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  • 1.
    Abeynanda, Hansi
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Nätverk och systemteknik.
    Weeraddana, Chathuranga
    Univ Oulu, Ctr Wireless Commun, Oulu 90014, Finland..
    Lanel, G. H. J.
    Univ Sri Jayewardenepura, Dept Math, Nugegoda 10250, Sri Lanka..
    Fischione, Carlo
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Nätverk och systemteknik.
    On the Primal Feasibility in Dual Decomposition Methods Under Additive and Bounded Errors2023Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 71, s. 655-669Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    With the unprecedented growth of signal processing and machine learning application domains, there has been a tremendous expansion of interest in distributed optimization methods to cope with the underlying large-scale problems. Nonetheless, inevitable system-specific challenges such as limited computational power, limited communication, latency requirements, measurement errors, and noises in wireless channels impose restrictions on the exactness of the underlying algorithms. Such restrictions have appealed to the exploration of algorithms' convergence behaviors under inexact settings. Despite the extensive research conducted in the area, it seems that the analysis of convergences of dual decomposition methods concerning primal optimality violations, together with dual optimality violations is less investigated. Here, we provide a systematic exposition of the convergence of feasible points in dual decomposition methods under inexact settings, for an important class of global consensus optimization problems. Convergences and the rate of convergences of the algorithms are mathematically substantiated, not only from a dual-domain standpoint but also from a primal-domain standpoint. Analytical results show that the algorithms converge to a neighborhood of optimality, the size of which depends on the level of underlying distortions.

  • 2.
    Alam, Syed Asad
    et al.
    Linköpings universitet, Institutionen för systemteknik, Datorteknik. Linköpings universitet, Tekniska fakulteten.
    Gustafsson, Oscar
    Linköpings universitet, Institutionen för systemteknik, Datorteknik. Linköpings universitet, Tekniska fakulteten.
    On the implementation of time-multiplexed frequency-response masking filters2016Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 64, nr 15, s. 3933-3944Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The complexity of narrow transition band finite-length impulse response (FIR) filters is high and can be reduced by using frequency-response masking (FRM) techniques. These techniques use a combination of periodic model and, possibly periodic, masking filters. Time-multiplexing is in general beneficial since only rarely does the technology bound maximum obtainable clock frequency and the application determined required sample rate correspond. Therefore, architectures for time-multiplexed FRM filters that benefit from the inherent sparsity of theperiodic filters are introduced in this work.

    We show that FRM filters not only reduces the number of multipliers needed, but also have benefits in terms of memory usage. Despite the total amount of samples to be stored is larger for FRM, it results in fewer memory resources needed in FPGAs and more energy efficient memory schemes in ASICs. In total, the power consumption is significantly reduced compared to a single stage implementation. Furthermore, we show that the choice of the interpolation factor which gives the least complexity for the periodic model filter and subsequent masking filter(s) is a function of the time-multiplexing factor, meaning that the minimum number of multipliers not always correspond to the minimum number of multiplications. Both single-port and dual-port memories are considered and the involved trade-off in number of multipliers and memory complexity is illustrated. The results show that for FPGA implementation, the power reduction ranges from 23% to 68% for the considered examples.

  • 3.
    Alenlov, Johan
    et al.
    Uppsala Univ, Dept Informat Technol, S-75236 Uppsala, Sweden..
    Olsson, Jimmy
    KTH, Skolan för teknikvetenskap (SCI), Matematik (Inst.), Matematisk statistik.
    Particle-Based Adaptive-Lag Online Marginal Smoothing in General State-Space Models2019Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 67, nr 21, s. 5571-5582Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We present a novel algorithm, an adaptive-lag smoother, approximating efficiently, in an online fashion, sequences of expectations under the marginal smoothing distributions in general state-space models. The algorithm evolves recursively a bank of estimators, one for each marginal, in resemblance with the so-called particle-based, rapid incremental smoother (PaRIS). Each estimator is propagated until a stopping criterion, measuring the fluctuations of the estimates, is met. The presented algorithm is furnished with theoretical results describing its asymptotic limit and memory usage.

  • 4.
    Alenlöv, Johan
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för systemteknik. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Reglerteknik.
    Olsson, Jimmy
    Particle-based adaptive-lag online marginal smoothing in general state-space models2019Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 67, nr 21, s. 5571-5582Artikkel i tidsskrift (Fagfellevurdert)
  • 5.
    Alenlöv, Johan
    et al.
    Department of Information Technology, Uppsala University, Uppsala, Sweden.
    Olsson, Jimmy
    Department of Mathematics, KTH Royal Institute of Technology, Stockholm, Sweden.
    Particle-based adaptive-lag online marginal smoothing in general state-space models2019Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 67, nr 21, s. 5571-5582Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We present a novel algorithm, an adaptive-lag smoother, approximating efficiently, in an online fashion, sequences of expectations under the marginal smoothing distributions in general state-space models. The algorithm evolves recursively a bank of estimators, one for each marginal, in resemblance with the so-called particle-based, rapid incremental smoother (PaRIS). Each estimator is propagated until a stopping criterion, measuring the fluctuations of the estimates, is met. The presented algorithm is furnished with theoretical results describing its asymptotic limit and memory usage.

  • 6. Alodeh, Maha
    et al.
    Chatzinotas, Symeon
    Ottersten, Björn E.
    KTH, Skolan för elektro- och systemteknik (EES), Signalbehandling.
    Spatial DCT-Based Channel Estimation in Multi-Antenna Multi-Cell Interference Channels2015Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 63, nr 6, s. 1404-1418Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This work addresses channel estimation in multiple antenna multicell interference-limited networks. Channel state information (CSI) acquisition is vital for interference mitigation. Wireless networks often suffer from multicell interference, which can be mitigated by deploying beamforming to spatially direct the transmissions. The accuracy of the estimated CSI plays an important role in designing accurate beamformers that can control the amount of interference created from simultaneous spatial transmissions to mobile users. Therefore, a new technique based on the structure of the spatial covariance matrix and the discrete cosine transform (DCT) is proposed to enhance channel estimation in the presence of interference. Bayesian estimation and least squares estimation frameworks are introduced by utilizing the DCT to separate the overlapping spatial paths that create the interference. The spatial domain is thus exploited to mitigate the contamination which is able to discriminate across interfering users. Gains over conventional channel estimation techniques are presented in our simulations which are also valid for a small number of antennas.

