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  • 1.
    Ainomae, Ahti
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Bengtsson, Mats
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Trump, Tonu
    Tallinn Univ Technol, Dept Radio & Telecommun Engn, EE-12616 Tallinn, Estonia..
    Distributed Largest Eigenvalue-Based Spectrum Sensing Using Diffusion LMS2018In: IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS, ISSN 2373-776X, Vol. 4, no 2, p. 362-377Article in journal (Refereed)
    Abstract [en]

    In this paper, we propose a distributed detection scheme for cognitive radio (CR) networks, based on the largest eigenvalues (LEs) of adaptively estimated correlation matrices (CMs), assuming that the primary user signal is temporally correlated. The proposed algorithm is fully distributed, there by avoiding the potential single point of failure that a fusion center would imply. Different forms of diffusion least mean square algorithms are used for estimating and averaging the CMs over the CR network for the LE detection and the resulting estimation performance is analyzed using a common framework. In order to obtain analytic results on the detection performance, the exact distribution of the CM estimates are approximated by a Wishart distribution, by matching the moments. The theoretical findings are verified through simulations.

  • 2.
    Alizadeh, Mahmoud
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. Department of Electronics, Mathematics and Natural Sciences, University of Gävle (HiG), Gävle, Sweden.
    Rönnow, D.
    Händel, Peter
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Characterization of Volterra Kernels for RF Power Amplifiers Using a Two-Tone Signal and a Large-Signal2018In: 2018 12th International Conference on Communications, COMM 2018 - Proceedings, Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 351-356, article id 8430119Conference paper (Refereed)
    Abstract [en]

    The 3rd-order Volterra kernels of a radio frequency (RF) power amplifier (PA) are characterized using a large-signal and a two-tone probing-signal. In this technique, the magnitude and phase asymmetries of the kernels of the PA excited by the probing-signal are analyzed in different amplitude regions of the large-signal. The device under test is a class-AB PA operating at 2.14 GHz. The maximum sweeping frequency space of the probing-signal is 20 MHz. The results indicate that the Volterra kernels of the PA show different behaviors (frequency dependency and asymmetry) in different regions.

  • 3.
    Bassi, Germán
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Skoglund, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Piantanida, Pablo
    Lossy Communication Subject to Statistical Parameter Privacy2018In: 2018 IEEE International Symposium on Information Theory (ISIT) - Proceedings, Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 1031-1035, article id 8437690Conference paper (Refereed)
    Abstract [en]

    We investigate the problem of sharing (communi-cating) the outcomes of a memoryless source when some of its statistical parameters must be kept private. Privacy is measured in terms of the Bayesian statistical risk according to a desired loss function while the quality of the reconstruction is measured by the average per-letter distortion. We first bound -uniformly over all possible estimators- the expected risk from below. This information-theoretic bound depends on the mutual information between the parameters and the disclosed (noisy) samples. We then present an achievable scheme that guarantees an upper bound on the average distortion while keeping the risk above a desired threshold, even when the length of the sample increases.

  • 4.
    Cao, Le Phuong
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Oechtering, Tobias J.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Skoglund, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Transmit Beamforming for Single-User Large-Scale MISO Systems With Sub-Connected Architecture and Power Constraints2018In: IEEE Communications Letters, ISSN 1089-7798, E-ISSN 1558-2558, Vol. 22, no 10, p. 2096-2099Article in journal (Refereed)
    Abstract [en]

    This letter considers optimal transmit beamforming for a sub-connected large-scale MISO system with RF chain and per-antenna power constraints. The system is configured such that each RF chain serves a group of antennas. For the hybrid scheme, necessary and sufficient conditions to design the optimal digital and analog precoders are provided. It is shown that, in the optimum, the optimal phase shift at each antenna has to match the channel coefficient and the phase of the digital precoder. In addition, an iterative algorithm is provided to find the optimal power allocation. We study the case where the power constraint on each RF chain is smaller than the sum of the corresponding per-antenna power constraints. Then, the optimal power is allocated based on two properties: each RF chain uses full power and if the optimal power allocation of the unconstraint problem violates a per-antenna power constraint then it is optimal to allocate the maximal power for that antenna.

  • 5.
    Cavarec, Baptiste
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. KTH Royal Inst Technol, Dept Informat Sci & Engn, Sch Elect Engn, Stockholm, Sweden..
    Bengtsson, Mats
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. KTH Royal Inst Technol, Dept Informat Sci & Engn, Sch Elect Engn, Stockholm, Sweden..
    CHANNEL DEPENDENT CODEBOOK DESIGN IN SPATIAL MODULATION2018In: 2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), IEEE, 2018, p. 6413-6417Conference paper (Refereed)
    Abstract [en]

    In this paper, we present a modulation design based on Spatial Modulation for the uplink in IoT applications. The proposed modulation design uses a Tabu search based deterministic heuristic to adapt the modulation link based on channel information fed back by the receiver. Our approach allows adaptivity to rate and energy constraints. We numerically validate the proposed method on a scenario with full channel state information available at the transceiver, showing clear performance gains compared to simpler heuristics and channel independent codebook designs.

  • 6.
    Celebi, Hasan Basri
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Pitarokoilis, Antonios
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Skoglund, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Training-assisted channel estimation for low-complexity squared-envelope receivers2018In: 2018 IEEE 19TH INTERNATIONAL WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS COMMUNICATIONS (SPAWC), IEEE , 2018, p. 196-200Conference paper (Refereed)
    Abstract [en]

    Squared-envelope receivers, also known as energy detectors, are, due to their simplified circuitry, low-cost and low-complexity receivers. Hence they are attractive implementation structures for future Internet-of-Things (IoT) applications. Even though there is considerable work on the wider research area of squared-envelope receivers, a comprehensive comparison and statistical characterization of training-assisted channel estimators for squared-envelope receivers appear to be absent from the literature. A detailed description of practical channel estimation schemes is necessary for the optimal training design of latency-constrained IoT applications. In this paper, various channel estimators are derived, their bias and variance are studied, and their performance is numerically compared against the Cramer-Rao lower bound.

  • 7.
    Champati, Jaya
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Al-Zubaidy, Hussein
    Gross, James
    KTH, School of Electrical Engineering (EES), Information Science and Engineering.
    Statistical Guarantee Optimization for Age of Information for the D/G/1 Queue2018Conference paper (Refereed)
    Abstract [en]

    Age of Information (AoI) has proven to be a useful metric in networked systems where timely information updates are of importance. Recently, minimizing the “average age” has received considerable attention. However, various applications pose stricter age requirements on the updates which demand knowledge of the AoI distribution. In this work, we study the distribution of the AoI and devise a problem of minimizing the tail of the AoI distribution function with respect to the frequency of generating information updates, i.e., the sampling rate of monitoring a process, for the D/G/1 queue model under FCFS queuing discipline. We argue that computing an exact expression for the AoI distribution may not always be feasible. Therefore, we opt for computing a bound on the tail of the AoI distribution and use it to formulate a tractable α-relaxed Upper Bound Minimization Problem (α-UBMP), where α > 1 is an approximation factor. This approximation can be used to obtain “good” heuristic solutions. We demonstrate the efficacy of our approach by solving α-UBMP for the D/M/1 queue. We show, using simulation, that the rate solutions obtained are near optimal for minimizing the tail of the AoI distribution.

