Mats Viberg

Bio: Mats Viberg is an academic researcher from Chalmers University of Technology. The author has contributed to research in topics: Sensor array & Estimation theory. The author has an hindex of 41, co-authored 231 publications receiving 11749 citations. Previous affiliations of Mats Viberg include Linköping University & Blekinge Institute of Technology.

Downlink performance of regularized ZF in massive MIMO systems subject to IQ imbalance

Abstract: This paper studies the impact of in-phase and quadrature imbalance (IQI) on the downlink of a single-cell multiuser multiple-input multiple-output (MU-MIMO) system with large antenna arrays. Moreover, we consider a time-division duplex (TDD) system where we assume uplink/downlink channel reciprocity in the downlink precoding design. We study the impact of uplink/downlink channel mismatch on the downlink rate caused by different IQI at the base station (BS) and users equipment (UEs). A tractable analytical expression to predict the achievable downlink rates is derived for the regularized zero-forcing (RZF) and based on this expression, we prove that, as the number of BS antennas grow large, the achievable downlink rate of each UE is limited either by the RX IQI at the UEs or by the simultaneous presence of the transmit/receive IQI at the BS and TX IQI at the UEs, when there is uplink/downlink channel mismatch.

Maximum Aperture Power Transmission in Lossy Homogeneous Matters

Abstract: We apply array signal processing techniques to the transmitting aperture field modes in order to determine the optimal field distribution that maximizes the power transmission through lossy media between a transmitting and an ideally receiving antenna aperture. The optimal aperture distribution is then used as a reference field for developing curves applicable to the design of many near-field systems, such as for the detection of foreign objects in lossy matters (e.g., food contamination detectors), wireless charging of batteries of human body implanted devices, and for in-body communication systems.

Transmission strategies for remote estimation under energy harvesting constraints

Abstract: We consider the remote estimation of a time-correlated field using an energy harvesting (EH) sensor. The sensor observes the unknown field and communicates its observations to a remote fusion center using an amplify-forward strategy. We consider the design of optimal transmission strategies in order to minimize the mean-square error (MSE) at the fusion center. Contrary to traditional approaches, the degree of correlation between the field values constitutes an important aspect of our formulation. We provide the optimal power allocation strategies for a number of illustrative scenarios, including the circularly wide-sense stationary (c.w.s.s.) signals with static correlation coefficient and the sampled low-pass c.w.s.s. signals. Based on these results, we propose low-complexity policies for the general case. Numerical evaluations illustrate the performance of the optimal and the low-complexity policies.

Tracking moving objects in video using enhanced mean shift and region-based motion field

Abstract: In this paper, we propose a scheme for moving object tracking from videos by combining mean shift and motion field statistics. For mean shift, we employ an enhanced spatial-range mean shift that enables a reduced number of over-segmentation. For motion statistics, we combine the optical flow and high-order moment to generate motion regions that are associated with moving objects (or object parts). Experiments have been conducted on several indoor and outdoor (color/gray-scale) image sequences ranging from simple to median complexity. To evaluate the performance, three objective criteria are applied in addition to the visual inspection. The results show that the proposed method is promising for moving object tracking in video, with an averaging detection rate of 95%. Further, the proposed scheme is compared with that using the conventional mean shift for the tracking, indicating a significantly reduction in false alarm (≈ 30%).

Direction finding with a dually polarized antenna array using path-wise constraints with application to real data

Abstract: Using an antenna array at the base station in a mobile communication system can lead to benefits such as increased capacity and coverage. Experimental results have shown that a further increase in diversity gain can be accomplished if the antenna not only consists of several elements, but also if the elements are diversely polarized. However, employing diversely polarized arrays complicates the estimation of parameters such as the directions of arrival, as the number of unknown parameters increases, and thereby the complexity of the estimator. Previous work has presented solutions to take the polarization parameters into account, but the necessary constraint used is in a sense restrictive. Instead, a constrained relaxed minimization procedure is proposed that eliminates this restriction. In essence, each propagation path is constrained separately. The proposed technique is applied to real GSM data from a dually polarized antenna array.

On Limits of Wireless Communications in a Fading Environment when UsingMultiple Antennas