  • 7. Ambat, Sooraj K.
    et al.
    Chatterjee, Saikat
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori.
    Hari, K. V. S.
    A Committee Machine Approach for Compressed Sensing Signal Reconstruction2014Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 62, nr 7, s. 1705-1717Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Although many sparse recovery algorithms have been proposed recently in compressed sensing (CS), it is well known that the performance of any sparse recovery algorithm depends on many parameters like dimension of the sparse signal, level of sparsity, and measurement noise power. It has been observed that a satisfactory performance of the sparse recovery algorithms requires a minimum number of measurements. This minimum number is different for different algorithms. In many applications, the number of measurements is unlikely to meet this requirement and any scheme to improve performance with fewer measurements is of significant interest in CS. Empirically, it has also been observed that the performance of the sparse recovery algorithms also depends on the underlying statistical distribution of the nonzero elements of the signal, which may not be known a priori in practice. Interestingly, it can be observed that the performance degradation of the sparse recovery algorithms in these cases does not always imply a complete failure. In this paper, we study this scenario and show that by fusing the estimates of multiple sparse recovery algorithms, which work with different principles, we can improve the sparse signal recovery. We present the theoretical analysis to derive sufficient conditions for performance improvement of the proposed schemes. We demonstrate the advantage of the proposed methods through numerical simulations for both synthetic and real signals.

  • 8. Ambat, Sooraj K.
    et al.
    Chatterjee, Saikat
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori.
    Hari, K. V. S.
    Fusion of Algorithms for Compressed Sensing2013Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 61, nr 14, s. 3699-3704Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    For compressed sensing (CS), we develop a new scheme inspired by data fusion principles. In the proposed fusion based scheme, several CS reconstruction algorithms participate and they are executed in parallel, independently. The final estimate of the underlying sparse signal is derived by fusing the estimates obtained from the participating algorithms. We theoretically analyze this fusion based scheme and derive sufficient conditions for achieving a better reconstruction performance than any participating algorithm. Through simulations, we show that the proposed scheme has two specific advantages: 1) it provides good performance in a low dimensional measurement regime, and 2) it can deal with different statistical natures of the underlying sparse signals. The experimental results on real ECG signals shows that the proposed scheme demands fewer CS measurements for an approximate sparse signal reconstruction.

  • 9.
    Andersson Naesseth, Christian
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Statistik och maskininlärning. Linköpings universitet, Tekniska fakulteten.
    Lindsten, Fredrik
    Linköpings universitet, Institutionen för datavetenskap, Statistik och maskininlärning. Linköpings universitet, Tekniska fakulteten.
    Schon, Thomas B.
    Uppsala Univ, Sweden.
    High-Dimensional Filtering Using Nested Sequential Monte Carlo2019Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 67, nr 16, s. 4177-4188Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Sequential Monte Carlo (SMC) methods comprise one of the most successful approaches to approximate Bayesian filtering. However, SMC without a good proposal distribution can perform poorly, in particular in high dimensions. We propose nested sequential Monte Carlo, a methodology that generalizes the SMC framework by requiring only approximate, properly weighted, samples from the SMC proposal distribution, while still resulting in a correctSMCalgorithm. This way, we can compute an "exact approximation" of, e. g., the locally optimal proposal, and extend the class of models forwhichwe can perform efficient inference using SMC. We showimproved accuracy over other state-of-the-art methods on several spatio-temporal state-space models.

    Fulltekst (pdf)
    fulltext
  • 10.
    Arghavani, Abbas
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Tekniska sektionen, Institutionen för elektroteknik, Signaler och system.
    Dey, Subhrakanti
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Tekniska sektionen, Institutionen för elektroteknik, Signaler och system.
    Ahlén, Anders
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Tekniska sektionen, Institutionen för elektroteknik, Signaler och system.
    Covert Outage Minimization in the Presence of Multiple Wardens2023Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 71, s. 686-700Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The idea of covert communication is to conceal the presence of a transmission from an illegitimate receiver, known as a warden. This paper tackles the problem of finite blocklength covert communication in the presence of multiple colluding wardens. The system consists of Alice, who aims to covertly transmit to Bob with the help of a cooperative jammer (henceforth known as Jammer), and a Fusion Center (FC) in charge of combining the wardens' information and deciding on the presence of Alice's transmission accordingly. In our proposed approach, we utilize a two-player zero-sum game to model the interaction between Alice and Jammer jointly as one player and FC as the second player. In this game, Alice and Jammer cooperatively randomize over a range of transmitting and jamming powers to confuse FC. In contrast, FC randomly changes the detection threshold to confuse Alice. The main focus of the paper is to study the impact of employing multiple wardens on the trade-off between the probability of error at FC and the outage probability at Bob. We derive a pay-off function that can be efficiently computed using linear programming to find the optimal distributions of transmitting and jamming powers as well as thresholds used by FC. The benefit of using a cooperative jammer in neutralizing the advantage of employing multiple wardens is shown by analytical results and numerical simulations.

  • 11. Arora, A.
    et al.
    Tsinos, C. G.
    Rao, B. S. M. R.
    Chatzinotas, S.
    Ottersten, Björn
    Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg, Luxembourg, U.K..
    Hybrid Transceivers Design for Large-Scale Antenna Arrays Using Majorization-Minimization Algorithms2020Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 68, s. 701-714, artikkel-id 8926431Artikkel i tidsskrift (Fagfellevurdert)
  • 12. Arora, Aakash
    et al.
    Tsinos, Christos G.
    Mysore R, Bhavani Shankar
    Chatzinotas, Symeon
    Ottersten, Björn
    Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg, Luxembourg, Luxembourg.
    Efficient Algorithms for Constant-Modulus Analog Beamforming2022Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 70, s. 756-771Artikkel i tidsskrift (Fagfellevurdert)
  • 13.
    Astély, David
    et al.
    KTH, Tidigare Institutioner (före 2005), Signaler, sensorer och system.
    Ottersten, Björn
    KTH, Tidigare Institutioner (före 2005), Signaler, sensorer och system.
    The effects of local scattering on direction of arrival estimation with MUSIC1999Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 47, nr 12, s. 3220-3234Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In wireless communication scenarios, multipath propagation may cause angular spreading as seen from a base station antenna array. Environments where most energy incident on the array is from scatterers local to the mobile transmitters are considered, and the effects on direction of arrival (DOA) estimation with the MUSIC algorithm are studied. Previous work has studied rapidly time-varying channels and concluded that local scattering has a minor effect on DOA estimation in such scenarios. In this work, a channel that is time-invariant during the observation period is considered, and under the assumption of small angular spread, an approximate distribution for the DOA estimates is derived. The results show that local scattering has a significant impact on DOA estimation in the time invariant case. Numerical examples are included to illustrate the analysis and to demonstrate that the results may be used to formulate a simple estimator of angular spread. An extension to more general Rayleigh and Ricean fading channels is also included, In addition, results from processing experimental data collected in suburban environments are presented. Good agreement with the derived distributions is obtained.