  • 8.
    Ciftci, Baris
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Gross, James
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Norrga, Staffan
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Kildehöj, Lars
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Nee, Hans-Peter
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    A Proposal for Wireless Control of Submodules in Modular Multilevel Converters2018Conference paper (Refereed)
    Abstract [en]

    The modular multilevel converter is one of the most preferred converters for high-power conversion applications. Wireless control of the submodules can contribute to its evolution by lowering the material and labor costs of cabling and by increasing the availability of the converter. However, wireless control leads to many challenges for the control and modulation of the converter as well as for proper low-latency high-reliability communication. This paper investigates the tolerable asynchronism between phase-shifted carriers used in modulation from a wireless control point of view and proposes a control method along with communication protocol for wireless control. The functionality of the proposed method is validated by computer simulations in steady state.

  • 9.
    del Aguila Pla, Pol
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Jaldén, Joakim
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Cell detection by functional inverse diffusion and non-negative group sparsity – Part I: Modeling and Inverse Problems2018In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 66, no 20, p. 5407-5421Article in journal (Refereed)
    Abstract [en]

    In this two-part paper, we present a novel framework and methodology to analyze data from certain image-based biochemical assays, e.g., ELISPOT and Fluorospot assays. In this first part, we start by presenting a physical partial differential equations (PDE) model up to image acquisition for these biochemical assays. Then, we use the PDEs' Green function to derive a novel parametrization of the acquired images. This parametrization allows us to propose a functional optimization problem to address inverse diffusion. In particular, we propose a non-negative group-sparsity regularized optimization problem with the goal of localizing and characterizing the biological cells involved in the said assays. We continue by proposing a suitable discretization scheme that enables both the generation of synthetic data and implementable algorithms to address inverse diffusion. We end Part I by providing a preliminary comparison between the results of our methodology and an expert human labeler on real data. Part II is devoted to providing an accelerated proximal gradient algorithm to solve the proposed problem and to the empirical validation of our methodology.

  • 10.
    del Aguila Pla, Pol
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Jaldén, Joakim
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Cell detection by functional inverse diffusion and non-negative group sparsity – Part II: Proximal optimization and Performance evaluation2018In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 66, no 20, p. 5422-5437Article in journal (Refereed)
    Abstract [en]

    In this two-part paper, we present a novel framework and methodology to analyze data from certain image-based biochemical assays, e.g., ELISPOT and Fluorospot assays. In this second part, we focus on our algorithmic contributions. We provide an algorithm for functional inverse diffusion that solves the variational problem we posed in Part I. As part of the derivation of this algorithm, we present the proximal operator for the non-negative group-sparsity regularizer, which is a novel result that is of interest in itself, also in comparison to previous results on the proximal operator of a sum of functions. We then present a discretized approximated implementation of our algorithm and evaluate it both in terms of operational cell-detection metrics and in terms of distributional optimal-transport metrics.

  • 11.
    del Aguila Pla, Pol
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Jaldén, Joakim
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Cell detection on image-based immunoassays2018In: 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), IEEE, 2018, p. 431-435Conference paper (Refereed)
    Abstract [en]

    Cell detection and counting in the image-based ELISPOT and Fluorospot immunoassays is considered a bottleneck.The task has remained hard to automatize, and biomedical researchers often have to rely on results that are not accurate.Previously proposed solutions are heuristic, and data-based solutions are subject to a lack of objective ground truth data. In this paper, we analyze a partial differential equations model for ELISPOT, Fluorospot, and assays of similar design. This leads us to a mathematical observation model forthe images generated by these assays. We use this model to motivate a methodology for cell detection. Finally, we provide a real-data example that suggests that this cell detection methodology and a human expert perform comparably.

  • 12.
    del Aguila Pla, Pol
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Jaldén, Joakim
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Convolutional group-sparse coding and source localization2018Conference paper (Refereed)
    Abstract [en]

    In this paper, we present a new interpretation of non-negatively constrained convolutional coding problems as blind deconvolution problems with spatially variant point spread function. In this light, we propose an optimization framework that generalizes our previous work on non-negative group sparsity for convolutional models. We then link these concepts to source localization problems that arise in scientific imaging, and provide a visual example on an image derived from data captured by the Hubble telescope.

  • 13.
    Du, Rong
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Gkatzikis, Lazaros
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Xiao, Ming
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    On Maximizing Sensor Network Lifetime by Energy Balancing2018In: IEEE Transactions on Control of Network Systems, ISSN 2325-5870, Vol. 5, no 3Article in journal (Refereed)
    Abstract [en]

    Many physical systems, such as water/electricity distribution networks, are monitored by battery-powered wireless-sensor networks (WSNs). Since battery replacement of sensor nodes is generally difficult, long-term monitoring can be only achieved if the operation of the WSN nodes contributes to long WSN lifetime. Two prominent techniques to long WSN lifetime are 1) optimal sensor activation and 2) efficient data gathering and forwarding based on compressive sensing. These techniques are feasible only if the activated sensor nodes establish a connected communication network (connectivity constraint), and satisfy a compressive sensing decoding constraint (cardinality constraint). These two constraints make the problem of maximizing network lifetime via sensor node activation and compressive sensing NP-hard. To overcome this difficulty, an alternative approach that iteratively solves energy balancing problems is proposed. However, understanding whether maximizing network lifetime and energy balancing problems are aligned objectives is a fundamental open issue. The analysis reveals that the two optimization problems give different solutions, but the difference between the lifetime achieved by the energy balancing approach and the maximum lifetime is small when the initial energy at sensor nodes is significantly larger than the energy consumed for a single transmission. The lifetime achieved by energy balancing is asymptotically optimal, and that the achievable network lifetime is at least 50% of the optimum. Analysis and numerical simulations quantify the efficiency of the proposed energy balancing approach.

  • 14.
    Du, Rong
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Xiao, Ming
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Optimal Node Deployment and Energy Provision for Wirelessly Powered Sensor Networks2018In: IEEE Journal on Selected Areas in Communications, ISSN 0733-8716, E-ISSN 1558-0008Article in journal (Refereed)
    Abstract [en]

    In a typical wirelessly powered sensor network (WPSN), wireless chargers provide energy to sensor nodes by using wireless energy transfer (WET). The chargers can greatly improve the lifetime of a WPSN using energy beamforming by a proper charging scheduling of energy beams. However, the supplied energy still may not meet the demand of the energy of the sensor nodes. This issue can be alleviated by deploying redundant sensor nodes, which not only increase the total harvested energy, but also decrease the energy consumption per node provided that an efficient  scheduling of the sleep/awake of the nodes is performed. Such a problem of joint optimal sensor deployment, WET scheduling, and node activation is posed and investigated in this paper. The problem is an integer optimization that is challenging due to the binary decision variables and non-linear constraints. Based on the analysis of the necessary condition such that the WPSN be immortal, we decouple the original problem into a node deployment problem and a charging and activation scheduling problem. Then, we propose an algorithm and prove that it achieves the optimal solution under a mild condition. The simulation results show that the proposed algorithm reduces the needed nodes to deploy by approximately 16%, compared to a random-based approach. The simulation also shows if the battery buffers are large enough, the optimality condition will be easy to meet.

