error (MMSE) estimators of the channel matrix and the squared channel norm are derived in a Rayleigh fading environment with known statistics at the receiver side. When the second-order channel statistics are available also at the transmitter, this information can be exploited in the training sequence design to improve the performance. Herein, mean square error (MSE) minimizing training sequences are considered. The structure of the general solution is developed, with explicit expressions at high and low SNRs and in the special case of uncorrelated receive antennas. The optimal length of the training sequence is equal or smaller than the number of transmit antennas.

  • 130.
    Björnson, Emil
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Jorswieck, Eduard
    Communication Theory, Communications Laboratory, Dresden University of Technology, D-01062 Dresden, Germany.
    On the impact of spatial correlation and precoder design on the performance of MIMO systems with space-time coding2009In: 2009 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1- 8, PROCEEDINGS, IEEE , 2009, p. 2741-2744Conference paper (Refereed)
    Abstract [en]

    The symbol error performance of spatially correlated multi-antenna systems is analyzed herein. When the transmitter only has statistical channel information, the use of space-time block codes still permits spatial multiplexing and mitigation of fading. The statistical information can be used for precoding to optimize some quality measure. Herein, we analyze the performance in terms of the symbol error rate (SER). It is shown analytically that spatial correlation at the receiver decreases the performance both without precoding and with an SER minimizing precoder. Without precoding, correlation should also be avoided at the transmitter side, but with an SER minimizing precoder the performance is actually improved by increasing spatial correlation at the transmitter. The structure of the optimized precoder is analyzed and the asymptotic properties at high and low SNRs are characterized and illustrated numerically.

  • 131.
    Björnson, Emil
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Papadogiannis, A.
    Matthaiou, M.
    Debbah, M.
    On the impact of transceiver impairments on af relaying2013In: ICASSP IEEE Int Conf Acoust Speech Signal Process Proc, 2013, p. 4948-4952Conference paper (Refereed)
    Abstract [en]

    Recently, it was shown that transceiver hardware impairments have a detrimental impact on the performance of communication systems, especially for high-rate systems. The vast majority of technical contributions in the area of relaying assume ideal transceiver hardware. This paper quantifies the impact of transceiver hardware impairments in dual-hop Amplify-and-Forward (AF) relaying, both for fixed and variable gain relays. The outage probability (OP) in this practical scenario is a function of the instantaneous end-to-end signal-to-noise-and-distortion ratio (SNDR). This paper derives closed-form expressions for the exact and asymptotic OPs under Rayleigh fading, accounting for hardware impairments at both the transmitter and the relay. The performance loss is small at low spectral efficiency, but can otherwise be very substantial. In particular, it turns out that for high signal-to-noise ratio (SNR), the instantaneous end-to-end SNDR converges to a deterministic constant, called the SNDR ceiling, which is inversely proportional to the level of impairments. This stands in stark contrast to the ideal hardware case for which the end-to-end SNDR grows without bound in the high SNR regime.

  • 132.
    Björnson, Emil
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Sanguinetti, L.
    Hoydis, J.
    Debbah, M.
    Designing multi-user MIMO for energy efficiency: When is massive MIMO the answer?2014In: IEEE Wireless Communications and Networking Conference, WCNC, 2014, p. 242-247Conference paper (Refereed)
    Abstract [en]

    Assume that a multi-user multiple-input multiple-output (MIMO) communication system must be designed to cover a given area with maximal energy efficiency (bits/Joule). What are the optimal values for the number of antennas, active users, and transmit power? By using a new model that describes how these three parameters affect the total energy efficiency of the system, this work provides closed-form expressions for their optimal values and interactions. In sharp contrast to common belief, the transmit power is found to increase (not decrease) with the number of antennas. This implies that energy efficient systems can operate at high signal-to-noise ratio (SNR) regimes in which the use of interference-suppressing precoding schemes is essential. Numerical results show that the maximal energy efficiency is achieved by a massive MIMO setup wherein hundreds of antennas are deployed to serve relatively many users using interference-suppressing regularized zero-forcing precoding.