  • 14.
    Astély, David
    et al.
    KTH, Tidigare Institutioner (före 2005), Signaler, sensorer och system.
    Swindlehurst, Andrew Lee
    Department of Electrical and Computer Engineering, Brigham Young University, Provo, UT 84602 USA.
    Ottersten, Björn
    KTH, Tidigare Institutioner (före 2005), Signaler, sensorer och system.
    Spatial signature estimation for uniform linear arrays with unknown receiver gains and phases1999Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 47, nr 8, s. 2128-2138Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The problem of spatial signature estimation using a uniform linear array (ULA) with unknown receiver gain and phase responses is studied. Sufficient conditions for identifying the spatial signatures are derived, and a closed-Form ESPRIT-like estimator is proposed, The performance of the method is investigated by means of simulations and on experimental data collected with an antenna array in a suburban environment. The results show that the absence of receiver calibration is not critical for uplink signal waveform estimation using a plane wave model.

  • 15.
    Avazkonandeh Gharavol, Ebrahim
    et al.
    Linköpings universitet, Institutionen för systemteknik, Kommunikationssystem. Linköpings universitet, Tekniska högskolan.
    Larsson, Erik G.
    Linköpings universitet, Institutionen för systemteknik, Kommunikationssystem. Linköpings universitet, Tekniska högskolan.
    The Sign-Definiteness Lemma and Its Applications to Robust Transceiver Optimization for Multiuser MIMO Systems2013Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 61, nr 2, s. 238-252Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We formally generalize the sign-definiteness lemma to the case of complex-valued matrices and multiple norm-bounded uncertainties. This lemma has found many applications in the study of the stability of control systems, and in the design and optimization of robust transceivers in communications. We then present three different novel applications of this lemma in the area of multi-user multiple-input multiple-output (MIMO) robust transceiver optimization. Specifically, the scenarios of interest are: (i) robust linear beamforming in an interfering adhoc network, (ii) robust design of a general relay network, including the two-way relay channel as a special case, and (iii) a half-duplex one-way relay system with multiple relays. For these networks, we formulate the design problems of minimizing the (sum) MSE of the symbol detection subject to different average power budget constraints. We show that these design problems are non-convex (with bilinear or trilinear constraints) and semiinfinite in multiple independent uncertainty matrix-valued variables. We propose a two-stage solution where in the first step the semi-infinite constraints are converted to linear matrix inequalities using the generalized signdefiniteness lemma, and in the second step, we use an iterative algorithm based on alternating convex search (ACS). Via simulations we evaluate the performance of the proposed scheme.

    Fulltekst (pdf)
    fulltext
  • 16.
    Axehill, Daniel
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Hansson, Anders
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Gunnarsson, Fredrik
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    A Low-Complexity High-Performance Preprocessing Algorithm for Multiuser Detection using Gold Sequences2008Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 56, nr 9, s. 4377-4385Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The optimum multiuser detection problem can be formulated as a maximum likelihood problem, which yields a binary quadratic programming problem to be solved. Generally this problem is NP-hard and is therefore hard to solve in real time. In this paper, a preprocessing algorithm is presented which makes it possible to detect some or all users optimally for a low computational cost if signature sequences with low cross correlation, e.g., Gold sequences, are used. The algorithm can be interpreted as, e.g., an adaptive tradeoff between parallel interference cancellation and successive interference cancellation. Simulations show that the preprocessing algorithm is able to optimally compute more than 94,% of the bits in the problem when the users are time-synchronous, even though the system is heavily loaded and affected by noise. Any remaining bits, not computed by the preprocessing algorithm, can either be computed by a suboptimal detector or an optimal detector. Simulations of the time-synchronous case show that if a suboptimal detector is chosen, the bit error rate (BER) rate is significantly reduced compared with using the suboptimal detector alone.

  • 17.
    Axell, Erik
    et al.
    Linköpings universitet, Institutionen för systemteknik, Kommunikationssystem. Linköpings universitet, Tekniska högskolan.
    Larsson, Erik G.
    Linköpings universitet, Institutionen för systemteknik, Kommunikationssystem. Linköpings universitet, Tekniska högskolan.
    Eigenvalue-Based Spectrum Sensing of Orthogonal Space-Time Block Coded Signals2012Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 60, nr 12, s. 6724-6728Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We consider spectrum sensing of signals encoded with an orthogonal space-time block code (OSTBC). We propose a CFAR detector based on knowledge of the eigenvalue multiplicities of the covariance matrix which are inherent owing to the OSTBC and derive theoretical performance bounds. In addition, we show that the proposed detector is robust to a carrier frequency offset, and propose a detector that deals with timing synchronization using the detector for the synchronized case as a building block. The proposed detectors are shown numerically to perform well.

  • 18.
    Bahne, Adrian
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Tekniska sektionen, Institutionen för teknikvetenskaper, Signaler och System.
    Brännmark, Lars-Johan
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Tekniska sektionen, Institutionen för teknikvetenskaper, Signaler och System.
    Ahlén, Anders
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Tekniska sektionen, Institutionen för teknikvetenskaper, Signaler och System.
    Symmetric loudspeaker-room equalization utilizing a pairwise channel similarity criterion2013Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 61, nr 24, s. 6276-6290Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Similarity of the room transfer functions (RTFs) of symmetric channel pairs is crucial for correct sound reproduction of, for example, stereophonic or 5.1 surround multichannel recordings. This physical and psychoacoustical insight yielded the filter design framework presented in this paper. The filter design framework introduced is based on MIMO feedforward control. It has the aim of pairwise equalization of two audio channels and incorporates two features. In the first place, each channel is individually equalized by minimizing the difference between a desired target response and the original RTF by means of support loudspeakers. The second and novel feature represents the similarity requirement and aims at minimizing the difference between the compensated RTFs of the two channels. In order to asses the proposed method a measure of RTF similarity is proposed. Tests with measurements of two different multichannel audio systems proved the method to be able to significantly improve the similarity of two RTFs.

  • 19.
    Bao, Lei
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Skoglund, Mikael
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Fischione, Carlo
    KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Johansson, Karl Henrik
    KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Rate Allocation for Quantized Control Over Binary Symmetric Channels2012Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 60, nr 6, s. 3188-3202Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Utility maximization in networked control systems (NCSs) is difficult in the presence of limited sensing and communication resources. In this paper, a new communication rate optimization method for state feedback control over a noisy channel is proposed. Linear dynamic systems with quantization errors, limited transmission rate, and noisy communication channels are considered. The most challenging part of the optimization is that no closed-form expressions are available for assessing the performance and the optimization problem is nonconvex. The proposed method consists of two steps: (i) the overall NCS performance measure is expressed as a function of rates at all time instants by means of high-rate quantization theory, and (ii) a constrained optimization problem to minimize a weighted quadratic objective function is solved. The proposed method is applied to the problem of state feedback control and the problem of state estimation. Monte Carlo simulations illustrate the performance of the proposed rate allocation. It is shown numerically that the proposed method has better performance when compared to arbitrarily selected rate allocations. Also, it is shown that in certain cases nonuniform rate allocation can outperform the uniform rate allocation, which is commonly considered in quantized control systems, for feedback control over noisy channels.