  • 15.
    Gao, Yulan
    et al.
    Univ Elect Sci & Technol China, Natl Key Lab Sci & Technol Commun, Chengdu 611731, Sichuan, Peoples R China..
    Xiao, Yue
    Univ Elect Sci & Technol China, Natl Key Lab Sci & Technol Commun, Chengdu 611731, Sichuan, Peoples R China..
    Wu, Mingming
    Univ Elect Sci & Technol China, Natl Key Lab Sci & Technol Commun, Chengdu 611731, Sichuan, Peoples R China..
    Xiao, Ming
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Shao, Jinliang
    Univ Elect Sci & Technol China, Sch Math Sci, Chengdu 611731, Sichuan, Peoples R China..
    Game Theory-Based Anti-Jamming Strategies for Frequency Hopping Wireless Communications2018In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 17, no 8, p. 5314-5326Article in journal (Refereed)
    Abstract [en]

    In frequency hopping (FH) wireless communications, finding an effective transmission strategy to properly mitigate jamming has been recently considered as a critical issue, due to the inherent broadcast nature of wireless communications. Recently, game theory has been proposed as a powerful tool for dealing with the jamming problem, which can be considered as a player (jammer) playing against a user (transmitter). Different from existing results, in this paper, a bimatrix game framework is developed for modeling the interaction process between the transmitter and the jammer, and the sufficient and necessary conditions for Nash equilibrium (NE) strategy of the game are obtained under the linear constraints. Furthermore, the relationship between the NE solution and the global optimal solution of the corresponding quadratic programming is presented. In addition, a special analysis case is developed based on the continuous game framework in which each player has a continuum of strategies. Finally, we show that the performance can be improved based on our game theoretic framework, which is verified by numerical investigations.

  • 16.
    Ghauch, Hadi
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Kim, Taejoon
    KTH, School of Electrical Engineering and Computer Science (EECS). City University of Hong Kong.
    Skoglund, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Low-Overhead Coordination in Sub-28 Millimeter-Wave Networks2018Conference paper (Refereed)
  • 17.
    Ghauch, Hadi
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Mahboob Ur Rahman, Muhammad
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Imtiaz, Sahar
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Qvarfordt, Christer
    Huawei.
    Skoglund, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Gross, James
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    User Assignment in C-RAN Systems: Algorithms and BoundsIn: Article in journal (Refereed)
  • 18. Ghayem, Fateme
    et al.
    Sadeghi, Mostafa
    Babaie-Zadeh, Massoud
    Chatterjee, Saikat
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Skoglund, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Jutten, Christian
    Sparse Signal Recovery Using Iterative Proximal Projection2018In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 66, no 4, p. 879-894Article in journal (Refereed)
    Abstract [en]

    This paper is concerned with designing efficient algorithms for recovering sparse signals from noisy underdetermined measurements. More precisely, we consider minimization of a nonsmooth and nonconvex sparsity promoting function subject to an error constraint. To solve this problem, we use an alternating minimization penalty method, which ends up with an iterative proximal-projection approach. Furthermore, inspired by accelerated gradient schemes for solving convex problems, we equip the obtained algorithm with a so-called extrapolation step to boost its performance. Additionally, we prove its convergence to a critical point. Our extensive simulations on synthetic as well as real data verify that the proposed algorithm considerably outperforms some well-known and recently proposed algorithms.

  • 19.
    Ghourchian, Hamid
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. Sharif Univ Technol, Dept Elect Engn, Tehran 11155, Iran..
    Aminian, Gholamali
    Sharif Univ Technol, Dept Elect Engn, Tehran 11155, Iran.;Sharif Univ Technol, Adv Commun Res Inst, Tehran 11155, Iran..
    Gohari, Amin
    Sharif Univ Technol, Dept Elect Engn, Tehran 11155, Iran.;Sharif Univ Technol, Adv Commun Res Inst, Tehran 11155, Iran..
    Mirmohseni, Mahtab
    Sharif Univ Technol, Dept Elect Engn, Tehran 11155, Iran.;Sharif Univ Technol, Adv Commun Res Inst, Tehran 11155, Iran..
    Nasiri-Kenari, Masoumeh
    Sharif Univ Technol, Dept Elect Engn, Tehran 11155, Iran.;Sharif Univ Technol, Adv Commun Res Inst, Tehran 11155, Iran..
    On the Capacity of a Class of Signal-Dependent Noise Channels2018In: IEEE Transactions on Information Theory, ISSN 0018-9448, E-ISSN 1557-9654, Vol. 64, no 12, p. 7828-7846Article in journal (Refereed)
    Abstract [en]

    In some applications, the variance of additive measurement noise depends on the signal that we aim to measure. For instance, additive signal-dependent Gaussian noise (ASDGN) channel models are used in molecular and optical communication. Herein, we provide lower and upper bounds on the capacity of additive signal-dependent noise (ASDN) channels. The first lower bound is based on an extension of majorization inequalities, and the second lower bound utilizes the properties of the differential entropy. The lower bounds are valid for arbitrary ASDN channels. The upper bound is based on a previous idea of the authors ("symmetric relative entropy") and is applied to the ASDGN channels. These bounds indicate that in the ASDN channels (unlike the classical additive white Gaussian noise channels), the capacity does not necessarily become larger by reducing the noise variance function. We also provide sufficient conditions under which the capacity becomes infinite. This is complemented by some conditions implying that the capacity is finite, and a unique capacity achieving measure exists (in the sense of the output measure).

  • 20.
    Hamadeh, Anas
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Anomaly Detection in A Multivariate DataStream in a Highly Scalable and Fault Tolerant Architecture2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The process of monitoring telecommunication systems performance by investigatingKey Performance Indicators (KPI) and Performance Measurements(PMs) is crucial for valuable sustainable solutions and requires analysts' interventionwith profound knowledge to help mitigate vulnerabilities and risks.This work focuses on PMs anomaly detection in order to automate the processof discovering unacceptable Radio Access Network (RAN) performance byleveraging K-meansjj algorithm and producing an anomaly scoring mechanism.It also oers a streaming, fault tolerant, scalable and loosely coupled architectureto process data on the y based on a normal behavior model. Theproposed architecture is used to test the anomaly scoring system where variousdata patterns are ingested. The tests focused on inspecting the anomaly score'sconsistency, variability and sensitivity. The results were highly impacted by thereal-time standardization process of data, and the scores were not entirely sensitiveto changes in constant features; however, the experiment yielded acceptableresults when the correlation between features was taken into account.

