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  • 1.
    Abdalmoaty, Mohamed
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Learning Stochastic Nonlinear Dynamical Systems Using Non-stationary Linear Predictors2017Licentiate thesis, monograph (Other academic)
    Abstract [en]

    The estimation problem of stochastic nonlinear parametric models is recognized to be very challenging due to the intractability of the likelihood function. Recently, several methods have been developed to approximate the maximum likelihood estimator and the optimal mean-square error predictor using Monte Carlo methods. Albeit asymptotically optimal, these methods come with several computational challenges and fundamental limitations.

    The contributions of this thesis can be divided into two main parts. In the first part, approximate solutions to the maximum likelihood problem are explored. Both analytical and numerical approaches, based on the expectation-maximization algorithm and the quasi-Newton algorithm, are considered. While analytic approximations are difficult to analyze, asymptotic guarantees can be established for methods based on Monte Carlo approximations. Yet, Monte Carlo methods come with their own computational difficulties; sampling in high-dimensional spaces requires an efficient proposal distribution to reduce the number of required samples to a reasonable value.

    In the second part, relatively simple prediction error method estimators are proposed. They are based on non-stationary one-step ahead predictors which are linear in the observed outputs, but are nonlinear in the (assumed known) input. These predictors rely only on the first two moments of the model and the computation of the likelihood function is not required. Consequently, the resulting estimators are defined via analytically tractable objective functions in several relevant cases. It is shown that, under mild assumptions, the estimators are consistent and asymptotically normal. In cases where the first two moments are analytically intractable due to the complexity of the model, it is possible to resort to vanilla Monte Carlo approximations. Several numerical examples demonstrate a good performance of the suggested estimators in several cases that are usually considered challenging.

  • 2.
    Abdalmoaty, Mohamed
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    A Simulated Maximum Likelihood Method for Estimation of Stochastic Wiener Systems2016In: 2016 IEEE 55th Conference on Decision and Control, CDC 2016, Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 3060-3065, article id 7798727Conference paper (Refereed)
    Abstract [en]

    This paper introduces a simulation-based method for maximum likelihood estimation of stochastic Wienersystems. It is well known that the likelihood function ofthe observed outputs for the general class of stochasticWiener systems is analytically intractable. However, when the distributions of the process disturbance and the measurement noise are available, the likelihood can be approximated byrunning a Monte-Carlo simulation on the model. We suggest the use of Laplace importance sampling techniques for the likelihood approximation. The algorithm is tested on a simple first order linear example which is excited only by the process disturbance. Further, we demonstrate the algorithm on an FIR system with cubic nonlinearity. The performance of the algorithm is compared to the maximum likelihood method and other recent techniques.

  • 3.
    Abdalmoaty, Mohamed
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering (EES), Automatic Control.
    On Re-Weighting, Regularization Selection, and Transient in Nuclear Norm Based Identification2015Conference paper (Refereed)
    Abstract [en]

    In this contribution, we consider the classical problem of estimating an Output Error model given a set of input-output measurements. First, we develop a regularization method based on the re-weighted nuclear norm heuristic. We show that the re-weighting improves the estimate in terms of better fit. Second, we suggest an implementation method that helps in eliminating the regularization parameters from the problem by introducing a constant based on a validation criterion. Finally, we develop a method for considering the effect of the transient when the initial conditions are unknown. A simple numerical example is used to demonstrate the proposed method in comparison to classical and another recent method based on the nuclear norm heuristic.

  • 4.
    Abdalmoaty, Mohamed
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH Royal Institute of Technology.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Simulated Pseudo Maximum Likelihood Identification of Nonlinear Models2017In: The 20th IFAC World Congress, Elsevier, 2017, Vol. 50, p. 14058-14063Conference paper (Refereed)
    Abstract [en]

    Nonlinear stochastic parametric models are widely used in various fields. However, for these models, the problem of maximum likelihood identification is very challenging due to the intractability of the likelihood function. Recently, several methods have been developed to approximate the analytically intractable likelihood function and compute either the maximum likelihood or a Bayesian estimator. These methods, albeit asymptotically optimal, are computationally expensive. In this contribution, we present a simulation-based pseudo likelihood estimator for nonlinear stochastic models. It relies only on the first two moments of the model, which are easy to approximate using Monte-Carlo simulations on the model. The resulting estimator is consistent and asymptotically normal. We show that the pseudo maximum likelihood estimator, based on a multivariate normal family, solves a prediction error minimization problem using a parameterized norm and an implicit linear predictor. In the light of this interpretation, we compare with the predictor defined by an ensemble Kalman filter. Although not identical, simulations indicate a close relationship. The performance of the simulated pseudo maximum likelihood method is illustrated in three examples. They include a challenging state-space model of dimension 100 with one output and 2 unknown parameters, as well as an application-motivated model with 5 states, 2 outputs and 5 unknown parameters.

  • 5. Abedan Kondori, Farid
    et al.
    Yousefi, Shahrouz
    KTH, School of Computer Science and Communication (CSC), Media Technology and Interaction Design, MID. Department of Applied Physics and Electronics, Umeå University, Umeå, Sweden.
    Smart Baggage in Aviation2011In: Proceedings - 2011 IEEE International Conferences on Internet of Things and Cyber, Physical and Social Computing, 2011Conference paper (Refereed)
    Abstract [en]

    Nowadays, the Internet has dramatically changed the way people take the normal course of actions. By the recent growth of the Internet, connecting different objects to users through mobile phones and computers is no longer a dream. Aviation industry is one of the areas which have a strong potential to benefit from the Internet of Things. Among many problems related to air travel, delayed and lost luggage are the most common and irritating. Therefore, this paper suggests anew baggage control system, where users can simply track their baggage at the airport to avoid losing them. Attaching a particular pattern on the bag, which can be detected and localized from long distance by an ordinary camera, users are able to track their baggage. The proposed system is much cheaper than previous implementations and does not require sophisticated equipment.

  • 6. Abedan Kondori, Farid
    et al.
    Yousefi, Shahrouz
    KTH, School of Computer Science and Communication (CSC), Media Technology and Interaction Design, MID.
    Li, Haibo
    KTH, School of Computer Science and Communication (CSC), Media Technology and Interaction Design, MID.
    Direct Head Pose Estimation Using Kinect-type Sensors2014In: Electronics Letters, ISSN 0013-5194, E-ISSN 1350-911XArticle in journal (Refereed)
  • 7. Abedan Kondori, Farid
    et al.
    Yousefi, Shahrouz
    KTH, School of Computer Science and Communication (CSC), Media Technology and Interaction Design, MID.
    Liu, Li
    Li, Haibo
    KTH, School of Computer Science and Communication (CSC), Media Technology and Interaction Design, MID. Nanjing University of Posts and Telecommunications, Nanjing, China .
    Head Operated Electric Wheelchair2014In: Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation, 2014, p. 53-56Conference paper (Refereed)
    Abstract [en]

    Currently, the most common way to control an electric wheelchair is to use joystick. However, there are some individuals unable to operate joystick-driven electric wheelchairs due to sever physical disabilities, like quadriplegia patients. This paper proposes a novel head pose estimation method to assist such patients. Head motion parameters are employed to control and drive an electric wheelchair. We introduce a direct method for estimating user head motion, based on a sequence of range images captured by Kinect. In this work, we derive new version of the optical flow constraint equation for range images. We show how the new equation can be used to estimate head motion directly. Experimental results reveal that the proposed system works with high accuracy in real-time. We also show simulation results for navigating the electric wheelchair by recovering user head motion.