  • 20. Beck, Amir
    et al.
    Stoica, Peter
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för systemteknik. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Reglerteknik.
    Li, Jian
    Exact and approximate solutions of source localization problems2008Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 56, nr 5, s. 1770-1778Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We consider least squares (LS) approaches for locating a radiating source from range measurements (which we call R-LS) or from range-difference measurements (RD-LS) collected using an array of passive sensors. We also consider LS approaches based on squared range observations (SR-LS) and based on squared range-difference measurements (SRD-LS). Despite the fact that the resulting optimization problems are nonconvex, we provide exact solution procedures for efficiently computing the SR-LS and SRD-LS estimates. Numerical simulations suggest that the exact SR-LS and SRD-LS estimates outperform existing approximations of the SR-LS and SRD-LS solutions as well as approximations of the R-LS and RD-LS solutions which are based on a semidefinite relaxation.

  • 21.
    Bengtsson, Mats
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Signalbehandling.
    Ottersten, Björn
    KTH, Skolan för elektro- och systemteknik (EES), Signalbehandling.
    A generalization of weighted subspace fitting to full-rank models2001Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 49, nr 5, s. 1002-1012Artikkel i tidsskrift (Fagfellevurdert)
    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)

  • 22.
    Bengtsson, Mats
    et al.
    KTH, Tidigare Institutioner (före 2005), Signaler, sensorer och system.
    Ottersten, Björn
    KTH, Tidigare Institutioner (före 2005), Signaler, sensorer och system.
    Low-complexity estimators for distributed sources2000Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 48, nr 8, s. 2185-2194Artikkel i tidsskrift (Fagfellevurdert)
    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

  • 23.
    Bergman, Svante
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Signalbehandling. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Ottersten, Björn
    KTH, Skolan för elektro- och systemteknik (EES), Signalbehandling. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Lattice-based linear precoding for MIMO channels with transmitter CSI2008Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 56, nr 7, s. 2902-2914Artikkel i tidsskrift (Fagfellevurdert)
    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.

  • 24.
    Bergman, Svante
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Signalbehandling. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Palomar, Daniel P.
    Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology.
    Ottersten, Björn
    KTH, Skolan för elektro- och systemteknik (EES), Signalbehandling. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Joint Bit Allocation and Precoding for MIMO Systems With Decision Feedback Detection2009Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 57, nr 11, s. 4509-4521Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This paper considers the joint design of bit loading, precoding and receive filters for a multiple-input multiple-output (MIMO) digital communication system employing decision feedback (DF) detection at the receiver. Both the transmitter as well as the receiver are assumed to know the channel matrix perfectly. It is well known that, for linear MIMO transceivers, a diagonal transmission (i.e., orthogonalization of the channel matrix) is optimal for some criteria. Surprisingly, it was shown five years ago that for the family of Schur-convex functions an additional rotation of the symbols is necessary. However, if the bit loading is optimized jointly with the linear transceiver, then this rotation is unnecessary. Similarly, for DF MIMO optimized transceivers a rotation of the symbols is sometimes needed. The main result of this paper shows that for a DF MIMO transceiver where the bit loading is jointly optimized with the transceiver filters, the rotation of the symbols becomes unnecessary, and because of this, also the DF part of the receiver is not required. The proof is based on a relaxation of the available bit rates on the individual substreams to the set of positive real numbers. In practice, the signal constellations are discrete and the optimal relaxed bit loading has to be rounded. It is shown that the loss due to rounding is small, and an upper bound on the maximum loss is derived. Numerical results are presented that confirm the theoretical results and demonstrate that orthogonal transmission and the truly optimal DF design perform almost equally well.

  • 25.
    Björnson, Emil
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Signalbehandling. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Bengtsson, Mats
    KTH, Skolan för elektro- och systemteknik (EES), Signalbehandling. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Ottersten, Björn
    KTH, Skolan för elektro- och systemteknik (EES), Signalbehandling. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Pareto characterization of the multicell MIMO performance region with simple receivers2012Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 60, nr 8, s. 4464-4469Artikkel i tidsskrift (Fagfellevurdert)
    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).

    Fulltekst (pdf)
    fulltext
  • 26.
    Björnson, Emil
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Signalbehandling. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Hammarwall, David
    Ericsson Research, Stockholm, Sweden.
    Ottersten, Björn
    KTH, Skolan för elektro- och systemteknik (EES), Signalbehandling. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Exploiting Quantized Channel Norm Feedback Through Conditional Statistics in Arbitrarily Correlated MIMO Systems2009Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 57, nr 10, s. 4027-4041Artikkel i tidsskrift (Fagfellevurdert)
    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.

    Fulltekst (pdf)
    fulltext
  • 27.
    Björnson, Emil
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Signalbehandling. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Jaldén, Niklas
    KTH, Skolan för elektro- och systemteknik (EES), Signalbehandling. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Bengtsson, Mats
    KTH, Skolan för elektro- och systemteknik (EES), Signalbehandling. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Ottersten, Björn
    KTH, Skolan för elektro- och systemteknik (EES), Signalbehandling. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Optimality Properties, Distributed Strategies, and Measurement-Based Evaluation of Coordinated Multicell OFDMA Transmission2011Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 59, nr 12, s. 6086-6101Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The throughput of multicell systems is inherently limited by interference andthe available communication resources. Coordinated resource allocation is the key to efficient performance, but the demand on backhaul signaling andcomputational resources grows rapidly with number of cells, terminals, andsubcarriers. To handle this, we propose a novel multicell framework with dynamic cooperation clusters where each terminal is jointly served by a small set of base stations. Each base station coordinates interference to neighboring terminals only, thus limiting backhaul signalling and making the framework scalable. This framework can describe anything from interference channels to ideal joint multicell transmission. The resource allocation (i.e., precoding and scheduling) is formulated as an optimization problem (P1) with performance described by arbitrary monotonic functions of the signal-to-interference-and-noise ratios (SINRs) and arbitrary linear power constraints. Although (P1) is nonconvex and difficult to solve optimally, we are able to prove: 1) optimalityof single-stream beamforming; 2) conditions for full power usage; and 3) a precoding parametrization based on a few parameters between zero and one. These optimality properties are used to propose low-complexity strategies: both a centralized scheme and a distributed version that only requires local channel knowledge and processing. We evaluate the performance on measuredmulticell channels and observe that the proposed strategies achieve close-to-optimal performance among centralized and distributed solutions, respectively. In addition, we show that multicell interference coordination can give substantial improvements in sum performance, but that joint transmission is very sensitive to synchronization errors and that some terminals can experience performance degradations.