  • 133.
    Björnson, Emil
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Zakhour, Randa
    Mobile Communications Department, EURECOM.
    Gesbert, David
    Mobile Communications Department, EURECOM.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Cooperative Multicell Precoding: Rate Region Characterization and Distributed Strategies With Instantaneous and Statistical CSI2010In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 58, no 8, p. 4298-4310Article in journal (Refereed)
    Abstract [en]

    Base station cooperation is an attractive way of increasing the spectral efficiency in multiantenna communication. By serving each terminal through several base stations in a given area, intercell interference can be coordinated and higher performance achieved, especially for terminals at cell edges. Most previous work in the area has assumed that base stations have common knowledge of both data dedicated to all terminals and full or partial channel state information (CSI) of all links. Herein, we analyze the case of distributed cooperation where each base station has only local CSI, either instantaneous or statistical. In the case of instantaneous CSI, the beamforming vectors that can attain the outer boundary of the achievable rate region are characterized for an arbitrary number of multiantenna transmitters and single-antenna receivers. This characterization only requires local CSI and justifies distributed precoding design based on a novel virtual signal-to-interference noise ratio (SINR) framework, which can handle an arbitrary SNR and achieves the optimal multiplexing gain. The local power allocation between terminals is solved heuristically. Conceptually, analogous results for the achievable rate region characterization and precoding design are derived in the case of local statistical CSI. The benefits of distributed cooperative transmission are illustrated numerically, and it is shown that most of the performance with centralized cooperation can be obtained using only local CSI.

  • 134.
    Björnson, Emil
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Zetterberg, Per
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Bengtsson, Mats
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Capacity Limits and Multiplexing Gains of MIMO Channels with Transceiver Impairments2013In: IEEE Communications Letters, ISSN 1089-7798, E-ISSN 1558-2558, Vol. 17, no 1, p. 91-94Article in journal (Refereed)
    Abstract [en]

    The capacity of ideal MIMO channels has a high-SNR slope that equals the minimum of the number of transmit and receive antennas. This letter analyzes if this result holds when there are distortions from physical transceiver impairments. We prove analytically that such physical MIMO channels have a finite upper capacity limit, for any channel distribution and SNR. The high-SNR slope thus collapses to zero. This appears discouraging, but we prove the encouraging result that the relative capacity gain of employing MIMO is at least as large as with ideal transceivers.

  • 135. Björsell, Niclas
    et al.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    A Statistical Evaluation of ADC Histogram Tests with Arbitrary Stimuli Signal2005In: ADDA 2005, 2005, p. 259-264Conference paper (Refereed)
  • 136. Björsell, Niclas
    et al.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Analog-to-Digital Converters for High-Speed Applications2005In: GigaHz 2005, 2005, p. 151-154Conference paper (Refereed)
  • 137. Björsell, Niclas
    et al.
    Händel, Peter
    KTH, Superseded Departments, Signals, Sensors and Systems.
    Benefits with Truncated Gaussian Noise in ADC Histogram Tests2004In: 9th IMEKO Workshop on ADC Modeling and Testing, IWADC 2004, Held Together with the 13th IMEKO TC4 Symposium on Measurements for Research and Industrial Applications, IMEKO-International Measurement Federation Secretariat , 2004, p. 787-792Conference paper (Refereed)
    Abstract [en]

    One method to characterize ADCs is to use a histogram, where Gaussian noise may be used as stimulus signal. However, a Gaussian noise signal that excites all transition levels also generates input values outside working range of the ADC. Modern signal generators can generate arbitrary signals. Hence, excluding undesired values outside the ADC full scale can minimize test sequences. Truncating the signal to the working range gives further advantages, which are explored in this paper. The statistical properties is theoretically evaluated and compared. It is shown that accuracy increases for a fixed sample length and that variation over transition levels decrease.