  • 8.
    Abtahi, Farhad
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Aspects of Electrical Bioimpedance Spectrum Estimation2014Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Electrical bioimpedance spectroscopy (EBIS) has been used to assess the status or composition of various types of tissue, and examples of EBIS include body composition analysis (BCA) and tissue characterisation for skin cancer detection. EBIS is a non-invasive method that has the potential to provide a large amount of information for diagnosis or monitoring purposes, such as the monitoring of pulmonary oedema, i.e., fluid accumulation in the lungs. However, in many cases, systems based on EBIS have not become generally accepted in clinical practice. Possible reasons behind the low acceptance of EBIS could involve inaccurate models; artefacts, such as those from movements; measurement errors; and estimation errors. Previous thoracic EBIS measurements aimed at pulmonary oedema have shown some uncertainties in their results, making it difficult to produce trustworthy monitoring methods. The current research hypothesis was that these uncertainties mostly originate from estimation errors. In particular, time-varying behaviours of the thorax, e.g., respiratory and cardiac activity, can cause estimation errors, which make it tricky to detect the slowly varying behaviour of this system, i.e., pulmonary oedema.

    The aim of this thesis is to investigate potential sources of estimation error in transthoracic impedance spectroscopy (TIS) for pulmonary oedema detection and to propose methods to prevent or compensate for these errors.   This work is mainly focused on two aspects of impedance spectrum estimation: first, the problems associated with the delay between estimations of spectrum samples in the frequency-sweep technique and second, the influence of undersampling (a result of impedance estimation times) when estimating an EBIS spectrum. The delay between frequency sweeps can produce huge errors when analysing EBIS spectra, but its effect decreases with averaging or low-pass filtering, which is a common and simple method for monitoring the time-invariant behaviour of a system. The results show the importance of the undersampling effect as the main estimation error that can cause uncertainty in TIS measurements.  The best time for dealing with this error is during the design process, when the system can be designed to avoid this error or with the possibility to compensate for the error during analysis. A case study of monitoring pulmonary oedema is used to assess the effect of these two estimation errors. However, the results can be generalised to any case for identifying the slowly varying behaviour of physiological systems that also display higher frequency variations.  Finally, some suggestions for designing an EBIS measurement system and analysis methods to avoid or compensate for these estimation errors are discussed.

  • 9. Abu-Shaban, Z.
    et al.
    Bhavani Shankar Mysore, R.
    Mehrpouyan, H.
    Ottersten, Björn
    SnT - Univ. of Luxembourg, Luxembourg, Luxembourg.
    Enhanced List-based Group-wise overloaded receiver with application to satellite reception2014In: 2014 IEEE International Conference on Communications (ICC), IEEE conference proceedings, 2014, p. 5616-5621Conference paper (Refereed)
    Abstract [en]

    The market trends towards the use of smaller dish antennas for TV satellite receivers, as well as the growing density of broadcasting satellites in orbit require the application of robust adjacent satellite interference (ASI) cancellation algorithms at the receivers. The wider beamwidth of a small size dish and the growing number of satellites in orbit impose an overloaded scenario, i.e., a scenario where the number of transmitting satellites exceeds the number of receiving antennas. For such a scenario, we present a two stage receiver to enhance signal detection from the satellite of interest, i.e., the satellite that the dish is pointing to, while reducing interference from neighboring satellites. Towards this objective, we propose an enhanced List-based Group-wise Search Detection (LGSD) receiver architecture that takes into account the spatially correlated additive noise and uses the signal-to-interference-plus-noise ratio (SINR) maximization criterion to improve detection performance. Simulations show that the proposed receiver structure enhances the performance of satellite systems in the presence of ASI when compared to existing methods.

  • 10. Abu-Shaban, Z.
    et al.
    Mehrpouyan, H.
    Grotz, J.
    Ottersten, Björn
    SnT - University of Luxembourg, Luxembourg .
    Overloaded satellite receiver using SIC with hybrid beamforming and ML detection2013In: 2013 IEEE 14th Workshop on Signal Processing Advances in Wireless Communications (SPAWC), New York: IEEE , 2013, p. 450-454Conference paper (Refereed)
    Abstract [en]

    In this paper, a new receiver structure that is intended to detect the signals from multiple adjacent satellites in the presence of other interfering satellites is proposed. We tackle the worst case interference conditions, i.e., it is assumed that uncoded signals that fully overlap in frequency arrive at a multiple-element small-size parabolic antenna in a spatially correlated noise environment. The proposed successive interference cancellation (SIC) receiver, denoted by SIC Hy/ML, employs hybrid beamforming and disjoint maximum likelihood (ML) detection. Depending on the individual signals spatial position, the proposed SIC Hy/ML scheme takes advantage of two types of beamformers: a maximum ratio combining (MRC) beamformer and a compromised array response (CAR) beamformer. The performance of the proposed receiver is compared to an SIC receiver that uses only MRC beamforming scheme with ML detection for all signals, a joint ML detector, and a minimum mean square error detector. It is found that SIC Hy/ML outperforms the other schemes by a large margin.

  • 11. Afzal, H.
    et al.
    Aouada, D.
    Font, D.
    Mirbach, B.
    Ottersten, Björn
    RGB-D multi-view system calibration for full 3D scene reconstruction2014In: 2014 22nd International Conference on Pattern Recognition, IEEE conference proceedings, 2014, p. 2459-2464Conference paper (Refereed)
    Abstract [en]

    One of the most crucial requirements for building a multi-view system is the estimation of relative poses of all cameras. An approach tailored for a RGB-D cameras based multi-view system is missing. We propose BAICP+ which combines Bundle Adjustment (BA) and Iterative Closest Point (ICP) algorithms to take into account both 2D visual and 3D shape information in one minimization formulation to estimate relative pose parameters of each camera. BAICP+ is generic enough to take different types of visual features into account and can be easily adapted to varying quality of 2D and 3D data. We perform experiments on real and simulated data. Results show that with the right weighting factor BAICP+ has an optimal performance when compared to BA and ICP used independently or sequentially.

  • 12.
    Agevik, Niklas
    et al.
    KTH, Superseded Departments, Signals, Sensors and Systems.
    Fransson, Henrik
    KTH, Superseded Departments, Signals, Sensors and Systems.
    Grunell, Henrik
    KTH, Superseded Departments, Signals, Sensors and Systems.
    Jakiel, Patrick
    KTH, Superseded Departments, Signals, Sensors and Systems.
    Lundin, Henrik
    KTH, Superseded Departments, Signals, Sensors and Systems.
    On Loudspeaker Linearization Using Pre-Distortion2004In: European DSP Education & Research Symposium (EDERS), 2004Conference paper (Refereed)
    Abstract [en]

    In this paper we present a system for linearizing the combined output of a stereo amplifier and loudspeaker through pre-distortion. Removal of room cancellation effects is also discussed. The system uses white noise to estimate an FIR model with the Recursive Least Squares algorithm and experiments show that this can significantly improve the linearity of the sound system. We show that the system can be extended with a nonlinear model and that this indeed can be implemented on a TexasInstruments TMS320C6701 DSP with excellent performance.