    Fulltekst (pdf)
    tsp2011
  • 28.
    Björnson, Emil
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Signalbehandling. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Kountouris, Marios
    Bengtsson, Mats
    KTH, Skolan för elektro- och systemteknik (EES), Signalbehandling. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Ottersten, Björn
    KTH, Skolan för elektro- och systemteknik (EES), Signalbehandling. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Receive Combining vs. Multi-Stream Multiplexing in Downlink Systems With Multi-Antenna Users2013Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 61, nr 13, s. 3431-3446Artikkel i tidsskrift (Fagfellevurdert)
    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.

    Fulltekst (pdf)
    tsp2013
  • 29.
    Björnson, Emil
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Signalbehandling. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Ottersten, Björn
    KTH, Skolan för elektro- och systemteknik (EES), Signalbehandling. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    A Framework for Training-Based Estimation in Arbitrarily Correlated Rician MIMO Channels With Rician Disturbance2010Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 58, nr 3, s. 1807-1820Artikkel i tidsskrift (Fagfellevurdert)
    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.

    Fulltekst (pdf)
    tsp2010
  • 30.
    Björnson, Emil
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Signalbehandling. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Zakhour, Randa
    Mobile Communications Department, EURECOM.
    Gesbert, David
    Mobile Communications Department, EURECOM.
    Ottersten, Björn
    KTH, Skolan för elektro- och systemteknik (EES), Signalbehandling. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Cooperative Multicell Precoding: Rate Region Characterization and Distributed Strategies With Instantaneous and Statistical CSI2010Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 58, nr 8, s. 4298-4310Artikkel i tidsskrift (Fagfellevurdert)
    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.

    Fulltekst (pdf)
    tsp2010
  • 31.
    Björnson, Emil
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Signalbehandling. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Zheng, Gan
    Interdisciplinary Centre for Security, Reliability and Trust, University of Luxembourg.
    Bengtsson, Mats
    KTH, Skolan för elektro- och systemteknik (EES), Signalbehandling. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Ottersten, Björn
    KTH, Skolan för elektro- och systemteknik (EES), Signalbehandling. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Robust Monotonic Optimization Framework for Multicell MISO Systems2012Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 60, nr 5, s. 2508-2523Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The performance of multiuser systems is both difficult to measure fairly and to optimize. Most resource allocation problems are nonconvex and NP-hard, even under simplifying assumptions such as perfect channel knowledge, homogeneous channel properties among users, and simple power constraints. We establish a general optimization framework that systematically solves these problems to global optimality. The proposed branch-reduce-and-bound (BRB) algorithm handles general multicell downlink systems with single-antenna users, multiantenna transmitters, arbitrary quadratic power constraints, and robustness to channel uncertainty. A robust fairness-profile optimization (RFO) problem is solved at each iteration, which is a quasiconvex problem and a novel generalization of max-min fairness. The BRB algorithm is computationally costly, but it shows better convergence than the previously proposed outer polyblock approximation algorithm. Our framework is suitable for computing benchmarks in general multicell systems with or without channel uncertainty. We illustrate this by deriving and evaluating a zero-forcing solution to the general problem.

    Fulltekst (pdf)
    fulltext
  • 32.
    Blasco-Serrano, Ricardo
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre. Ericsson Research.
    Zachariah, Dave
    KTH, Skolan för elektro- och systemteknik (EES), Signalbehandling. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre. Division of Systems and Control. Division of Systems and Control. Uppsala University.
    Sundman, Dennis
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Thobaben, Ragnar
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Skoglund, Mikael
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    A Measurement Rate-MSE Tradeoff for Compressive Sensing Through Partial Support Recovery2014Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 62, nr 18, s. 4643-4658Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We study the fundamental relationship between two relevant quantities in compressive sensing: the measurement rate, which characterizes the asymptotic behavior of the dimensions of the measurement matrix in terms of the ratio m/ log n (m being the number of measurements and n the dimension of the sparse signal), and the mean square estimation error. First, we use an information-theoretic approach to derive sufficient conditions on the measurement rate to reliably recover a part of the support set that represents a certain fraction of the total signal power when the sparsity level is fixed. Second, we characterize the mean square error of an estimator that uses partial support set information. Using these two parts, we derive a tradeoff between the measurement rate and the mean square error. This tradeoff is achievable using a two-step approach: first support set recovery, then estimation of the active components. Finally, for both deterministic and random signals, we perform a numerical evaluation to verify the advantages of the methods based on partial support set recovery.

    Fulltekst (pdf)
    fulltext
  • 33.
    Blomqvist, Anders
    et al.
    KTH, Skolan för teknikvetenskap (SCI), Matematik (Inst.), Optimeringslära och systemteori.
    Wahlberg, Bo
    KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    On the relation between weighted frequency-domain maximum-likelihood power spectral estimation and the prefiltered covariance extension approach2007Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 55, nr 1, s. 384-389Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The aim of this correspondence is to study the connection between weighted frequency-domain maximum-likelihood power spectral estimation and the time-domain prefiltered covariance extension approach. Weighting and prefiltering are introduced to emphasize the model fit in a certain frequency range. The main result is that these two methods are very closely related for the case of autoregressive (AR) model estimation, which implies that both can be formulated as convex optimization problems. Examples illustrating the methods and the effect of prefiltering/weighting are provided.

  • 34.
    Bodnar, Taras
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Dmytriv, Solomiia
    Okhrin, Yarema
    Parolya, Nestor
    Schmid, Wolfgang
    Statistical Inference for the Expected Utility Portfolio in High Dimensions2021Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 69, s. 1-14Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In this paper, using the shrinkage-based approach for portfolio weights and modern results from random matrix theory we construct an effective procedure for testing the efficiency of the expected utility (EU) portfolio and discuss the asymptotic behavior of the proposed test statistic under the high-dimensional asymptotic regime, namely when the number of assets p increases at the same rate as the sample size n such that their ratio p/n approaches a positive constant c is an element of (0, 1) as n -> infinity. We provide an extensive simulation study where the power function and receiver operating characteristic curves of the test are analyzed. In the empirical study, the methodology is applied to the returns of S&P 500 constituents.

  • 35.
    Bodnar, Taras
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Dmytriv, Solomiia
    Parolya, Nestor
    Schmid, Wolfgang
    Tests for the Weights of the Global Minimum Variance Portfolio in a High-Dimensional Setting2019Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 67, nr 17, s. 4479-4493Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In this paper, we construct two tests for the weights of the global minimum variance portfolio (GMVP) in a high-dimensional setting, namely, when the number of assets p depends on the sample size n such that p/n -> c is an element of (0, 1) as n tends to infinity. In the case of a singular covariance matrix with rank equal to q we assume that q/n -> <(c)over tilde is an element of (0,1) as n -> infinity. The considered tests are based on the sample estimator and on the shrinkage estimator of the GMVP weights. We derive the asymptotic distributions of the test statistics under the null and alternative hypotheses. Moreover, we provide a simulation study where the power functions and the receiver operating characteristic curves of the proposed tests are compared with other existing approaches. We observe that the test based on the shrinkage estimator performs well even for values of c close to one.