  • 138. Björsell, Niclas
    et al.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Dynamic behavior models of analog to digital converters aimed for post-correction in wideband applications2006In: 18th IMEKO World Congress 2006: Metrology for a Sustainable Development, 2006, p. 1344-1348Conference paper (Refereed)
    Abstract [en]

    In this paper a dynamic behavior model of analog to digital converters is proposed. The model is aimed for post correction in wideband applications. The suggested post correction method is a combination of look up tables and model based correction.The model consists of three components. The first is a component represented by a Hammerstein model; that is a static nonlinearity followed by a time invariant linear filter. The second component is a nonparametric model caused by significant deviation from the characterized integral nonlinearity and the output from the Hammerstein model. The third component contains of the remaining deviation and is considered as a random model error.Results from simulations verify that the examined ADC can be described by an ordinary Hammerstein model and a static look-up table.

  • 139. Björsell, Niclas
    et al.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    On Gaussian and Sine Wave Histogram Tests for Wideband Applications2005In: Proceedings of the IEEE Instrumentation and Measurement Technology Conference, IEEE , 2005, p. 677-682Conference paper (Refereed)
    Abstract [en]

    Characterization and testing of analog-to-digital converters (ADCs) are interesting in many different aspects. Histogram test is a common method to characterize the linearity features of an ADC. Two commonly used stimuli signals are sine waves and Gaussian noise. This paper will present a metrological comparison between Gaussian and sine wave histogram tests for wideband applications; that is evaluate the performance in characterization of the ADC and the usability of post-correction. A post-correction procedure involves characterization of the ADC non-linearity and then utilization of this information by processing the ADC output samples to remove the distortion. The results indicates that even though the Gaussian histogram test seems to give reasonable accuracy to measure non-linearities it is not thereby a suitable model for post-correction. A single-tone sine wave histogram will most likely be a better solution. Best result is to train the look-up table with several single-tone sine waves in the frequency band.

  • 140.
    Björsell, Niclas
    et al.
    University of Gävle.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Jansson, Magnus
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Medawar, Samer
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Improved estimate of parametric models for analogue to digital converters by using weighted integral nonlinearity data2010In: 17th Symposium IMEKO TC4 - Measurement of Electrical Quantities, 15th International Workshop on ADC Modelling and Testing, and 3rd Symposium IMEKO TC19 - Environmental Measurements, 2010, p. 597-600Conference paper (Refereed)
    Abstract [en]

    Error modelling has played a major role in generating post-corrections of analogue to digital converters (ADC). Benefits by using parametric models for post-correction are that they requires less memory and that they are easier to identify for arbitrary signals. However, the parameters are estimated in two steps; firstly, the integral nonlinearity (INL) is estimated and secondly, the model parameters. In this paper we propose a method to improve the performance in the second step, by utilizing information about the statistical properties of the first step.

  • 141.
    Björsell, Niclas
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Isaksson, Magnus
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Rönnow, Daniel
    Kautz-Volterra modelling of an analogue-to-digital converter using a stepped three-tone excitation2007In: 12th IMEKO TC-4 International Workshop on ADC MODELLING AND TESTING, 2007, p. 107-112Conference paper (Refereed)
    Abstract [en]

    In many test and measurement applications, the analogue-to-digital converter (ADC) is the limiting component. Using post-correction methods can improve the performance of the component as well as the over all measurement system. In this paper an ADC is characterised by a Kautz-Volterra (KV) model, which utilises a model-based post-correction of the ADC with general properties and a reasonable number of parameters. Results that are based on measurements on a high-speed 12-bit ADC, shows good results for a third order model.

  • 142.
    Björsell, Niclas
    et al.
    University of Gävle, Radio center for measurement technology.
    Nader, Charles
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Multi-tone design for out-of-band characterization of nonlinear RF modules using harmonic sampling2010In: 2010 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2010 - Proceedings, IEEE , 2010, p. 620-623Conference paper (Refereed)
    Abstract [en]

    In this paper we evaluate the generation of a multi-tone set for characterizing the behavior of nonlinear radio frequency (RF) modules in its out-of-band when harmonic sampling is used as digitizer. The purpose is to provide the reader with a tool to select proper frequencies and record length for a given application and test-bed. The method is based on simulations and the use of Sidon sequences. The proposed method is applicable to sparse discrete frequency multi-tones.