  • 13. Ahmed, Zakir
    et al.
    Bhardwaj, Krishna
    Krishnan, Ramesh
    Yajnanarayana, Vijaya
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Estimation of Sample Clock Frequency Offset Using Error Vector Magnitude2011Patent (Other (popular science, discussion, etc.))
    Abstract [en]

    A low complexity system and method for operating a receiver in order to estimate an offset between the actual sample clock rate 1/TS' of a receiver and an intended sample clock rate 1/TS. The receiver captures samples of a received baseband signal at the rate 1/TS', operates on the captured samples to generate an estimate for the clock rate offset, and fractionally resamples the captured samples using the clock rate offset. The resampled data represents an estimate of baseband symbols transmitted by the transmitter. The action of operating on the captured samples involves computing an error vector signal and then estimating the clock rate offset using the error vector signal. The error vector signal may be computed in different ways depending on whether or not carrier frequency offset and carrier phase offset are assumed to be present in the received baseband signal.

  • 14. Ahmed, Zakir
    et al.
    Yajnanarayana, Vijaya
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Blind mechanism for the joint estimation of frequency offset and phase offset for QAM modulated signals2010Patent (Other (popular science, discussion, etc.))
    Abstract [en]

    A mechanism for jointly correcting carrier phase and carrier frequency errors in a demodulated signal. A computer system may receive samples of a baseband input signal (resulting from QAM demodulation). The computer system may compute values of a cost function J over a grid in a 2D angle-frequency space. A cost function value J(theta,omega) is computed for each point (theta,omega) in the grid by (a) applying a phase adjustment of angle theta and a frequency adjustment of frequency omega to the input signal; (b) performing one or more iterations of the K-means algorithm on the samples of the adjusted signal; (c) generated a sum on each K-means cluster; and (d) adding the sums. The point (thetae,omegae) in the 2D angle-frequency space that minimizes the cost function J serves an estimate for the carrier phase error and carrier frequency error.; The estimated errors may be used to correct the input signal.

  • 15. Ahmed, Zakir
    et al.
    Yajnanarayana, Vijaya
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Maximizing the Viterbi Winning Path Metric to Estimate Carrier Frequency and Phase Offsets in Continuous Phase Modulated Signals2012Patent (Other (popular science, discussion, etc.))
    Abstract [en]

    A system and method for estimating carrier frequency offset Δf and carrier phase offset φ0 inherent in a received CPM signal. Samples of a continuous phase modulated (CPM) signal are received. A maximum of an objective function J is determined over a two-dimensional region parameterized by frequency offset v and phase offset w. The coordinates vmax and wmax of a maximizing point in the region represent estimates of the carrier frequency offset Δf and the carrier phase offset φ0. To evaluate the objective function J at a point (v, w), apply a frequency shift of amount −v and a phase shift of amount −w to the received samples to obtain modified samples, and perform Viterbi demodulation on the modified samples to obtain a winning path metric value at a final time. The winning path metric value is the objective function value J(v, w). 

  • 16.
    Ahmed, Zakir
    et al.
    Motorola India Electron. Ltd., Bangalore .
    Yajnanarayana, Vijaya
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Sancheti, Nirmal Kumar
    A time domain based efficient block decision algorithm for audio coders2007In: International Symposium on Communications and Information Technologies, 2007. ISCIT '07, IEEE Press, 2007, p. 1077-1081Conference paper (Refereed)
    Abstract [en]

    In typical audio encoders the block decision is done either using time-domain techniques like energy computation or frequency domain techniques like temporal noise shaping (TNS) [1], [2]. The time-domain energy computation based decisions are less effective for detecting many of the stringent scenarios presented by test cases like castanets and fatboy. The frequency domain based algorithms have better decision making capabilities, however they are inherently complex as they require the computation of the FFT, additionally in case of TNS the computation of LPC (Linear Prediction coding) in the frequency domain. An improved time-domain technique with better block decision capability compared to TNS and with lesser computational complexity is proposed in this paper.

  • 17. Ahnström, Ulrika
    et al.
    Falk, Johan
    KTH, Superseded Departments, Signals, Sensors and Systems.
    Händel, Peter
    KTH, Superseded Departments, Signals, Sensors and Systems. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Wikström, Maria
    Detection and direction-finding of spread spectrum signals using correlation and narrowband interference rejection2003In: Nordic Matlab Conference 2003, 2003Conference paper (Refereed)
    Abstract [en]

    An algorithm for correlation-based detection of direct sequence spread spectrum signals with direction finding, including direction-filtering and narrow-band interference rejection, is implemented and evaluated in MATLAB. An analog noise-free signal is generated and sampled by a test-bed system. Numerical simulations are run based on data corrupted by mutually uncorrelated white Gaussian noise sequences, and also with recorded noise from two spatially separated HF radio receivers. The simulations and measurements show promising results for detection and direction-finding of covert wideband signals in low SNR and in presence of narrowband interferers. Direction filtering is shown to improve the results.

  • 18.
    Ainomäe, Ahti
    KTH, School of Electrical Engineering (EES), Information Science and Engineering.
    Distributed Detection in Cognitive Radio Networks2017Licentiate thesis, monograph (Other academic)
    Abstract [en]

    One of the problems with the modern radio communication is the lack of availableradio frequencies. Recent studies have shown that, while the available licensed radiospectrum becomes more occupied, the assigned spectrum is significantly underutilized.To alleviate the situation, cognitive radio (CR) technology has been proposedto provide an opportunistic access to the licensed spectrum areas. Secondary CRsystems need to cyclically detect the presence of a primary user by continuouslysensing the spectrum area of interest. Radiowave propagation effects like fading andshadowing often complicate sensing of spectrum holes. When spectrum sensing isperformed in a cooperative manner, then the resulting sensing performance can beimproved and stabilized.

    In this thesis, two fully distributed and adaptive cooperative Primary User (PU)detection solutions for CR networks are studied.

    In the first part of this thesis we study a distributed energy detection schemewithout using any fusion center. Due to reduced communication such a topologyis more energy efficient. We propose the usage of distributed, diffusion least meansquare (LMS) type of power estimation algorithms with different network topologies.We analyze the resulting energy detection performance by using a commonframework and verify the theoretical findings through simulations.

    In the second part of this thesis we propose a fully distributed detection scheme,based on the largest eigenvalue of adaptively estimated correlation matrices, assumingthat the primary user signal is temporally correlated. Different forms of diffusionLMS algorithms are used for estimating and averaging the correlation matrices overthe CR network. The resulting detection performance is analyzed using a commonframework. In order to obtain analytic results on the detection performance, theadaptive correlation matrix estimates are approximated by a Wishart distribution.The theoretical findings are verified through simulations.

  • 19.
    Ainomäe, Ahti
    et al.
    KTH, School of Electrical Engineering (EES), Information Science and Engineering. Tallinn University of Technology, Estonia.
    Trump, T.
    Bengtsson, Mats
    KTH, School of Electrical Engineering (EES), Information Science and Engineering.
    Distributed largest eigenvalue detection2017In: 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017, Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 3519-3523, article id 7952811Conference paper (Refereed)
    Abstract [en]

    Cognitive radio (CR) systems need to detect the presence of a primary user (PU) signal by continuously sensing the spectrum area of interest. Radiowave propagation effects like fading and shadowing often complicate sensing of spectrum holes because the PU signal can be weak in a particular area. Cooperative spectrum sensing is seen as a prospective solution to enhance the detection of PU signals. In this paper we study distributed spectrum sensing, based on the largest eigenvalue of adaptively estimated correlation matrices (CMs) of received signals. The PU signal is assumed to be temporally correlated. In this paper an Combine and Adapt (CTA) least Mean Square (LMS) diffusion based mean vector estimation scheme is proposed. No fusion center (FC) for estimation or detection is used. We analyse the resulting detection performance and verify the theoretical findings through simulations.