  • 21.
    Huang, Victor K. L.
    et al.
    Sage Technol Resources, Richmond, VA USA.;Sage Technol Resources, IT Automot Sect Elect Vehicles, Richmond, VA USA.;Six Silicon Valley, Richmond, VA USA.;IES, Richmond, VA USA.;IES Stand Tech Comm, Richmond, VA USA.;IES IEEE Stand Assoc, Richmond, VA USA.;IEEE Commun Soc, Richmond, VA USA.;IEEE Tech Engn Management Soc, Richmond, VA USA..
    Pang, Zhibo
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. ABB Corp Res, Wireless Commun, Västerås, Sweden;Tsinghua Univ, Beijing, Peoples R China.;Univ Sydney, Sydney, NSW, Australia.;Zhejiang Univ, Hangzhou, Zhejiang, Peoples R China.;Beijing Univ Posts & Telecommun, Beijing, Peoples R China..
    Chen, Cheng-Jen (Allen)
    IES Stand Tech Comm, Richmond, VA USA..
    Tsang, Kim Fung
    City Univ Hong Kong, Dept Elect Engn, Hong Kong, Hong Kong, Peoples R China.;Internet Things Comm, Smart City Consortium, Hong Kong, Hong Kong, Peoples R China..
    New Trends in the Practical Deployment of Industrial Wireless2018In: IEEE Industrial Electronics Magazine, ISSN 1932-4529, E-ISSN 1941-0115, Vol. 12, no 2, p. 50-58Article in journal (Refereed)
  • 22.
    Händel, Peter
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Ronnow, Daniel
    Univ Gavle, Dept Elect Math & Nat Sci, S-80176 Gavle, Sweden..
    Dirty MIMO Transmitters: Does It Matter?2018In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 17, no 8, p. 5425-5436Article in journal (Refereed)
    Abstract [en]

    The radio frequency transmitter is a key component in contemporary multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing systems. A detailed study of a 2 x 2 MIMO transmitter subjected to correlated input data streams, nonlinear distortion, thermal noise, and crosstalk is provided by stochastic modeling. The effects of correlated input streams, crosstalk, and nonlinearities are studied in detail and exemplified both by approximate expressions and numerical simulations. Key results include exact and approximate expressions for the normalized mean-squared error (NMSE) for systems with or without digital predistortion; the relationship between NMSE and the signal-to-noise-and-distortion ratio, the properties of the distortion noise, and a novel design for power amplifier back-off for MIMO transmitters subject to crosstalk. The theoretical derivations are illustrated by numerical examples and simulation results, and their relationships to the state-of-the-art research are discussed.

  • 23.
    Imtiaz, Sahar
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Ghauch, Hadi
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Koudouridis, George
    Gross, James
    KTH, School of Electrical Engineering (EES), Information Science and Engineering.
    Random Forests Resource Allocation for 5G Systems: Performance and Robustness Study2018Conference paper (Refereed)
  • 24.
    Imtiaz, Sahar
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Koudouridis, Georgios P.
    Ghauch, Hadi
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Gross, James
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Random forests for resource allocation in 5G cloud radio access networks based on position information2018In: EURASIP Journal on Wireless Communications and Networking, ISSN 1687-1472, E-ISSN 1687-1499, Vol. 2018, no 1, article id 142Article in journal (Refereed)
    Abstract [en]

    Next generation 5G cellular networks are envisioned to accommodate an unprecedented massive amount of Internet of things (IoT) and user devices while providing high aggregate multi-user sum rates and low latencies. To this end, cloud radio access networks (CRAN), which operate at short radio frames and coordinate dense sets of spatially distributed radio heads, have been proposed. However, coordination of spatially and temporally denser resources for larger sets of user population implies considerable resource allocation complexity and significant system signalling overhead when associated with channel state information (CSI)-based resource allocation (RA) schemes. In this paper, we propose a novel solution that utilizes random forests as supervised machine learning approach to determine the resource allocation in multi-antenna CRAN systems based primarily on the position information of user terminals. Our simulation studies show that the proposed learning based RA scheme performs comparably to a CSI-based scheme in terms of spectral efficiency and is a promising approach to master the complexity in future cellular networks. When taking the system overhead into account, the proposed learning-based RA scheme, which utilizes position information, outperforms legacy CSI-based scheme by up to 100%. The most important factor influencing the performance of the proposed learning-based RA scheme is antenna orientation randomness and position inaccuracies. While the proposed random forests scheme is robust against position inaccuracies and changes in the propagation scenario, we complement our scheme with three approaches that restore most of the original performance when facing random antenna orientations of the user terminal.

  • 25.
    Jaldén, Joakim
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. KTH Royal Inst Technol, Dept Informat Sci & Engn, Stockholm, Sweden..
    Moreno, Xavier Casas
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. KTH Royal Inst Technol, Dept Informat Sci & Engn, Stockholm, Sweden..
    Skog, Isaac
    Linkoping Univ, Dept Elect Engn, Linkoping, Sweden..
    USING THE ARDUINO DUE FOR TEACHING DIGITAL SIGNAL PROCESSING2018In: 2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), IEEE, 2018, p. 6468-6472Conference paper (Refereed)
    Abstract [en]

    This paper describes an Arduino Due based platform for digital signal processing (DSP) education. The platform consists of an in-house developed shield for robust interfacing with analog audio signals and user inputs, and an off-the-shelf Arduino Due that executes the students' DSP code. This combination enables direct use of the Arduino integrated development environment (IDE), with its low barrier to entry for students, its low maintenance need and cross platform interoperability, and its large user base. Relevant hardware and software features of the platform are discussed throughout, as are design choices made in relation to learning objectives, and the planned use of the platform in our own DSP course.

  • 26. Jia, D.
    et al.
    Fei, Z.
    Xiao, Ming
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Cao, C.
    Kuang, J.
    Enhanced frameless slotted ALOHA protocol with Markov chains analysis2018In: Science China Information Sciences, ISSN 1674-733X, E-ISSN 1869-1919, Vol. 61, no 10, article id 102304Article in journal (Refereed)
    Abstract [en]

    In this paper, we propose a novel approach to enhance the performance of frameless slotted ALOHA (SA) protocol. We employ signature codes to help the receiver identify the packets contained in collisions, and use successive interference cancellation (SIC) for packet recovery. We model the proposed scheme as a two-state Markov model represented by a uni-partite graph. We evaluate the throughput, expected delay and average memory size of the proposed scheme, and optimize the proposed scheme to maximize the throughput. We show that the theoretical analysis matches well with simulation results. The throughput and expected delay of the proposed protocol outperform the conventional slotted ALOHA protocol significantly. 

  • 27.
    Jiang, Xiaolin
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Pang, Zhibo
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Zhan, Ming
    KTH.
    Dzung, Dacfey
    Luvisotto, Michele
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Packet Detection by Single OFDM Symbol in URLLC for Critical Industrial Control: a Realistic Study2018In: IEEE Journal on Selected Areas in Communications, ISSN 0733-8716, E-ISSN 1558-0008Article in journal (Other academic)
  • 28.
    Khan, Zain Ahmed
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. University of Gävle.
    Characterization and Compensation of Hardware Impairments in Transmitters for Wireless Communications2018Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Increasing demands for data rate, energy efficiency and reliability in wireless communications have resulted in the introduction of radio frequency (RF) multiple input multiple output (MIMO) transmitters. However, MIMO transmitters suffer from additional crosstalk impairments along with the power amplifier (PA) and I/Q imbalance distortions observed in single input single output (SISO) transmitters. Therefore, this thesis focuses on the characterization and compensation of these hardware impairments in RF SISO and MIMO transmitters.

    PA distortions are often compensated using the Volterra series, but it suffers from high computational complexity. Therefore, a non-parametric method based on density estimation has been proposed in this thesis to estimate the PA transfer function, from which pruned Volterra models can be developed. The method is validated for a Doherty PA and achieves competitive error performance at a lower complexity than its competitors.