  • 36.
    Bodnar, Taras
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Parolya, Nestor
    Thorsén, Erik
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Dynamic shrinkage estimation of the high-dimensional minimum-variance portfolio2023Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 71, s. 1334-1349Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In this paper, new results in random matrix theory are derived, which allow us to construct a shrinkage estimator of the global minimum variance (GMV) portfolio when the shrinkage target is a random object. More specifically, the shrinkage target is determined as the holding portfolio estimated from previous data. The theoretical findings are applied to develop theory for dynamic estimation of the GMV portfolio, where the new estimator of its weights is shrunk to the holding portfolio at each time of reconstruction. Both cases with and without overlapping samples are considered in the paper. The non-overlapping samples corresponds to the case when different data of the asset returns are used to construct the traditional estimator of the GMV portfolio weights and to determine the target portfolio, while the overlapping case allows intersections between the samples. The theoretical results are derived under weak assumptions imposed on the data-generating process. No specific distribution is assumed for the asset returns except from the assumption of finite 4+ε, ε>0, moments. Also, the population covariance matrix with unbounded largest eigenvalue can be considered. The performance of new trading strategies is investigated via an extensive simulation. Finally, the theoretical findings are implemented in an empirical illustration based on the returns on stocks included in the S&P 500 index.

  • 37.
    Borpatra Gohain, Prakash
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Intelligenta system, Teknisk informationsvetenskap.
    Jansson, Magnus
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Intelligenta system, Teknisk informationsvetenskap.
    Robust Information Criterion for Model Selection in Sparse High-Dimensional Linear Regression Models2023Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 71, s. 2251-2266Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Model selection in linear regression models is a major challenge when dealing with high-dimensional data where the number of available measurements (sample size) is much smaller than the dimension of the parameter space. Traditional methods for model selection such as Akaike information criterion, Bayesian information criterion (BIC), and minimum description length are heavily prone to overfitting in the high-dimensional setting. In this regard, extended BIC (EBIC), which is an extended version of the original BIC, and extended Fisher information criterion (EFIC), which is a combination of EBIC and Fisher information criterion, are consistent estimators of the true model as the number of measurements grows very large. However, EBIC is not consistent in high signal-to-noise-ratio (SNR) scenarios where the sample size is fixed and EFIC is not invariant to data scaling resulting in unstable behaviour. In this article, we propose a new form of the EBIC criterion called EBIC-Robust, which is invariant to data scaling and consistent in both large sample sizes and high-SNR scenarios. Analytical proofs are presented to guarantee its consistency. Simulation results indicate that the performance of EBIC-Robust is quite superior to that of both EBIC and EFIC.

    Fulltekst (pdf)
    fulltext
  • 38.
    Brännmark, Lars-Johan
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Tekniska sektionen, Institutionen för teknikvetenskaper, Signaler och System.
    Ahlén, Anders
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Tekniska sektionen, Institutionen för teknikvetenskaper, Signaler och System.
    Spatially robust audio compensation based on SIMO feedforward control2009Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 57, nr 5, s. 1689-1702Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This paper introduces a single-input multiple-output (SIMO) feedforward approach to the single-channel loudspeaker equalization problem. Using a polynomial multivariable control framework, a spatially robust equalizer is derived base on a set of room transfer functions (RTFs) and a multipoint mean-square error (MSE) criterion. In contrast to earlier multipoint methods, the polynomial approach provides analytical expressions for the optimum filter, involving the RTF polynomials and certain spatial averages thereof. However, a direct use of the optimum solution is questionable from a perceptual point of view. Despite its multipoint MSE optimality, the filter exhibits similar, albeit less severe, problems as those encountered in nonrobust single-point designs. First, in the case of mixed phase design it is shown to cause residual "pre-ringings" and undesirable magnitude distortion in the equalized system. Second, due to insufficient spatial averaging when using a limited number of RTFs in the design, the filter is overfitted to the chosen set of measurement points, thus providing insufficient robustness. A remedy to these two problems is proposed, based on a   constrained MSE design and a method for clustering of RTF zeros. The outcome is a mixed phase compensator with a time-domain performance preferable to that of the original unconstrained design.

  • 39.
    Byrnes, Christopher
    et al.
    KTH, Tidigare Institutioner (före 2005), Matematik.
    Enqvist, Per
    KTH, Tidigare Institutioner (före 2005), Matematik.
    Lindquist, Anders
    KTH, Tidigare Institutioner (före 2005), Matematik.
    Cepstral coefficients, covariance lags, and pole-zero models for finite data strings2001Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 49, nr 4, s. 677-693Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    One of the most widely used methods of spectral estimation in signal and speech processing is linear predictive coding (LPC). LPC has some attractive features, which account for its popularity, including the properties that the resulting modeling filter i) matches a finite window of n + 1 covariance lags, ii) is rational of degree at most n, and iii) has stable zeros and poles. The only limiting factor of this methodology is that the modeling filter is "all-pole," i.e., an autoregressive (AR) model. In this paper, we present a systematic description of all autoregressive moving-average (ARMA) models of processes that have properties i)-iii) in the context of cepstral analysis and homomorphic filtering. Indeed, we show that each such ARMA model determines and is completely determined by its finite windows of cepstral coefficients and covariance lags. This characterization has an intuitively appealing interpretation of a characterization by using measures of the transient and the steady-state behaviors of the signal, respectively. More precisely, we show that these nth-order windows form local coordinates for all ARMA models of degree n and that the pole-zero model can be determined from the windows as the unique minimum of a convex objective function. We refine this optimization method by first noting that the maximum entropy design of an LPC filter is obtained by maximizing the zeroth cepstral coefficient, subject to the constraint i). More generally, we modify this scheme to a more well-posed optimization problem where the covariance data enters as a constraint and the linear weights of the cepstral coefficients are "positive"-in a sense that a certain pseudo-polynomial is positive-rather succinctly generalizing the maximum entropy method. This new problem is a homomorphic filter generalization of the maximum entropy method, providing a procedure for the design of any stable, minimum-phase modeling filter of degree less or equal to n that interpolates the given covariance window We conclude the paper by presenting an algorithm for realizing these biters in a lattice-ladder form, given the covariance window and the moving average part of the model. While we also show how to determine the moving average part using cepstral smoothing, one can make use of any good a priori estimate for the system zeros to initialize the algorithm. Indeed, we conclude the paper with an example of this method, incorporating an example from the literature on ARMA modeling.