  • 20.
    Ainomäe, Ahti
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. Tallinn Univ. of Technol., Tallinn, Estonia.
    Trump, Tõnu
    Tallinn Univ. of Technol., Tallinn, Estonia.
    Bengtsson, Mats
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Distributed Diffusion LMS based Energy Detection2014In: Proceedings of 6th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT), 2014, 2014, p. 176-183Conference paper (Refereed)
    Abstract [en]

    Cognitive radio (CR) is seen as a promising technology to make radio spectrum usage more effective by providing an opportunistic access for secondary users to the licensed spectrum areas. CR systems need to detect the presence of a primary user (PU) signal by continuously sensing the spectrum area of interest. Radiowave propagation effects like fading and shadowing often complicate sensing of spectrum holes because the PU signal can be weak in a particular area. Cooperative spectrum sensing is seen as a prospective solution to enhance the detection of PU signals. This paper studies distributed spectrum sensing in a cognitive radio context. We investigate distributed energy detection schemes without using any fusion center. We propose the usage of distributed, diffusion least mean square (LMS) type of power estimation algorithms. In this paper an Adapt and Combine (ATC) diffusion based power estimation scheme is proposed and the performance is compared with the Combine and Adapt (CTA) and ring-around schemes in a common framework. The PU signal is assumed to be slowly fading. We analyse the resulting energy detection performance and verify the theoretical findings through simulations.

  • 21.
    Ainomäe, Ahti
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. Department of Radio and Telecommunication Engineering, Tallinn University of Technology, Tallinn, Estonia .
    Trump, Tõnu
    Tallin University of Technology.
    Bengtsson, Mats
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Distributed Recursive Energy Detection2014In: Proceedings of Wireless Communications and Networking Conference (WCNC), 2014, IEEE Communications Society, 2014, p. 1242-1247Conference paper (Refereed)
    Abstract [en]

    Recent studies have shown that, while the available licensed radio spectrum becomes more occupied, the assigned spectrum is significantly underutilized. To alleviate the situation, cognitive radio (CR) technology has been proposed to provide an opportunistic access to the licensed spectrum areas. CR systems are able to serve the secondary users for detecting and utilizing so called spectrum holes by sensing and adapting to the environment without causing harmful effects or interference to the licensed primary users (PU). CR systems need to detect the presence of a primary user by continuously sensing the spectrum area of interest. Radiowave propagation effects like fading and shadowing often complicate sensing of spectrum holes because the PU signal can be weak in a particular area. Cooperative spectrum sensing is seen as a prospective solution to enhance the detection of PU signals. This paper studies distributed spectrum sensing in a cognitive radio context. We investigate a distributed energy detection scheme without using any fusion center. Due to reduced communication such a topology is more energy efficient. The PU signal is assumed to be in slow fading. A recursive distributed power estimation and detection scheme is proposed. The theoretical findings are verified through simulations.

  • 22.
    Akbarnejad, Shahin
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Materials Science and Engineering, Applied Process Metallurgy.
    Kennedy, M. W.
    Fritzsch, R.
    Aune, R. E.
    An investigation on permeability of ceramic foam filters (CFF)2015In: TMS Light Metals, 2015, p. 949-954Conference paper (Refereed)
    Abstract [en]

    CFFs are used to filter liquid metal in the aluminum industry. CFFs are classified in grades or pores per inch (PPI), ranging from 10-100 PPI. Their properties vary in everything from pore and strut size to window size. CFFs of 80-100 PPI are generally not practical for use by industry, as priming of the filters by gravitational forces requires an excessive metal head. Recently, co-authors have invented a method to prime such filters using electromagnetic Lorentz forces, thus allowing filters to be primed with a low metal head. In the continuation of this research work, an improved experimental setup was developed in the present study to validate previous results and to measure the permeability of different filters, as well as a stack of filters. The study of permeability facilitates estimation of the required pressure drop to prime the filters and the head required to generate a given casting rate.

  • 23. Al Ismaeil, K.
    et al.
    Aouada, D.
    Mirbach, B.
    Ottersten, Björn
    Interdisciplinary Centre for Security, Reliability and Trust, Universtity of Luxembourg, Luxembourg.
    Depth super-resolution by enhanced shift and add2013In: Computer Analysis of Images and Patterns: 15th International Conference, CAIP 2013, York, UK, August 27-29, 2013, Proceedings, Part II, Springer, 2013, Vol. 8048 LNCS, no PART 2, p. 100-107Conference paper (Refereed)
    Abstract [en]

    We use multi-frame super-resolution, specifically, Shift & Add, to increase the resolution of depth data. In order to be able to deploy such a framework in practice, without requiring a very high number of observed low resolution frames, we improve the initial estimation of the high resolution frame. To that end, we propose a new data model that leads to a median estimation from densely upsampled low resolution frames. We show that this new formulation solves the problem of undefined pixels and further allows to improve the performance of pyramidal motion estimation in the context of super-resolution without additional computational cost. As a consequence, it increases the motion diversity within a small number of observed frames, making the enhancement of depth data more practical. Quantitative experiments run on the Middlebury dataset show that our method outperforms state-of-the-art techniques in terms of accuracy and robustness to the number of frames and to the noise level.

  • 24. Al Ismaeil, K.
    et al.
    Aouada, D.
    Mirbach, B.
    Ottersten, Björn
    Advanced Engineering - IEE S.A., Luxembourg .
    Dynamic super resolution of depth sequences with non-rigid motions2013In: 2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings, IEEE Signal Processing Society, 2013, p. 660-664Conference paper (Refereed)
    Abstract [en]

    We enhance the resolution of depth videos acquired with low resolution time-of-flight cameras. To that end, we propose a new dedicated dynamic super-resolution that is capable to accurately super-resolve a depth sequence containing one or multiple moving objects without strong constraints on their shape or motion, thus clearly outperforming any existing super-resolution techniques that perform poorly on depth data and are either restricted to global motions or not precise because of an implicit estimation of motion. The proposed approach is based on a new data model that leads to a robust registration of all depth frames after a dense upsampling. The textureless nature of depth images allows to robustly handle sequences with multiple moving objects as confirmed by our experiments.

  • 25. Al Ismaeil, K.
    et al.
    Aouada, D.
    Mirbach, B.
    Ottersten, Björn
    SnT - Universtity of Luxembourg, Luxembourg .
    Multi-frame super-resolution by enhanced shift & add2013In: 2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA), IEEE , 2013, p. 171-176Conference paper (Refereed)
    Abstract [en]

    A critical step in multi-frame super-resolution is the registration of frames based on their motion. We improve the performance of current state-of-the-art super-resolution techniques by proposing a more robust and accurate registration as early as in the initialization stage of the high resolution estimate. Indeed, we solve the limitations on scale and motion inherent to the classical Shift & Add approach by upsampling the low resolution frames up to the super-resolution factor prior to estimating motion or to median filtering. This is followed by an appropriate selective optimization, leading to an enhanced Shift & Add. Quantitative and qualitative evaluations have been conducted at two levels; the initial estimation and the final optimized superresolution. Results show that the proposed algorithm outperforms existing state-of-art methods.