    For MIMO transmitters, a characterization technique that uses multitone excitation signals has been proposed. Multitone signals yield non-overlapping tones at the outputs of the MIMO Volterra kernels. These kernel outputs are used to identify the dominant crosstalk impairments, from which block structure and base-band behavioral models are developed. The method is validated for 2x2 and 3x3 MIMO transmitters and it is shown that the derived models achieve a better complexity accuracy trade-off than the other pruned MIMO Volterra models considered in this thesis.

    Finally, the thesis presents compensation models for joint static I/Q imbalance and MIMO PA distortions based on conjugate pair and real-valued basis functions. The models are augmented with sub-sample resolution to compensate for dynamic I/Q imbalance distortions. The proposed models are validated for a 2x2 RF MIMO transmitter and achieve a better complexity accuracy trade-off than the other state-of-the-art models considered in this thesis.

  • 29.
    Khan, Zain Ahmed
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Zenteno, Efrain
    Universidad Católica San Pablo.
    Händel, Peter
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Isaksson, Magnus
    University of Gävle.
    Extraction of the Third-Order 3x3 MIMO VolterraKernel Outputs Using Multitone Signals2018In: IEEE transactions on microwave theory and techniques, ISSN 0018-9480, E-ISSN 1557-9670, Vol. 66, no 11, p. 4985-4999Article in journal (Refereed)
    Abstract [en]

    This paper uses multitone signals to simplify theanalysis of 3×3 multiple-input multiple-output (MIMO) Volterrasystems by isolating the third-order kernel outputs from eachother. Multitone signals fed to an MIMO Volterra system yielda spectrum that is a permutation of the sums of the inputsignal tones. This a priori knowledge is used to design multitonesignals such that the third-order kernel outputs are isolated inthe frequency domain. The signals are designed by deriving theconditions for the offset and spacing of the input frequency grids.The proposed technique is then validated for the six possibleconfigurations of a 3x3 RF MIMO transmitter impaired bycrosstalk effects. The proposed multitone signal design is usedto extract the third-order kernel outputs, and their relativecontributions are analyzed to determine the dominant crosstalkeffects for each configuration.

  • 30.
    Khan, Zain Ahmed
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. Högskolan i Gävle.
    Zenteno, Efrain
    Universidad Católica San Pablo.
    Händel, Peter
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. KTH, Superseded Departments (pre-2005), Signals, Sensors and Systems.
    Isaksson, Magnus
    Högskolan i Gävle.
    Identification of Third Order 3x3 MIMO Volterra Kernels using Multitone Excitation SignalsManuscript (preprint) (Other academic)
  • 31.
    Larsson, Peter
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    On Performance Analysis of Retransmission Schemes with Fading Channels2018Doctoral thesis, monograph (Other academic)
    Abstract [en]

    Future wireless communication systems and services bring increased performance demands, with respect to data-rate(s), reliable communication, (stochastic) real-time guarantees, and more. In this context, not only new communication schemes are needed, but also more capable performance analysis methods are essential. Digital wireless communication systems convey information (digital messages, as data packets) inherently susceptible to errors when communicated. In this respect, fading channels, receiver noise, and interference, are often the main causes of errors. State-of-the-art wireless systems use, e.g., retransmissions (and channel coding) to correct possible remaining errors in communicated message. Retransmissions of erroneous messages are generally known, under the umbrella-term, as automatic repeat request. Adopting a modern terminology (see Chapter 2.2), the three main schemes are here denoted; automatic repeat request (ARQ), repetition redundancy hybrid-ARQ (RR-HARQ), and incremental redundancy hybrid-ARQ (IR-HARQ). There are at least three factors that motivate further performance studies of the ARQ-, RR-, and IR-schemes. First, many commercially important and extensively deployed wireless systems, e.g. cellular systems, use those (H)ARQ-schemes as core system components. Second, those schemes are often integrated with various (recently invented) communication schemes, such as multiple-antenna systems, which promote the need of further studies. Third, the information theoretically-based performance characterization of those (H)ARQ-schemes is, in our view, only in its infancy, and only a few closed-form expressions for very basic (H)ARQ-cases exists in the literature. The thesis deals, on a high level, with the problem of developing performance analysis methods for (H)ARQ-schemes, and, on a more detailed level, studying particularly important (H)ARQ-cases, i.e. with respect to (wrt) (H)ARQ-scheme, fading statistics, antenna-scheme, etc. In doing so, the thesis addresses tools and models that support, ease, or strengthen the analysis.

    We start our study with a basic throughput analysis of (H)ARQ (Chapter 4). A general throughput expression for HARQ is given in terms of the Laplace-transform (LT) for the probability density function (pdf) of a so called effective-channel. Here, the effective-channel represents the signal-to-noise-ratio (SNR), or mutual information (MI), after signal processing. We then focus on some important (H)ARQ-cases and give closed-form throughput expressions in a general diversity (GD) channel, accounting for space-time-block coding (STC), maximal ratio combining (MRC), and Nakagami-m fading. The throughput of (H)ARQ can, in many cases, be maximized by tuning the initial transmission rate. However, analytical throughput optimization has proven challenging to solve even for the simplest (H)ARQ-cases. We propose a parametric optimization approach, based on judiciously chosen parameter, that allows expressions for the optimal throughput, and the optimal rate point, to be given in closed-forms (Chapter 5). The method is demonstrated for several important, but previously not handled, (H)ARQ-cases. An inherent assumption in this thesis, shared with many other works in wireless communication analysis, is the assumption of that the average symbol MI equals the additive white Gaussian noise (AWGN) channel capacity. The underlying assumption is that the communication symbol can be modeled as an independent and identically distributed (iid) complex Gaussian random variable (r.v). However, practical systems use discrete modulation, not a continuous r.v. Quadrature amplitude modulation (QAM) is the most common (discrete) modulation format in communication systems. Unfortunately, QAM exhibits an asymptotic 1.53 dB SNR-gap relative to the AWGN channel capacity. We substantiate the assumption, of modeling the communication signal as iid complex Gaussian, and close the SNR-shaping-gap, by proposing a novel modulation framework inspired from packing arrangements (spiral-phyllotaxis) among plants (Chapter 6). Much work on wireless performance analysis focus on specialized fading channel gain models, such as exponentially- or gamma-distributed fading. We introduce the idea of a matrix exponential (ME) distributed effective channel SNR (Chapter 7). The ME-distribution is dense on the positive axis, and includes the exponential- and gamma-distribution as special cases. With the ME-distributed channel at hand, we develop an overall ME-distribution-based framework that simplifies the performance analysis and directly express performance measures in the ME-distributed (effective) channel parameters. It has proven hard to analyze (H)ARQ with interference via standard methods, and only special cases have previously been handled successfully. With the ME-distribution-based performance analysis framework, we can now analyze interferers with ME-distributed SNRs. Numerous closed-form throughput expressions are also given in terms of ME-distribution-based channels. Up to this point, the performance measure of choice has been throughput. However, communication systems may impose delay requirements. For this purpose, the effective capacity, giving an indication of communication rate for a given maximum delay and delay violation probability, is a more suitable performance measure. We formulate a very general retransmission system model (allowing for multiple transmissions, multiple communication modes, and multiple rate increments), going beyond classical ARQ-, RR-, and IR-models, and develop a powerful recurrence-based effective capacity performance analysis framework (Chapter 8).