Abstract: This paper is motivated by the need for fundamental understanding of ultimate limits of bandwidth efficient delivery of higher bit-rates in digital wireless communications and to also begin to look into how these limits might be approached. We examine exploitation of multi-element array (MEA) technology, that is processing the spatial dimension (not just the time dimension) to improve wireless capacities in certain applications. Specifically, we present some basic information theory results that promise great advantages of using MEAs in wireless LANs and building to building wireless communication links. We explore the important case when the channel characteristic is not available at the transmitter but the receiver knows (tracks) the characteristic which is subject to Rayleigh fading. Fixing the overall transmitted power, we express the capacity offered by MEA technology and we see how the capacity scales with increasing SNR for a large but practical number, n, of antenna elements at both transmitter and receiver. We investigate the case of independent Rayleigh faded paths between antenna elements and find that with high probability extraordinary capacity is available. Compared to the baseline n = 1 case, which by Shannon‘s classical formula scales as one more bit/cycle for every 3 dB of signal-to-noise ratio (SNR) increase, remarkably with MEAs, the scaling is almost like n more bits/cycle for each 3 dB increase in SNR. To illustrate how great this capacity is, even for small n, take the cases n = 2, 4 and 16 at an average received SNR of 21 dB. For over 99% of the channels the capacity is about 7, 19 and 88 bits/cycle respectively, while if n = 1 there is only about 1.2 bit/cycle at the 99% level. For say a symbol rate equal to the channel bandwith, since it is the bits/symbol/dimension that is relevant for signal constellations, these higher capacities are not unreasonable. The 19 bits/cycle for n = 4 amounts to 4.75 bits/symbol/dimension while 88 bits/cycle for n = 16 amounts to 5.5 bits/symbol/dimension. Standard approaches such as selection and optimum combining are seen to be deficient when compared to what will ultimately be possible. New codecs need to be invented to realize a hefty portion of the great capacity promised.

Pattern Recognition and Machine Learning

Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Two decades of array signal processing research: the parametric approach

Abstract: The quintessential goal of sensor array signal processing is the estimation of parameters by fusing temporal and spatial information, captured via sampling a wavefield with a set of judiciously placed antenna sensors. The wavefield is assumed to be generated by a finite number of emitters, and contains information about signal parameters characterizing the emitters. A review of the area of array processing is given. The focus is on parameter estimation methods, and many relevant problems are only briefly mentioned. We emphasize the relatively more recent subspace-based methods in relation to beamforming. The article consists of background material and of the basic problem formulation. Then we introduce spectral-based algorithmic solutions to the signal parameter estimation problem. We contrast these suboptimal solutions to parametric methods. Techniques derived from maximum likelihood principles as well as geometric arguments are covered. Later, a number of more specialized research topics are briefly reviewed. Then, we look at a number of real-world problems for which sensor array processing methods have been applied. We also include an example with real experimental data involving closely spaced emitters and highly correlated signals, as well as a manufacturing application example.

Survey of Wireless Indoor Positioning Techniques and Systems

Abstract: Wireless indoor positioning systems have become very popular in recent years. These systems have been successfully used in many applications such as asset tracking and inventory management. This paper provides an overview of the existing wireless indoor positioning solutions and attempts to classify different techniques and systems. Three typical location estimation schemes of triangulation, scene analysis, and proximity are analyzed. We also discuss location fingerprinting in detail since it is used in most current system or solutions. We then examine a set of properties by which location systems are evaluated, and apply this evaluation method to survey a number of existing systems. Comprehensive performance comparisons including accuracy, precision, complexity, scalability, robustness, and cost are presented.

Convergence of probability measures

Abstract: The author's preface gives an outline: "This book is about weakconvergence methods in metric spaces, with applications sufficient to show their power and utility. The Introduction motivates the definitions and indicates how the theory will yield solutions to problems arising outside it. Chapter 1 sets out the basic general theorems, which are then specialized in Chapter 2 to the space C[0, l ] of continuous functions on the unit interval and in Chapter 3 to the space D [0, 1 ] of functions with discontinuities of the first kind. The results of the first three chapters are used in Chapter 4 to derive a variety of limit theorems for dependent sequences of random variables. " The book develops and expands on Donsker's 1951 and 1952 papers on the invariance principle and empirical distributions. The basic random variables remain real-valued although, of course, measures on C[0, l ] and D[0, l ] are vitally used. Within this framework, there are various possibilities for a different and apparently better treatment of the material. More of the general theory of weak convergence of probabilities on separable metric spaces would be useful. Metrizability of the convergence is not brought up until late in the Appendix. The close relation of the Prokhorov metric and a metric for convergence in probability is (hence) not mentioned (see V. Strassen, Ann. Math. Statist. 36 (1965), 423-439; the reviewer, ibid. 39 (1968), 1563-1572). This relation would illuminate and organize such results as Theorems 4.1, 4.2 and 4.4 which give isolated, ad hoc connections between weak convergence of measures and nearness in probability. In the middle of p. 16, it should be noted that C*(S) consists of signed measures which need only be finitely additive if 5 is not compact. On p. 239, where the author twice speaks of separable subsets having nonmeasurable cardinal, he means "discrete" rather than "separable." Theorem 1.4 is Ulam's theorem that a Borel probability on a complete separable metric space is tight. Theorem 1 of Appendix 3 weakens completeness to topological completeness. After mentioning that probabilities on the rationals are tight, the author says it is an