  • 26. Al Ismaeil, Kassem
    et al.
    Aouada, Djamila
    Mirbach, Bruno
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Bilateral Filter Evaluation Based on Exponential Kernels2012Conference paper (Refereed)
    Abstract [en]

    The well-known bilateral filter is used to smooth noisy images while keeping their edges. This filter is commonly used with Gaussian kernel functions without real justification. The choice of the kernel functions has a major effect on the filter behavior. We propose to use exponential kernels with L1 distances instead of Gaussian ones. We derive Stein's Unbiased Risk Estimate to find the optimal parameters of the new filter and compare its performance with the conventional one. We show that this new choice of the kernels has a comparable smoothing effect but with sharper edges due to the faster, smoothly decaying kernels.

  • 27.
    Alam, Assad
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Asplund, Fredrik
    KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.
    Behere, Sagar
    KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.
    Björk, Mattias
    KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.
    Garcia Alonso, Liliana
    KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.
    Khaksari, Farzad
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Khan, Altamash
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Kjellberg, Joakim
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Liang, Kuo-Yun
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Lyberger, Rickard
    Scania CV AB.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Nilsson, John-Olof
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Pettersson, Henrik
    Scania CV AB.
    Pettersson, Simon
    KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.
    Stålklinga, Elin
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Sundman, Dennis
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Zachariah, Dave
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Cooperative driving according to Scoop2011Report (Other academic)
    Abstract [en]

    KTH Royal Institute of Technology and Scania are entering the GCDC 2011 under the name Scoop –Stockholm Cooperative Driving. This paper is an introduction to their team and to the technical approach theyare using in their prototype system for GCDC 2011.

  • 28.
    Al-Askary, Omar
    KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS.
    Coding and Iterative Decoding of Concentrated Multi-level Codes for the Rayleigh Fading Channel2006Doctoral thesis, monograph (Other scientific)
    Abstract [en]

    In this thesis we present the concept of concatenated multilevel codes. These codes are a combination of generalized concatenated codes with multilevel coding. The structure of these codes is simple and relies on the concatenation of two or more codes of shorter length. These codes can be designed to have large diversity which makes them attractive for use in fading channels. We also present an iterative decoding algorithm taylored to fit the properties of the proposed codes. The iterative decoding algorithm we present has a complexity comparable to the complexity of GMD decoding of the same codes. However, The gain obtained by using the iterative decoder as compared to GMD decdoing of these codes is quite high for Rayleigh fading channels at bit error rates of interest. Some bounds on the performance of these codes are given in this thesis. Some of the bounds are information theoretic bounds which can be used regardless of the code under study. Other bounds are on the error probability of concatenated multilevel codes.

    Finally we give examples on the implementation of these codes in adaptive coding of OFDM channels and MIMO channels.

  • 29.
    Aldayel, Omar
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. King Saud University, Saudi Arabia.
    Bengtsson, Mats
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Alshebeili, Saleh A.
    King Saud University, Saudi Arabia.
    Evaluation of MIMO channel non-stationarity2013In: 2013 Proceedings of the 21st European Signal Processing Conference (EUSIPCO), IEEE , 2013, p. 6811769-Conference paper (Refereed)
    Abstract [en]

    Several MIMO processing algorithms have been proposed that exploit long-term channel statistics, relaying on the critical assumption that this long-term information is valid long enough. In this paper, we consider the Correlation Matrix Distance (CMD) method previously proposed for the evaluation of MIMO channel non-stationarity. We highlight a couple of problems with the CMD measure and propose two new metrics that are more appropriate for non-stationarity evaluation. The performance of the CMD method and new correlation matrix distance metrics is investigated using measured 4×4 MIMO channels. Both Line-of-Sight (LOS) and Non-LOS (NLOS) environments are considered.

  • 30.
    Al-Ghazu, Nader
    KTH, School of Electrical Engineering (EES), Signal Processing.
    A Study of the Next WLAN Standard IEEE 802.11ac Physical Layer2013Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    This thesis studies the Physical Layer (PHY) of the new IEEE 802.11acWireless Local Access Network (WLAN) standard. The 11ac is built basedon the 11n successful standard. The standard is expected to be completedby the end of 2013. And it promises a Very High Throughput (VHT),and robust communication. In order to achieve that, the 11ac uses morebandwidth, it employs higher numbers of Multiple-Input Multiple-Output(MIMO) spatial streams, and higher orders of modulations. The 11ac PHYframe structure is studied in details. The transmitter and receiver blocks areexplained and implemented by MATLAB. Bit Error Rate (BER) and ErrorVector Magnitude (EVM) simulations of the PHY were run. The effectof different Modulation and Coding Scheme (MCS), and bandwidths werestudied. The performance of MIMO and Space-Time Block Coding (STBC)was investigated. The simulation results shows how the 11ac benefits fromthe new employed features. The created MATLAB simulation program canbe used for further tests and research.

  • 31. Ali Khan, N.
    et al.
    Ali, S.
    Jansson, Magnus
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Direction of arrival estimation using adaptive directional time-frequency distributions2018In: Multidimensional systems and signal processing, ISSN 0923-6082, E-ISSN 1573-0824, Vol. 29, no 2, p. 503-521Article in journal (Refereed)
    Abstract [en]

    Time-frequency distributions (TFDs) allow direction of arrival (DOA) estimation algorithms to be used in scenarios when the total number of sources are more than the number of sensors. The performance of such time-frequency (t-f) based DOA estimation algorithms depends on the resolution of the underlying TFD as a higher resolution TFD leads to better separation of sources in the t-f domain. This paper presents a novel DOA estimation algorithm that uses the adaptive directional t-f distribution (ADTFD) for the analysis of close signal components. The ADTFD optimizes the direction of kernel at each point in the t-f domain to obtain a clear t-f representation, which is then exploited for DOA estimation. Moreover, the proposed methodology can also be applied for DOA estimation of sparse signals. Experimental results indicate that the proposed DOA algorithm based on the ADTFD outperforms other fixed and adaptive kernel based DOA algorithms.

  • 32.
    Ali, Sadiq
    Electrical Engineering, University of Engineering and Technology of Peshawar, Pakistan.
    Seco-Granados, Gonzalo
    Telecommunications and Systems Engineering, Universitat Autònoma de Barcelona, Spain.
    Lopez-Salcedo, Jose A.
    Universitat Autònoma de Barcelona, Spain.
    Kronecker-Based Fusion Rule for Cooperative Spectrum Sensing with Multi-Antenna Receivers2014In: Electronics, ISSN 2079-9292, Vol. 3, no 4, p. 675-688Article in journal (Refereed)
    Abstract [en]

    This paper considers a novel fusion rule for spectrum sensing scheme for a cognitive radio network with multi-antenna receivers. The proposed scheme exploits the fact that when any primary signal is present, measurements are spatially correlated due to presence of inter-antenna and inter-receiver spatial correlation. In order to exploit this spatial structure, the generalized likelihood ratio test (GLRT) operates with the determinant of the sample covariance matrix. Therefore, it depends on the sample size N and the dimensionality of the received data (i.e., the number of receivers K and antennas L). However, when the dimensionality fK; Lg is on the order, or larger than the sample size N, the GLRT degenerates due to the ill-conditioning of the sample covariance matrix. In order to circumvent this issue, we propose two techniques that exploit the inner spatial structure of the received observations by using single pair and multi-pairs Kronecker products. The performance of the proposed detectors is evaluated by means of numerical simulations, showing important advantages with respect to the traditional (i.e., unstructured) GLRT approach.