    Thus, to summarize on a high-level, we introduce a simplifying LT-based performance analysis framework, develop a powerful auxiliary-parameterized throughput optimization method, propose a novel AWGN channel capacity approaching (golden angle) modulation scheme, introduce the ME-distributed channel, develop the ME-distribution-based performance analysis framework, design a highly general retransmission system model, and propose a recurrence-based (effective capacity) performance analysis framework. Throughout the thesis, numerous new closed-form performance expressions are given built on the tools and models introduced in the preceding chapters.

  • 32.
    Li, Nan
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Smart Cooperation with Network Coding in Hierarchical Wireless Networks2018Doctoral thesis, monograph (Other academic)
    Abstract [en]

    To achieve more dynamic, efficient and intelligent use of the scarce wireless spectrum resource, the concept of cooperation has been formalized into several hierarchical network models in future mobile networks. Cooperative communications, such as relaying, can potentially increase communication efficiency and spectrum utilization due to the broadcast nature of wireless networks, and may lead to a better support for diverse communication modes with flexible spectrum sharing. In this thesis, we investigate the cooperation between users with different priorities in hierarchical wireless networks. Especially, by coinciding the idea of relaying and network coding, we explore cooperation schemes from several aspects.

    First we discuss orthogonal time-frequency access for cooperation between primary and secondary users in a cognitive radio network, where two binary network coding schemes are developed. We analyze the transmission process and propose a novel methodology for performance evaluation. Second we propose a selective cooperation mechanism for intelligent resource sharing. By evaluating the system throughput with the approxiamtion method, we further discuss the spectrum sharing strategy by formulating an optimization problem to maximize the secondary system throughput. Besides, we extend our model to larger cognitive radio networks with multiple primary/secondary users. Finally we investigate non-orthogonal multiple access combined with orthogonal multiple access with hierarchical users. We define and study two cooperation schemes, where we derive the achievable rate regions with diverse communication modes supported. We formulate a problem jointly optimizing the strategy on time sharing and transmit power allocation at transmitters.

    Throughout the thesis we progressively reveal the importance of smart cooperation in hierarchical wireless networks, through rendering our models more realistic with smart strategies.

  • 33.
    Li, Nan
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Rasmussen, Lars Kildehöj
    Xiao, Ming
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Performance Analysis of Cognitive User Cooperation Using Binary Network Coding2018In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 67, no 8, p. 7355-7369Article in journal (Refereed)
    Abstract [en]

    We consider a cognitive radio network where a primary and a secondary transmitter, respectively, communicate a message to their primary and secondary receivers over a packet-based wireless link, using a joint automatic-repeat-request (ARQ) error control scheme. The secondary transmitter assists in the retransmission of the primary message, which improves the primary performance, and as a reward it is granted limited access to the transmission resources. Conventional ARQ, as well as two network-coding schemes are investigated for applications in the retransmission phase; namely the static network-coding scheme and the adaptive network-coding scheme. For each scheme we analyze the transmission process by investigating the distribution of the number of transmission attempts. We divide every frame into three transmission sessions and in each session we discover that the number of transmission attempts follows a certain negative binomial distribution, in which case can be further approximated by a normal distribution. Considering both the cases of an adaptive frame size and a truncated frame size, we derive analytical results on system performances and discuss the comparison of three schemes. Besides, the approximation method greatly reduces the complexity of transmission analysis, especially in the truncated frame-size case. Numerical results show that our analysis are valid and closely match the simulations.

  • 34.
    Li, Nan
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Xiao, Ming
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Rasmussen, Lars Kildehöj
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Optimized Cooperative Multiple Access in Industrial Cognitive Networks2018In: IEEE Transactions on Industrial Informatics, ISSN 1551-3203, E-ISSN 1941-0050, Vol. 14, no 6, p. 2666-2676Article in journal (Refereed)
    Abstract [en]

    We consider optimized cooperation in joint orthogonal multiple access and nonorthogonal multiple access in industrial cognitive networks, in which lots of devices may have to share spectrum and some devices (e.g., those for critical control devices) have higher transmission priority, known as primary users. We consider one secondary transmitter (less important devices) as a potential relay between a primary transmitter and receiver pair. The choice of cooperation scheme differs in terms of use cases. With decode-and-forward relaying, the channel between the primary and secondary users limits the achievable rates especially when it experiences poor channel conditions. To alleviate this problem, we apply analog network coding to directly combine the received primary message for relaying with the secondary message. We find achievable rate regions for these two schemes over Rayleigh fading channels. We then investigate an optimization problem jointly considering orthogonalmultiple access and nonorthogonal multiple access, where the secondary rate is maximized under the constraint of maintaining the primary rate. We find both analytical solutions as well as solutions based on experiments through the time sharing strategy between the primary and secondary system and the transmit power allocation strategy at the secondary transmitter. We show the performance improvements of exploiting analog network coding and the impacts of cooperative schemes and user geometry on achievable rates and resource sharing strategies.

  • 35.
    Liang, Xinyue
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. KTH Royal Inst Technol, Sch Elect Engn, Dept Informat Sci & Engn, Stockholm, Sweden..
    Javid, Alireza M.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. KTH Royal Inst Technol, Sch Elect Engn, Dept Informat Sci & Engn, Stockholm, Sweden..
    Skoglund, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. KTH Royal Inst Technol, Sch Elect Engn, Dept Informat Sci & Engn, Stockholm, Sweden..
    Chatterjee, Saikat
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH Royal Inst Technol, Sch Elect Engn, Dept Informat Sci & Engn, Stockholm, Sweden..
    DISTRIBUTED LARGE NEURAL NETWORK WITH CENTRALIZED EQUIVALENCE2018In: 2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), IEEE, 2018, p. 2976-2980Conference paper (Refereed)
    Abstract [en]

    In this article, we develop a distributed algorithm for learning a large neural network that is deep and wide. We consider a scenario where the training dataset is not available in a single processing node, but distributed among several nodes. We show that a recently proposed large neural network architecture called progressive learning network (PLN) can be trained in a distributed setup with centralized equivalence. That means we would get the same result if the data be available in a single node. Using a distributed convex optimization method called alternating-direction-method-of-multipliers (ADMM), we perform training of PLN in the distributed setup.

  • 36.
    Liu, Chengpeng
    et al.
    UESTC, NCL, Chengdu, Sichuan, Peoples R China..
    Zhang, Lin
    UESTC, NCL, Chengdu, Sichuan, Peoples R China..
    Xiao, Ming
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Chen, Zhi
    UESTC, NCL, Chengdu, Sichuan, Peoples R China..
    Li, Shaoqian
    UESTC, NCL, Chengdu, Sichuan, Peoples R China..
    Secrecy Performance Analysis in Downlink NOMA Systems with Cooperative Full-duplex Relaying2018In: 2018 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS WORKSHOPS (ICC WORKSHOPS), IEEE, 2018Conference paper (Refereed)
    Abstract [en]

    We introduce the cooperative full-duplex relaying to a downlink non-orthogonal multiple access (NOMA) system and analyze the secrecy performance of each NOMA user. In particular, we enable the near NOMA user, which is close to a base station (BS), to act as a full-duplex relay for the far NOMA user, which is far away from the BS. By taking imperfect self-interference cancellation into consideration, we analytically derive the secrecy outage probabilities of both NOMA users with integral expressions. To reduce the computational complexity of both secrecy outage probabilities, we adopt approximation techniques and obtain approximated secrecy outage probabilities with closed-form expressions. Simulation results validate the correctness of our analysis and reveal that suppressing the self-interference at the full-duplex relay can enhance the secrecy performance of NOMA users. Meanwhile, simulation results demonstrate the advantages of the cooperative full-duplex relaying in the NOMA system over the OMA system.