  • 40.
    Cao, Phuong
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori.
    Oechtering, Tobias
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori.
    Schaefer, Rafael
    The Information Theory and Applications Chair, Technische Universitat Berlin.
    Mikael, Skoglund
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori.
    Optimal Transmit Strategy for MISO Channels with Joint Sum and Per-antenna Power Constraints2016Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In this paper, we study an optimal transmit strategy for multiple-input single-output (MISO) Gaussian channels with joint sum and per-antenna power constraints. We study in detail the interesting case where the sum of the per-antenna power constraints is larger than sum power constraint. A closed-form characterization of an optimal beamforming strategy is derived.It is shown that we can always find an optimal beamforming transmit strategy that allocates the maximal sum power with phases matched to the complex channel coefficients. The main result is a simple recursive algorithm to compute the optimal power allocation. Whenever the optimal power allocation of the corresponding problem with sum power constraint only exceeds per-antenna power constraints, it is optimal to allocate maximal per-antenna power to those antennas to satisfy the per-antenna power constraints. The remaining power is divided amongst the other antennas whose optimal allocation follows from a reduced joint sum and per-antenna power constraints problem of smaller channel coefficient dimension and reduced sum power constraint. Finally, the theoretical results are illustrated by numerical examples.

    Fulltekst (pdf)
    fulltext
  • 41. Carotenuto, Vincenzo
    et al.
    De Maio, Antonio
    Orlando, Danilo
    Stoica, Peter
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för systemteknik. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Reglerteknik.
    Model order selection rules for covariance structure classification in radar2017Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 65, nr 20, s. 5305-5317Artikkel i tidsskrift (Fagfellevurdert)
  • 42.
    Chatterjee, Saikat
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Flåm, John T.
    NTNU - Norwegian University of Science and Technology.
    Kansanen, Kimmo
    NTNU - Norwegian University of Science and Technology.
    Ekman, Tobjorn
    NTNU - Norwegian University of Science and Technology.
    On MMSE estimation: A linear model under Gaussian mixture statistics2012Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 60, nr 7, s. 3840-3845Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In a Bayesian linear model, suppose observation y = Hx + n stems from independent inputs x and n which are Gaussian mixture (GM) distributed. With known matrix H, the minimum mean square error (MMSE) estimator for x , has analytical form. However, its performance measure, the MMSE itself, has no such closed form. Because existing Bayesian MMSE bounds prove to have limited practical value under these settings, we instead seek analytical bounds for the MMSE, both upper and lower. This paper provides such bounds, and relates them to the signal-to-noise-ratio (SNR).

    Fulltekst (pdf)
    fulltext
  • 43.
    Chatterjee, Saikat
    et al.
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori.
    Sundman, Dennis
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori.
    Vehkaperä, Mikko
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori.
    Skolglund, Mikael
    KTH, Skolan för elektro- och systemteknik (EES), Kommunikationsteori.
    Projection-based and look ahead strategies for atom selection2012Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 60, nr 2, s. 634-647Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In this paper, we improve iterative greedy search algorithms in which atoms are selected serially over iterations, i.e., one-by-one over iterations. For serial atom selection, we devise two new schemes to select an atom from a set of potential atoms in each iteration. The two new schemes lead to two new algorithms. For both the algorithms, in each iteration, the set of potential atoms is found using a standard matched filter. In case of the first scheme, we propose an orthogonal projection strategy that selects an atom from the set of potential atoms. Then, for the second scheme, we propose a look-ahead strategy such that the selection of an atom in the current iteration has an effect on the future iterations. The use of look-ahead strategy requires a higher computational resource. To achieve a tradeoff between performance and complexity, we use the two new schemes in cascade and develop a third new algorithm. Through experimental evaluations, we compare the proposed algorithms with existing greedy search and convex relaxation algorithms.

    Fulltekst (pdf)
    fulltext
  • 44.
    Chen, Tianshi
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Schön, Thomas
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Ohlsson, Henrik
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Ljung, Lennart
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Decentralized Particle Filter with Arbitrary State Decomposition2011Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 59, nr 2, s. 465-478Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In this paper, a new particle filter (PF) which we refer to as the decentralized PF (DPF) is proposed. By first decomposing the state into two parts, the DPF splits the filtering problem into two nested subproblems and then handles the two nested subproblems using PFs. The DPF has the advantage over the regular PF that the DPF can increase the level of parallelism of the PF. In particular, part of the resampling in the DPF bears a parallel structure and can thus be implemented in parallel. The parallel structure of the DPF is created by decomposing the state space, differing from the parallel structure of the distributed PFs which is created by dividing the sample space. This difference results in a couple of unique features of the DPF in contrast with the existing distributed PFs. Simulation results of two examples indicate that the DPF has a potential to achieve in a shorter execution time the same level of performance as the regular PF.

    Fulltekst (pdf)
    FULLTEXT01
  • 45.
    Chen, Xu
    et al.
    Univ Hong Kong, Peoples R China.
    Larsson, Erik G
    Linköpings universitet, Institutionen för systemteknik, Kommunikationssystem. Linköpings universitet, Tekniska fakulteten.
    Huang, Kaibin
    Univ Hong Kong, Peoples R China.
    Analog MIMO Communication for One-Shot Distributed Principal Component Analysis2022Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 70, s. 3328-3342Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    A fundamental algorithm for data analytics at the edge of wireless networks is distributed principal component analysis (DPCA), which finds the most important information embedded in a distributed high-dimensional dataset by distributed computation of a reduced-dimension data subspace, called principal components (PCs). In this paper, to support one-shot DPCA in wireless systems, we propose a framework of analog MIMO transmission featuring the uncoded analog transmission of local PCs for estimating the global PCs. To cope with channel distortion and noise, two maximum-likelihood (global) PC estimators are presented corresponding to the cases with and without receive channel state information (CSI). The first design, termed coherent PC estimator, is derived by solving a Procrustes problem and reveals the form of regularized channel inversion where the regulation attempts to alleviate the effects of both receiver noise and data noise. The second one, termed blind PC estimator, is designed based on the subspace channel-rotation-invariance property and computes a centroid of received local PCs on a Grassmann manifold. Using the manifold-perturbation theory, tight bounds on the mean square subspace distance (MSSD) of both estimators are derived for performance evaluation. The results reveal simple scaling laws of MSSD concerning device population, data and channel signal-to-noise ratios (SNRs), and array sizes. More importantly, both estimators are found to have identical scaling laws, suggesting the dispensability of CSI to accelerate DPCA. Simulation results validate the derived results and demonstrate the promising latency performance of the proposed analog MIMO.