  • 143.
    Blomberg, Niclas
    KTH, School of Electrical Engineering (EES), Automatic Control.
    On Nuclear Norm Minimization in System Identification2016Licentiate thesis, monograph (Other academic)
    Abstract [en]

    In system identification we model dynamical systems from measured data. This data-driven approach to modelling is useful since many real-world systems are difficult to model with physical principles. Hence, a need for system identification arises in many applications involving simulation, prediction, and model-based control.

    Some of the classical approaches to system identification can lead to numerically intractable or ill-posed optimization problems. As an alternative, it has recently been shown beneficial to use so called regularization techniques, which make the ill-posed problems ‘regular’. One type of regularization is to introduce a certain rank constraint. However, this in general still leads to a numerically intractable problem, since the rank function is non-convex. One possibility is then use a convex approximation of rank, which we will do here.

    The nuclear norm, i.e., the sum of the singular values, is a popular, convex surrogate of the rank function. This results in a heuristic that has been widely used in e.g. signal processing, machine learning, control, and system identification, since its introduction in 2001. The nuclear norm heuristic introduces a regularization parameter which governs the trade-off between model fit and model complexity. The parameter is difficult to tune, and the

    current thesis revolves around this issue.

    In this thesis, we first propose a choice of the regularization parameter based on the statistical properties of fictitious validation data. This can be used to avoid computationally costly techniques such as cross-validation, where the problem is solved multiple times to find a suitable parameter value. The proposed choice can also be used as initialization to search methods for minimizing some criterion, e.g. a validation cost, over the parameter domain.

    Secondly, we study how the estimated system changes as a function of the parameter over its entire domain, which can be interpreted as a sensitivity analysis. For this we suggest an algorithm to compute a so called approximate regularization path with error guarantees, where the regularization path is the optimal solution as a function of the parameter. We are then able to guarantee the model fit, or, alternatively, the nuclear norm of the approximation, to deviate from the optimum by less than a pre-specified tolerance. Furthermore, we bound the l2-norm of the Hankel singular value approximation error, which means that in a certain subset of the parameter domain, we can guarantee the optimal Hankel singular values returned by the nuclear norm heuristic to not change more (in l2-norm) than a bounded, known quantity.

    Our contributions are demonstrated and evaluated by numerical examples using simulated and benchmark data.

  • 144.
    Blomberg, Niclas
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Rojas, Cristian
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Wahlberg, Bo
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Approximate Regularization Paths for Nuclear Norm Minimization using Singular Value Bounds: with Implementation and Extended Appendix2015Conference paper (Refereed)
    Abstract [en]

    The widely used nuclear norm heuristic for rank minimizationproblems introduces a regularization parameter which isdifficult to tune. We have recently proposed a method to approximatethe regularization path, i.e., the optimal solution asa function of the parameter, which requires solving the problemonly for a sparse set of points. In this paper, we extendthe algorithm to provide error bounds for the singular valuesof the approximation. We exemplify the algorithms on largescale benchmark examples in model order reduction. Here,the order of a dynamical system is reduced by means of constrainedminimization of the nuclear norm of a Hankel matrix.

  • 145.
    Blomqvist, Anders
    et al.
    KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.
    Nagamune, R.
    Optimization-based computation of analytic interpolants of bounded complexity2005In: Systems & control letters (Print), ISSN 0167-6911, E-ISSN 1872-7956, Vol. 54, no 9, p. 855-864Article in journal (Refereed)
    Abstract [en]

    This paper provides a unifying algorithm for computing any analytic interpolant of bounded complexity. Such computation can be performed by solving an optimization problem, due to a theorem by Georgiou and Lindquist. This optimization problem is numerically solvable by a continuation method. The proposed numerical algorithm is useful, among other cases, for designing a low-degree controller for a benchmark problem in robust control. The algorithm unifies previously developed 19 algorithms for the Caratheodory extension and the Nevanlinna-Pick interpolation to one for more general interpolation problems.