  • 37.
    Liu, Du
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Orthonormal Motion-Adaptive Transforms for Image Sequences2018Doctoral thesis, monograph (Other academic)
    Abstract [en]

    In this thesis, we propose and discuss a class of motion-adaptive transforms (MAT) to describe the temporal correlation in image sequences for compression. The temporal correlation is based on motion models, and undirected graphs are used to represent this correlation in image sequences. The transforms are adaptive to general motion fields. Hence, they avoid the predict-update mismatch of the classic block-motion lifting schemes in processing connected and disconnected pixels. Moreover, the proposed transforms are orthonormal for general motion field, and thus, they permit energy conservation and perfect reconstruction.

    As we represent the motion-connected signals by graphs, we introduce a graph-based covariance matrix model and use the associated eigenvector matrix for compression. As the proposed covariance model is closely related to the graph, the relation between the covariance matrix and theLaplacian matrix is studied and the associated eigenvector matrices are discussed. The class of MAT is constructed by using so-called scale factors.We show that the scale factors determine a relevant subspace of the signal representation.Hence, we propose a subspace-constrained transform, which achieves optimal energy compaction given the subspace constraint. On the other hand, the resulting basis vectors are signal dependent.

    To construct practical transforms without using covariance matrices, we consider two types of incremental transforms over graphs, namely the uni-directional orthogonal transform (Uni-OT) and the bidirectional orthogonal transform (Bi-OT). In addition, fractional-pel MAT is proposed to further extend the class of MAT. Our fractional-pel MAT can incorporate a general interpolation filter into the basis vectors, while offering perfect reconstruction, orthogonality, and improved coding efficiency.

  • 38.
    Luan, Dehan
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Fundamental Performance Limits on Time of Arrival Estimation Accuracy with 5G Radio Access2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    5G radio access technology stimulates new use cases and emerging businessmodels, evolving the world to become a fully mobile and connected networksociety, expected to be operational by 2020. To enable ultra-high reliable andhighly precise features, there are more stringent positioning accuracy requirementsfor location based services and E911 emergency calls, targeting at bothindoor and outdoor users which include humans, devices, vehicles and machines.In currently deployed Long Term Evolution (LTE) networks, Observed TimeDi↵erence of Arrival (OTDoA) positioning is acting as one of the User Equipment(UE) localization techniques. The positioning accuracy in OTDoA methoddepends on various factors, e.g. network deployment, signal propagation conditionand properties of Positioning Reference Signal (PRS). For a given deploymentand propagation scenario, significant improvements of positioning accuracyis achievable by appropriately redesigning the PRS with 5G radio access.In this thesis, fundamental performance limits (i.e. Cramer Rao Lower Bounds)on Time of Arrival (ToA) estimation are derived respectively considering frequencyselective channel with additive white noise, carrier frequency o↵set andWiener phase noise. Particularly, the e↵ects of flexible bandwidth, subcarrierspacing and power allocation on ToA estimation accuracy have been investigatedin di↵erent settings based on corresponding performance bounds. Furthermore,the performance limits on ToA estimation can be translated into UE positioningaccuracy for a given deployment scenario. Overall, the thesis has built valuableinsights on PRS design and waveform optimization for 5G based positioning.

  • 39. Ma, Zhanyu
    et al.
    Chien, Jen-Tzung
    Tan, Zheng-Hua
    Song, Yi-Zhe
    Taghia, Jalil
    Xiao, Ming
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Recent advances in machine learning for non-Gaussian data processing2018In: Neurocomputing, ISSN 0925-2312, E-ISSN 1872-8286, Vol. 278, p. 1-3Article in journal (Refereed)
  • 40.
    Maros, Marie
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Jaldén, Joakim
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    DYNAMIC POWER ALLOCATION FOR SMART GRIDS VIA ADMM2018In: 2018 IEEE 19TH INTERNATIONAL WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS COMMUNICATIONS (SPAWC), IEEE , 2018, p. 416-420Conference paper (Refereed)
    Abstract [en]

    Electric power distribution systems encounter fluctuations in supply due to renewable sources with high variability in generation capacity. It is therefore necessary to provide algorithms that are capable of dynamically finding approximate solutions. We propose two semi-distributed algorithms based on ADMM and discuss their advantages and disadvantages. One of the algorithms computes a feasible approximate of the optimal power allocation at each time instance. We require coordination between the nodes to guarantee feasibility of each of the iterates. We bound the distance from the approximate solutions to the optimal solution as a function of the variation in optimal power allocation, and we verify our results via experiments.

  • 41.
    Mochaourab, Rami
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. RISE Acreo, Res Inst Sweden, S-16425 Stockholm, Sweden.
    Oechtering, Tobias J.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Private Filtering for Hidden Markov Models2018In: IEEE Signal Processing Letters, ISSN 1070-9908, E-ISSN 1558-2361, Vol. 25, no 6, p. 888-892Article in journal (Refereed)
    Abstract [en]

    Consider a hidden Markov model describing a system with two types of states: a monitored state and a private state. The two types of states are dependent and evolve jointly according to a Markov process with a stationary transition probability. It is desired to reveal the monitored states to a receiver but hide the private states. For this purpose, a privacy filter is necessary which suitably perturbs the monitored states before communication with the receiver. Our objective is to design the privacy filter to optimize the tradeoff between the monitoring accuracy and privacy, measured through a time-invariant distortion measure and Shannon's equivocation, respectively. As the optimal privacy filter is difficult to compute using the dynamic programming, we adopt a suboptimal greedy approach through which the privacy filter can be computed efficiently. Here, the greedy approach has the additional advantage of not being restricted to the finite time horizon setups. Simulations show the superiority of the approach compared to a privacy filter which only adds independent noise to the observations.

  • 42.
    Moles-Cases, Vicent
    et al.
    Ericsson Res, Kista, Sweden..
    Zaidi, Ali A.
    Ericsson Res, Kista, Sweden..
    Chen, Xiaoming
    Qamcom Res & Technol, Gothenburg, Sweden..
    Oechtering, Tobias J.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Baldemair, Robert
    Ericsson Res, Kista, Sweden..
    A Comparison of OFDM, QAM-FBMC, and OQAM-FBMC Waveforms Subject to Phase Noise2017In: 2017 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC) / [ed] Gesbert, D Debbah, M Mellouk, A, IEEE , 2017Conference paper (Refereed)
    Abstract [en]

    Frequencies above 6 GHz are being considered by mobile communication industry for the deployment of future 5G networks. However in the higher carrier frequencies, especially the millimeter-wave frequencies (above 30 GHz), there can be severe degradations in the transmitted and received signals due to Phase Noise (PN) introduced by the local oscillators. In this paper, the effect of PN has been investigated for Orthogonal Frequency Division Multiplexing (OFDM), Offset QAM Filter-Bank Multi-Carrier (OQAM-FBMC) and QAM Filter-Bank Multi-Carrier (QAM-FBMC). The sources of degradation in these waveforms are quantified and closed-form expressions are derived for Signal-to-Interference Ratio (SIR). Evaluations are performed in terms of SIR and Symbol Error Rate (SER) for mm-wave frequencies using mmMAGIC PN model. The results reveal that OFDM outperforms OQAM-FBMC and QAM-FBMC and is a promising candidate for mm-wave communication.