  • 33.
    Ali, Sadiq
    et al.
    Universitat Autònoma de Barcelona (UAB),.
    Jansson, Magnus
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Seco-Granados, Gonzalo
    Universitat Autònoma de Barcelona (UAB),.
    López-Salzedo, José A.
    Universitat Autònoma de Barcelona (UAB),.
    Novel collaborative spectrum sensing based on spatial covariance structure2013In: 2013 Proceedings of the 21st European Signal Processing Conference (EUSIPCO), 2013, p. 6811678-Conference paper (Refereed)
    Abstract [en]

    In collaborative spectrum sensing, spatial correlation in the measurements obtained by sensors can be exploited by adopting Generalized Likelihood Ratio Test (GLRT). In this process the GLRT provides a test statistics that is normally based on the sample covariance matrix of the received signal samples. Unfortunately, problems arise when the dimensions of this matrix become excessively large, as it happens in the so-called large-scale wireless sensor networks. In these circumstances, a huge amount of samples are needed in order to avoid the ill-conditioning of the GLRT, which degenerates when the dimensionality of data is equal to the sample size or larger. To circumvent this problem, we modify the traditional GLRT detector by decomposing the large spatial covariance matrix into small covariance matrices by using properties of the Kronecker Product. The proposed detection scheme is robust in the case of high dimensionality and small sample size. Numerical results are drawn, which show that the proposed detection schemes indeed outperform the traditional approaches when the dimension of data is larger than the sample size.

  • 34.
    Alizadeh, Mahmoud
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. Univ Gavle, Sweden.
    Amin, Shoaib
    KTH, School of Electrical Engineering (EES), Signal Processing. Univ Gavle, Sweden.
    Ronnow, Daniel
    Measurement and Analysis of Frequency-Domain Volterra Kernels of Nonlinear Dynamic 3 x 3 MIMO Systems2017In: IEEE Transactions on Instrumentation and Measurement, ISSN 0018-9456, E-ISSN 1557-9662, Vol. 66, no 7, p. 1893-1905Article in journal (Refereed)
    Abstract [en]

    Multiple-input multiple-output (MIMO) frequencydomain Volterra kernels of nonlinear order 3 are experimentally determined in bandwidth-limited frequency regions. How the effect of higher nonlinear orders can be reduced and how this affects the estimated errors are discussed. The magnitude and the phase of the kernels are Kramers-Kronig consistent. The self-kernels and cross-kernels have different symmetries, and the kernels are therefore determined and analyzed in different regions in the 3-D frequency space. By analyzing the properties along certain paths in the 3-D frequency space, the block structures for the respective kernels are determined. These block structures contain the significant blocks of the general block structures for the third-order kernels. The device under test is an MIMO transmitter for radio frequency signals.

  • 35.
    Alizadeh, Mahmoud
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Amin, Shoaib
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Rönnow, Daniel
    ATM, University of Gävle.
    Measurement and analysis of frequency-domainVolterra kernels of nonlinear dynamic 3x3 MIMO systems2016In: IEEE Transactions on Instrumentation and Measurement, ISSN 0018-9456, E-ISSN 1557-9662Article in journal (Refereed)
    Abstract [en]

    Multiple-input multiple-output (MIMO) frequency-domain Volterra kernels of nonlinear order 3 are experimentally determined in bandwidth-limited frequency regions. How the effect of higher nonlinear orders can be reduced and how this affects the estimated errors are discussed. The magnitude and phase of the kernels areKramers-Kronig consistent. The self- and cross-kernels have different symmetries and the kernels are therefore determined and analyzed in different regions in the 3D frequency space. By analyzing the properties along certain paths in the 3D frequency space, the block structures for the respective kernels are determined. These block structures contain the significant blocks of the general block structures for third-order kernels. The device under test is a MIMO transmitter for radio frequency signals.

  • 36. Alodeh, M.
    et al.
    Chatzinotas, S.
    Ottersten, Björn
    A multicast approach for constructive interference precoding in MISO downlink channel2014In: 2014 IEEE International Symposium on Information Theory, IEEE conference proceedings, 2014, p. 2534-2538Conference paper (Refereed)
    Abstract [en]

    This paper studies the concept of jointly utilizing the data information (DI) and channel state information (CSI) in order to design symbol-level precoders for a multiple input and single output (MISO) downlink channel. In this direction, the interference among the simultaneous data streams is transformed to useful signal that can improve the signal to interference noise ratio (SINR) of the downlink transmissions. We propose a maximum ratio transmissions (MRT) based algorithm that jointly exploits DI and CSI to gain the benefits from these useful signals. In this context, a novel framework to minimize the power consumption is proposed by formalizing the duality between the constructive interference downlink channel and the multicast channels. The numerical results have shown that the proposed schemes outperform other state of the art techniques.

  • 37. Alodeh, M.
    et al.
    Chatzinotas, S.
    Ottersten, Björn
    Joint channel estimation and pilot allocation in underlay cognitive MISO networks2014In: 2014 International Wireless Communications and Mobile Computing Conference (IWCMC), IEEE conference proceedings, 2014, p. 797-802Conference paper (Refereed)
    Abstract [en]

    Cognitive radios have been proposed as agile technologies to boost the spectrum utilization. This paper tackles the problem of channel estimation and its impact on downlink transmissions in an underlay cognitive radio scenario. We consider primary and cognitive base stations, each equipped with multiple antennas and serving multiple users. Primary networks often suffer from the cognitive interference, which can be mitigated by deploying beamforming at the cognitive systems to spatially direct the transmissions away from the primary receivers. The accuracy of the estimated channel state information (CSI) plays an important role in designing accurate beamformers that can regulate the amount of interference. However, channel estimate is affected by interference. Therefore, we propose different channel estimation and pilot allocation techniques to deal with the channel estimation at the cognitive systems, and to reduce the impact of contamination at the primary and cognitive systems. In an effort to tackle the contamination problem in primary and cognitive systems, we exploit the information embedded in the covariance matrices to successfully separate the channel estimate from other users' channels in correlated cognitive single input multiple input (SIMO) channels. A minimum mean square error (MMSE) framework is proposed by utilizing the second order statistics to separate the overlapping spatial paths that create the interference. We validate our algorithms by simulation and compare them to the state of the art techniques.