  • 146.
    Blomqvist, Anders
    et al.
    KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.
    Wahlberg, Bo
    KTH, School of Electrical Engineering (EES), Automatic Control.
    On frequency weighting in autoregressive spectral estimation2005In: IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 2005, p. 245-248Conference paper (Refereed)
    Abstract [en]

    This paper treats the problem of approximating a complex stochastic process in a given frequency region by an estimated autoregressive (AR) model. Two frequency domain approaches are discussed: a weighted frequency domain maximum likelihood method and a prefiltered covariance extension method based on the theory of Lindquist and co-workers. It is shown that these two approaches are very closely related and can both be formulated as convex optimization problems. An examples illustrating the methods and the effect of prefiltering/weighting is provided. The results show that these methods are capable of tuning the AR model fit to a specified frequency region.

  • 147.
    Boem, Francesca
    et al.
    Department of Industrial and Information Engineering, University of Trieste.
    Xu, Yuzhe
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Fischione, Carlo
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Parisini, Thomas
    Department of Industrial and Information Engineering, University of Trieste.
    Distributed Fault Detection using Sensor Networks and Pareto Estimation2013In: 2013 European Control Conference, ECC 2013, IEEE conference proceedings, 2013, p. 932-937Conference paper (Refereed)
    Abstract [en]

    In this paper, a preliminary novel distributed fault detection architecture for dynamic systems using sensor networks and a distributed estimation method based on Pareto optimization is proposed. The goal is to monitor large-scale or distributed systems by using a sensor network where each node acts as a local estimation agent without centralized coordination. Probabilistic detection thresholds related to a given rate of false alarms are derived in several different scenarios as far as the measurement pattern and the nominal dynamics is concerned. Preliminary simulation results show the effectiveness of the proposed fault detection methodology.

  • 148.
    Bohman, Mikael
    et al.
    KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH.
    Ternström, Sten
    KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Music Acoustics.
    Södersten, M.
    Karolinska University Hospital at Huddinge.
    The use of channel estimation techniques for investigating vocal stress in noisy environments2003In: Ultragarsas, ISSN 1392-2114, Vol. 3, no 48, p. 9-13Article in journal (Other academic)
  • 149.
    Bollepalli, Bajibabu
    et al.
    KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH.
    Raito, T.
    Effect of MPEG audio compression on vocoders used in statistical parametric speech synthesis2014In: 2014 Proceedings of the 22nd European Signal Processing Conference (EUSIPCO), European Signal Processing Conference, EUSIPCO , 2014, p. 1237-1241Conference paper (Refereed)
    Abstract [en]

    This paper investigates the effect of MPEG audio compression on HMM-based speech synthesis using two state-of-the-art vocoders. Speech signals are first encoded with various compression rates and analyzed using the GlottHMM and STRAIGHT vocoders. Objective evaluation results show that the parameters of both vocoders gradually degrade with increasing compression rates, but with a clear increase in degradation with bit-rates of 32 kbit/s or less. Experiments with HMM-based synthesis with the two vocoders show that the degradation in quality is already perceptible with bit-rates of 32 kbit/s and both vocoders show similar trend in degradation with respect to compression ratio. The most perceptible artefacts induced by the compression are spectral distortion and reduced bandwidth, while prosody is better preserved.

  • 150. Borkar, A.
    et al.
    Hayes, M.
    Smith, Mark T.
    KTH, School of Information and Communication Technology (ICT), Electronic Systems.
    Detecting lane markers in a complex environment using a single camera approach2011In: Proceedings of the 8th IASTED International Conference on Signal Processing, Pattern Recognition, and Applications, 2011, p. 15-22Conference paper (Refereed)
    Abstract [en]

    Lane detection is an important application of driver assistance. In this paper, a new technique for detecting lane markers that is able to cope with many complex conditions is presented. Some of these conditions include dynamic illumination, scattered shadows, and the presence of neighboring vehicles to name a few. The input image is first pre-processed with a perspective removal transformation followed by a color space conversion. Then, the core elements of the proposed technique consisting of template matching, lane region merging, elliptical projections, and parametric tracking are explained. A formal error metric used in performance evaluation is also introduced. Finally, quantitative analyses show that the developed system performs well in real-world driving conditions with variations in illumination, traffic, and road surface quality.

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