  • 43.
    Montzka, Thomas
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Investigating the Potential of Using SOM on Audit Changed Trades2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    During the last 20 years, operational risk has been identified as an considerablerisk that needs to be tracked and handled, particular in the financial industry.The Basel Committee on banking supervision is a global cooperation thatsets standard regulations for banking corporations. The framework of Basel IIcontains an explicit definition and proposed calculation about the size of riskcapital needed. Beside this, the responsibility of how to manage and lower theoperational risk is still in the hands of the operating companies.The company Handelsbanken has identified that their operational risk riseswhen trades become the object of Audit Change. Because of the large numberof trades every day that are Audit Changed, the motivation is to automatevisualization and categorization of the trades, so focus can be given to thosetrades that are associated with higher risk.This thesis has been carried out to investigate the usage of the Self-OrganizingMaps (SOM), an unsupervised Machine Learning algorithm, to explore its potentialin gaining information from the trades that have been Audit Changed.The results reveal that SOM have several potential applications for Handelsbankento develop around the trades done in their business, especially withinAudit Changed but also in general for categorizing trades done in the company.

  • 44.
    Mouris, Boules Atef
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Quevedo-Teruel, Oscar
    KTH, School of Electrical Engineering and Computer Science (EECS), Electromagnetic Engineering.
    Thobaben, Ragnar
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Exploiting Glide Symmetry in Planar EBG Structures2018In: Journal of Physics, Conference Series, ISSN 1742-6588, E-ISSN 1742-6596, Vol. 963, no 1, article id 012002Article in journal (Refereed)
    Abstract [en]

    Periodic structures such as electromagnetic band gap (EBG) structures can be used to prevent the propagation of electromagnetic waves within a certain frequency range known as the stop band. One of the main limitations of using EBG structures at low frequencies is their relatively large size. In this paper, we investigate the possibility of using glide symmetry in planar EBG structures to reduce their size. Simulated results demonstrate that exploiting glide symmetry in EBG structures can lead to size reduction.

  • 45.
    Olfat, Ehsan
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Parameter Estimation of Nonlinearities in Future Wireless Systems2018Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Nowadays, our every-day life is immersed with wireless communications.From our hand-held cell-phones to televisions to navigation systems in cars, all and all are using wireless communications. This usage will even be enormouslyexpanded due to the introduction of the era of 5G-based Internet-of-Things(IoT) which consists wearables, sensors and more smart appliances.Orthogonal frequency division multiplexing is a very well-known commu-nication method which has been utilized in modern standards and technolo-gies due to its high spectral efficiency, simple frequency-domain equalization,and robustness against inter-symbol interference. Nevertheless, the major do-wnside of OFDM systems is the large fluctuations of the amplitudes of theirsignals causing high peak-to-average-power-ratio (PAPR). This forces the po-wer amplifier (PA) in the transmitter’s RF front-end to work in its saturationregion, hence introducing nonlinear distortion to the transmitted signal. Thisis particularly challenging in low-cost and low-power (and even low-weight)devices where a high-quality PA with a large dynamic range is not affordable,using complex digital processing techniques to mitigate the PAPR or to line-arize the PA is not computationally feasible, and introducing input back-offto change the operating point of the PA is not desirable due to decreasingthe power efficiency of the PA, which can be problematic because of the shortbattery-life. On the other hand, there are more resources available for a high-quality base station (or IoT gateway) in terms of power, budget, space and computational complexity, which motivates transferring all the complexity and cost to them and implement receiver-side nonlinearity estimation and compensation algorithms.To compensate the effects of a nonlinear PA on the transmitted signal and lastly detect them correctly, an iterative detection algorithm has been proposed in the literature. However, to use this algorithm successfully, thereceiver first needs to estimate the nonlinearity parameters. The importanceof this is more noticeable in the 5G-based Internet-of-Things networks, inwhich presumedly, numerous low-cost and low-power devices aim to transmitdata to a base station (or an IoT gateway).The focus of this thesis is on estimating the nonlinearity parameters al-ong with channel estimation, nonlinearity distortion mitigation, and symboldetection in future wireless systems deploying OFDM. In particular, we firstconsider an OFDM system with a limiter (clipper) communicating over anAWGN channel, and derive a maximum-likelihood estimator of the clippingamplitude. Next, we consider OFDM systems tranceiving over multi-pathfading channels, and propose a joint channel and clipping amplitude esti-mation algorithm using block-type frequency-domain pilots. Furthermore, we propose a new packet-frame consisting time-domain and frequency-domain pilots to separately estimate channel and clipping amplitude. After, we consider a broader types of memory less nonlinear PA models, and propose a jointestimation-detection algorithm to jointly estimate the nonlinearity parame-ters and channel and detect symbols. Finally, the joint channel and clipping amplitude estimation algorithm is extended to SIMO-OFDM systems. The performance of all of these algorithms are verified by means of simulations

  • 46.
    Olfat, Ehsan
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Bengtsson, Mats
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    A General Framework for JointChannel-Nonlinearity Parameters Estimation and Symbol Detection forOFDM in IoT-based 5G NetworksManuscript (preprint) (Other academic)
  • 47.
    Olfat, Ehsan
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Bengtsson, Mats
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Channel and Clipping Level Estimation in OFDMSystems2018Conference paper (Refereed)
  • 48.
    Olfat, Ehsan
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Bengtsson, Mats
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Estimation of the Clipping Level in OFDM Systems2015Conference paper (Refereed)
  • 49.
    Olfat, Ehsan
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Bengtsson, Mats
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Joint Channel and Clipping Level Estimationfor SIMO-OFDM Systems2018Conference paper (Refereed)
  • 50.
    Olfat, Ehsan
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Shokri-Ghadikolaei, Hossein
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Moghadam, Nima N.
    KTH.
    Bengtsson, Mats
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Learning-based Pilot Precoding and Combining for Wideband Millimeter-wave Networks2017In: 2017 IEEE 7TH INTERNATIONAL WORKSHOP ON COMPUTATIONAL ADVANCES IN MULTI-SENSOR ADAPTIVE PROCESSING (CAMSAP), IEEE , 2017Conference paper (Refereed)
    Abstract [en]

    This paper proposes an efficient channel estimation scheme with a minimum number of pilots for a frequency-selective millimeter-wave communication system. We model the dynamics of the channel's second-order statistics by a Markov process and develop a learning framework that finds the optimal precoding and combining vectors for pilot signals, given the channel dynamics. Using these vectors, the transmitter and receiver will sequentially estimate the corresponding angles of departure and arrival, and then refine the pilot precoding and combining vectors to minimize the error of estimating the small-scale fading of all subcarriers. Numerical results demonstrate near-optimality of our approach, compared to the oracle wherein the second-order statistics (not the dynamics) are perfectly known a priori.

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