  • 38. Alodeh, M.
    et al.
    Chatzinotas, S.
    Ottersten, Björn
    Spatial DCT-based least square estimation in multi-antenna multi-cell interference channels2014In: 2014 IEEE International Conference on Communications (ICC), IEEE conference proceedings, 2014, p. 4729-4734Conference paper (Refereed)
    Abstract [en]

    Interference management techniques in multicell multiple input multiple output (MIMO) networks require accurate channel state information (CSI). A popular technique for acquiring this CSI in time division duplex (TDD) systems is uplink training by exploiting the reciprocity of the wireless medium. Recently, the pilot contamination problem has been identified as one of the limiting factors for such kind of CSI acquisition. In an effort to tackle the problem of contamination, we utilize the compression capability of discrete cosine transform (DCT) and covariance matrices to spatially separate the estimate for the scenario of correlated single input multiple input (SIMO) channels. A least square estimation framework is proposed 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 the interfering users. We validate our algorithms by simulation and compare them to the state of the art techniques.

  • 39. Ambat, S. K.
    et al.
    Chatterjee, Saikat
    KTH, School of Electrical Engineering (EES), Communication Theory.
    Hari, K. V. S.
    Fusion of algorithms for Compressed Sensing2013In: ICASSP IEEE Int Conf Acoust Speech Signal Process Proc, 2013, p. 5860-5864Conference paper (Refereed)
    Abstract [en]

    Numerous algorithms have been proposed recently for sparse signal recovery in Compressed Sensing (CS). In practice, the number of measurements can be very limited due to the nature of the problem and/or the underlying statistical distribution of the non-zero elements of the sparse signal may not be known a priori. It has been observed that the performance of any sparse signal recovery algorithm depends on these factors, which makes the selection of a suitable sparse recovery algorithm difficult. To take advantage in such situations, we propose to use a fusion framework using which we employ multiple sparse signal recovery algorithms and fuse their estimates to get a better estimate. Theoretical results justifying the performance improvement are shown. The efficacy of the proposed scheme is demonstrated by Monte Carlo simulations using synthetic sparse signals and ECG signals selected from MIT-BIH database.

  • 40. Ambat, Sooraj K.
    et al.
    Chatterjee, Saikat
    KTH, School of Electrical Engineering (EES), Communication Theory.
    Hari, K. V. S.
    A Committee Machine Approach for Compressed Sensing Signal Reconstruction2014In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 62, no 7, p. 1705-1717Article in journal (Refereed)
    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.

  • 41. Ambat, Sooraj K.
    et al.
    Chatterjee, Saikat
    KTH, School of Electrical Engineering (EES), Communication Theory.
    Hari, K. V. S.
    Fusion of Algorithms for Compressed Sensing2013In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 61, no 14, p. 3699-3704Article in journal (Refereed)
    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.

  • 42.
    Ambat, Sooraj K.
    et al.
    IISc - Indian Institute of Science.
    Chatterjee, Saikat
    KTH, School of Electrical Engineering (EES), Communication Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Hari, K.V.S.
    IISc - Indian Institute of Science.
    Fusion of greedy pursuits for compressed sensing signal reconstruction2012In: 2012 Proceedings Of The 20th European Signal Processing Conference (EUSIPCO), IEEE Computer Society, 2012, p. 1434-1438Conference paper (Refereed)
    Abstract [en]

    Greedy Pursuits are very popular in Compressed Sensing for sparse signal recovery. Though many of the Greedy Pursuits possess elegant theoretical guarantees for performance, it is well known that their performance depends on the statistical distribution of the non-zero elements in the sparse signal. Inpractice, the distribution of the sparse signal may not be knowna priori. It is also observed that performance of Greedy Pursuits degrades as the number of available measurements decreases from a threshold value which is method dependent. To improve the performance in these situations, we introduce a novel fusion framework for Greedy Pursuits and also propose two algorithms for sparse recovery. Through Monte Carlo simulations we show that the proposed schemes improve sparse signal recovery in clean as well as noisy measurement cases.

  • 43.
    Amin, Shoaib
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Characterization and Linearization of Multi-band Multi-channel RF Power Amplifiers2017Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The World today is deeply transformed by the advancement in wireless technology. The envision of a smart society where interactions between physical and virtual dimensions of life are intertwined and where human interaction is mediated by machines, e.g., smart phones, demands increasingly more data traffic. This continual increase in data traffic requires re-designing of the wireless technologies for increased system capacity and flexibility. In this thesis, aspects related to behavioral modeling, characterization, and linearization of multi-channel/band power amplifiers (PAs) are discussed.

    When building a model of any system, it is advantageous to take into account the knowledge of the physics of the system and include into the model. This approach could help to improve the model performance. In this context, three novel behavioral models and DPD schemes for nonlinear MIMO transmitters are proposed.

    To model and compensate distortions in GaN based RF PAs in presence of long-term memory effects, novel models for SISO and concurrent dual-band PAs are proposed. These models are based on a fixed pole expansion technique and have infinite impulse response. They show substantial performance improvement. A behavioral model based on the physical knowledge of the concurrent dual-band PA is derived, and its performance is investigated both for behavioral modeling and compensation of nonlinear distortions.

    Two-tone characterization is a fingerprint method for the characterization of memory effects in dynamic nonlinear systems. In this context, two novel techniques are proposed. The first technique is a dual two-tone characterization technique to characterize the memory effects of self- and cross-modulation products in concurrent dual-band transmitter. The second technique is for the characterization and analysis of self- and cross-Volterra kernels of nonlinear 3x3 MIMO systems using three-tone signals.

  • 44.
    Amin, Shoaib Amin
    KTH, School of Electrical Engineering (EES), Signal Processing. University of Gävle, Sweden.
    Characterization and Linearization of Multi-channel RF Power Amplifiers2015Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    The demands for high data rates and broadband wireless access require the development of wireless systems that can support wide and multi-band signals. To deploy these signals, new radio frequency (RF) front-ends are required which impose new challenges in terms of power consumption efficiency and sources of distortion e.g., nonlinearity. These challenges are more pronounced in power amplifiers (PAs) that degrade the overall performance of the RF transmitter. Since it is difficult to optimize the linearity and efficiency characteristics of a PA simultaneously, a trade-off is needed. At high input power, a PA exhibits high efficiency at the expense of linearity. On the other hand, at low input power, a PA is linear at the expense of the efficiency. To achieve linearity and efficiency at the same time, digital pre-distortion (DPD) is often used to compensate for the PA nonlinearity at high input power. In case of multi-channel PAs, input and output signals of different channels interact with each other due to cross-talk. Therefore, these PAs exhibit different nonlinear behavior than the single-input single-output (SISO) PAs. The DPD techniques developed for SISO PAs do not result in adequate performance when used for multi-channel PAs. Hence, an accurate behavioral modeling is essential for the development of DPD for multi-channel RF PAs. In this thesis, we propose three novel behavioral models and DPD schemes for nonlinear multiple-input multiple-output (MIMO) transmitters in presence of cross-talk. A study of the source of cross-talk in MIMO transmitters have been investigated to derive simple and powerful modeling schemes. These models are extensions of a SISO generalized memory polynomial model. A comparative study with a previously published MIMO model is also presented. The effect of coherent and partially non-coherent signal generationon DPD performance is also highlighted. It is shown experimentally that with partially non-coherent signal generation, the performance of the DPD degrades compared to coherent signal generation. In context of multi-channel RF transmitters, PA behavioral models and DPD schemes suffer from a large number of model parameters with the increase in nonlinear order and memory depth. This growth leads to high complexity model identification and implementation. We have designed a DPD scheme for MIMO PAs using a sparse estimation technique for reducing model complexity. This technique also increases the numerical stability when linear least square estimation model identification is used. A method to characterize the memory effects in a nonlinear concurrent dual-band PAs is also presented. Compared to the SISO PAs, concurrent dual-band PAs are not only affected by intermodulation distortions but also by cross-modulation distortions. The characterization of memory effects inconcurrent dual-band transmitter is performed by injecting a two-tone test signal in each input channel of the transmitter. Asymmetric energy surfaces are introduced for the intermodulation and cross-modulation products, which can be used to identify the power and frequency regions where the memory effects are dominant.