    Fulltekst (pdf)
    fulltext
  • 46.
    Cheng, Hei Victor
    et al.
    Linköping Univ, Dept Elect Engn ISY, S-58183 Linköping, Sweden..
    Björnson, Emil
    Linköping Univ, Dept Elect Engn ISY, S-58183 Linköping, Sweden..
    Larsson, Erik G.
    Linköping Univ, Dept Elect Engn ISY, S-58183 Linköping, Sweden..
    Optimal Pilot and Payload Power Control in Single-Cell Massive MIMO Systems2017Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 65, nr 9, s. 2363-2378Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This paper considers the jointly optimal pilot and data power allocation in single-cell uplink massive multiple-input-multiple- output systems. Using the spectral efficiency (SE) as performance metric and setting a total energy budget per coherence interval, the power control is formulated as optimization problems for two different objective functions: the weighted minimum SE among the users and the weighted sum SE. A closed form solution for the optimal length of the pilot sequence is derived. The optimal power control policy for the former problem is found by solving a simple equation with a single variable. Utilizing the special structure arising from imperfect channel estimation, a convex reformulation is found to solve the latter problem to global optimality in polynomial time. The gain of the optimal joint power control is theoretically justified, and is proved to be large in the low-SNR regime. Simulation results also show the advantage of optimizing the power control over both pilot and data power, as compared to the cases of using full power and of only optimizing the data powers as done in previous work.

  • 47.
    Cheng, Victor
    et al.
    Linköpings universitet, Institutionen för systemteknik, Kommunikationssystem. Linköpings universitet, Tekniska fakulteten.
    Björnson, Emil
    Linköpings universitet, Institutionen för systemteknik, Kommunikationssystem. Linköpings universitet, Tekniska fakulteten.
    Larsson, Erik G
    Linköpings universitet, Institutionen för systemteknik, Kommunikationssystem. Linköpings universitet, Tekniska fakulteten.
    Optimal Pilot and Payload Power Control in Single-Cell Massive MIMO Systems2017Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 65, nr 9, s. 2363-2378Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This paper considers the jointly optimal pilot and data power allocation in single-cell uplink massive multiple-input-multiple- output systems. Using the spectral efficiency (SE) as performance metric and setting a total energy budget per coherence interval, the power control is formulated as optimization problems for two different objective functions: the weighted minimum SE among the users and the weighted sum SE. A closed form solution for the optimal length of the pilot sequence is derived. The optimal power control policy for the former problem is found by solving a simple equation with a single variable. Utilizing the special structure arising from imperfect channel estimation, a convex reformulation is found to solve the latter problem to global optimality in polynomial time. The gain of the optimal joint power control is theoretically justified, and is proved to be large in the low-SNR regime. Simulation results also show the advantage of optimizing the power control over both pilot and data power, as compared to the cases of using full power and of only optimizing the data powers as done in previous work.

    Fulltekst (pdf)
    fulltext
  • 48.
    Cheng, Yuanbo
    et al.
    Univ Sci & Technol China, Dept Elect Engn & Informat Sci, Hefei 230027, Peoples R China..
    Shang, Xiaolei
    Univ Sci & Technol China, Dept Elect Engn & Informat Sci, Hefei 230027, Peoples R China..
    Li, Jian
    Univ Florida, Dept Elect & Comp Engn, Gainesville, FL 32611 USA..
    Stoica, Peter
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för systemteknik.
    Interval Design for Signal Parameter Estimation From Quantized Data2022Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 70, s. 6011-6020Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We consider the problem of optimizing the quantization intervals (or thresholds) of low-resolution analog-to-digital converters (ADCs) via the minimization of a Cramer-Rao bound (CRB)-based metric. The interval design is formulated as a dynamic programming problem. A computationally efficient global algorithm, referred to as the interval design for enhanced accuracy (IDEA) algorithm, is presented to solve this optimization problem. If the realization in hardware of a quantizer with optimized intervals is difficult, it can be approximated by a design whose practical implementation is feasible. Furthermore, the optimized quantizer can also be useful in signal compression applications, in which case no approximation should be necessary. As an additional contribution, we establish the equivalence between the Lloyd-Max type of quantizer and a low signal-to-noise ratio version of our IDEA quantizer, and show that it holds true if and only if the noise is Gaussian. Furthermore, IDEA quantizers for several typical signals, for instance normally distributed signals, are provided. Finally, a number of numerical examples are presented to demonstrate that the use of IDEA quantizers can enhance the parameter estimation performance.

  • 49.
    Chopra, Ribhu
    et al.
    Indian Inst Technol, India.
    Murthy, Chandra R.
    Indian Inst Sci, India.
    Suraweera, Himal A.
    Univ Peradeniya, Sri Lanka.
    Larsson, Erik G
    Linköpings universitet, Institutionen för systemteknik, Kommunikationssystem. Linköpings universitet, Tekniska fakulteten.
    Blind Channel Estimation for Downlink Massive MIMO Systems With Imperfect Channel Reciprocity2020Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 68, s. 3132-3145Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We consider the performance of time-division duplex (TDD) massive multiple-input multiple-output (MIMO) with imperfect calibration of the transmit and receive radio frequency chains. By deriving the achievable signal-to-interference-plus-noise ratio & x00A0;(SINR) and the per-user bit error rate & x00A0;(BER) for constant modulus constellations, we establish that, under linear precoding, reciprocity imperfections can result in substantial reduction of the array gain. To mitigate this loss, we propose an algorithm for blind estimation of the effective channel gain at each user. We show that, with sufficiently many downlink data symbols, our blind channel estimation algorithm restores the array gain. In addition, the proposed blind gain estimation algorithm can improve performance compared to standard hardening-based receivers even under perfect reciprocity. Following this, we derive the BERs for non-constant modulus constellations, viz.& x00A0;-PAM and -QAM. We corroborate all our derived results using numerical simulations.

  • 50. Christopoulos, D.
    et al.
    Chatzinotas, S.
    Ottersten, Björn
    Weighted fair multicast multigroup beamforming under per-antenna power constraints2014Inngår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 62, nr 19, s. 5132-5142Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    A multiantenna transmitter that conveys independent sets of common data to distinct groups of users is considered. This model is known as physical layer multicasting to multiple cochannel groups. In this context, the practical constraint of a maximum permitted power level radiated by each antenna is addressed. The per-antenna power constrained system is optimized in a maximum fairness sense with respect to predetermined quality of service weights. In other words, the worst scaled user is boosted by maximizing its weighted signal-to-interference plus noise ratio. A detailed solution to tackle the weighted max-min fair multigroup multicast problem under per-antenna power constraints is therefore derived. The implications of the novel constraints are investigated via prominent applications and paradigms. What is more, robust per-antenna constrained multigroup multicast beamforming solutions are proposed. Finally, an extensive performance evaluation quantifies the gains of the proposed algorithm over existing solutions and exhibits its accuracy over per-antenna power constrained systems.

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