  • 45.
    Amin, Shoaib
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. University of Gävle, Sweden.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Rönnow, Daniel
    ATM, University of Gävle.
    Digital Predistortion of Single and Concurrent Dual BandRadio Frequency GaN Amplifiers with Strong NonlinearMemory Effects2017In: IEEE transactions on microwave theory and techniques, ISSN 0018-9480, E-ISSN 1557-9670, Vol. 65, no 7, p. 2453-2464Article in journal (Refereed)
    Abstract [en]

    Electrical anomalies due to trapping effects in gallium nitride (GaN) power amplifiers (PAs) give rise to long-term or strong memory effects. We propose novel models based on infinite impulse response fixed pole expansion techniques for the behavioral modeling and digital predistortion of single-input single-output (SISO) and concurrent dual-band GaN PAs. Experimental results show that the proposed models outperform the corresponding finite impulse response (FIR) models by up to 17 dB for the same number of model parameters. For the linearization of a SISO GaN PA, the proposed models give adjacent channel power ratios (ACPRs) that are 7-17 dB lower than the FIR models. For the concurrent dual-band case, the proposed models give ACPRs that are 9-14 dB lower than the FIR models.

  • 46.
    Amin, Shoaib
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Khan, Zain Ahmed
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Isaksson, Magnus
    Högskolan i Gävle.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Rönnow, Daniel
    Högskolan i Gävle.
    Concurrent Dual-band Power Amplifier Model Modification using Dual Two-Tone Test2016In: European Microwave Week 2016: "Microwaves Everywhere", EuMW 2016 - Conference Proceedings; 46th European Microwave Conference, EuMC 2016, Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 186-189, article id 7824309Conference paper (Refereed)
    Abstract [en]

    A dual two-tone technique for the characterization of memory effects in concurrent dual-band transmitters is revisited to modify a 2D-DPD model for the linearization of concurrent dual-band transmitters. By taking into account the individual nonlinear memory effects of the self- and cross-kernels, a new2D modified digital pre-distortion (2D-MDPD) model is proposed,which not only supersedes the linearization performance but also reduces the computational complexity compared to the 2DDPDmodel in terms of a number of floating point operations(FLOPs). Experimental results show an improvement of 1.7 dBin normalized mean square error (NMSE) and a 58% reduction in the number of FLOPs.

  • 47.
    Amin, Shoaib
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Ladin, Per N.
    ATM, University of Gävle.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Rönnow, Daniel
    ATM, University of Gävle.
    2D Extended Envelope Memory Polynomial Model forConcurrent Dual-band RF Transmitters2016In: International journal of microwave and wireless technologies, ISSN 1759-0795, E-ISSN 1759-0787Article in journal (Refereed)
    Abstract [en]

    The paper presents a 2D extended envelope memory polynomial (2D-EEMP) model for concurrent dual-band radio frequency (RF) power amplifiers (PAs). The model is derived based on the physical knowledge of a dual-band RF PA. The derived model contains cross-modulation terms not included in previously published models; these terms are found to be of importance for both behavioral modeling and digital pre-distortion (DPD). The performance of the derived model is evaluated both as the behavioral model and DPD, and the performance is compared with state-of-the-art2D-DPD and dual-band generalized memory polynomial (DB-GMP) models. Experimental result shows that the proposed model resulted in normalized mean square error (NMSE) of -51.7/-51.6dB and adjacent channel error power ratio (ACEPR) of -63.1/-63.4 dB, for channel 1/2, whereas the 2D-DPD resulted in the largest model error and DB-GMP resulted in model parameters that are 3 times more than those resulted with the proposed model with the same performance. As pre-distorter, the proposed model resulted in adjacent channel power ratio (ACPR) of -55.8/ -54.6 dB for channel 1/2 and is 7-10 dB lower than those resulted with the 2D-DPD model and2-4 dB lower compared to the DB-GMP model.

  • 48.
    Amin, Shoaib
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. Högskolan i Gävle.
    Landin, Per
    Chalmers University of Technology.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Rönnow, Daniel
    Högskolan i Gävle.
    Behavioral modeling and linearization of crosstalk and memory effects in RF MIMO transmitters2014In: IEEE transactions on microwave theory and techniques, ISSN 0018-9480, E-ISSN 1557-9670, Vol. 62, no 4, p. 810-823Article in journal (Refereed)
    Abstract [en]

    This paper proposes three novel models for behavioral modeling and digital pre-distortion (DPD) of nonlinear 2 x 2 multiple-input multiple-output (MIMO) transmitters in the presence of crosstalk. The proposed models are extensions of the single-input single-output generalized memory polynomial model. Three types of crosstalk effects were studied and characterized as linear, nonlinear, and nonlinear & linear crosstalk. A comparative study was performed with previously published models for the linearization of crosstalk in a nonlinear 2 x 2 MIMO transmitter. The experiments indicate that, depending on the type of crosstalk, the selection of the correct model in the transmitter is necessary for behavioral modeling and sufficient DPD performance. The effects of coherent and partially noncoherent signal generation on the performance of DPD were also studied. For crosstalk levels of 30 dB, the difference in the normalized mean square error and adjacent channel power ratio was found to be 3-4 dB between coherent and partially noncoherent signal generation.

  • 49.
    Amin, Shoaib
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. University of Gävle, Sweden.
    Van Moer, Wendy
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Rönnow, Daniel
    Characterization of a Concurrent dual-band Power Amplifier using a dual-tone excitation signals2014In: IEEE Transactions on Instrumentation and Measurement, ISSN 0018-9456, E-ISSN 1557-9662Article in journal (Other academic)
  • 50.
    Amin, Shoaib
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Van Moer, Wendy
    University of Gävle.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Rönnow, Daniel
    University of Gävle.
    Characterization of concurrent dual-band Power Amplifiers using a dual two-tone excitation signal2015In: IEEE Transactions on Instrumentation and Measurement, ISSN 0018-9456, E-ISSN 1557-9662, no 99Article in journal (Refereed)
    Abstract [en]

    A method to characterize the memory effects in a nonlinear concurrent dual-band transmitter is presented. It is an extension of the conventional two tone test for power amplifiers to concurrent dual band transmitters. The output signal of a concurrent dual-band transmitter is affected not only by intermodulation products but also by cross-modulation products. In one frequency band, the transmitter is excited by a two tone signal which frequency separation is swept. In the second band the transmitter is concurrently excited by an other two tone signal with slightly wider frequency separation. The frequency difference of the two signals is fixed during the frequency sweep. The two tone test is made at different power levels. The upper and lower third-order inter- and cross-modulation products are measured. The asymmetry between the upper and lower third-order inter- and cross-modulation products are measures of the transmitter's memory effects. The measurement results show that the memory effects are more dominant in the third-order intermodulation products than in the cross modulation products. An error analysis and system calibration was performed and measurement results for two different devices are presented.

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