MIMO signal processing in offset-QAM based filter bank multicarrier systems

Next-generation communication systems have to comply with very strict requirements for increased flexibility in heterogeneous environments, high spectral efficiency, and agility of carrier aggregation. This fact motivates research in advanced multicarrier modulation (MCM) schemes, such as filter bank-based multicarrier (FBMC) modulation. This paper focuses on the offset quadrature amplitude modulation (OQAM)-based FBMC variant, known as FBMC/OQAM, which presents outstanding spectral efficiency and confinement in a number of channels and applications. Its special nature, however, generates a number of new signal processing challenges that are not present in other MCM schemes, notably, in orthogonal-frequency-division multiplexing (OFDM). In multiple-input multiple-output (MIMO) architectures, which are expected to play a primary role in future communication systems, these challenges are intensified, creating new interesting research problems and calling for new ideas and methods that are adapted to the particularities of the MIMO-FBMC/OQAM system. The goal of this paper is to focus on these signal processing problems and provide a concise yet comprehensive overview of the recent advances in this area. Open problems and associated directions for future research are also discussed.Peer ReviewedPostprint (author's final draft

Channel estimation techniques for filter bank multicarrier based transceivers for next generation of wireless networks

A dissertation submitted to Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfillment of the requirements for the degree of Master of Science in Engineering (Electrical and Information Engineering), August 2017The fourth generation (4G) of wireless communication system is designed based on the principles of cyclic prefix orthogonal frequency division multiplexing (CP-OFDM) where the cyclic prefix (CP) is used to combat inter-symbol interference (ISI) and inter-carrier interference (ICI) in order to achieve higher data rates in comparison to the previous generations of wireless networks. Various filter bank multicarrier systems have been considered as potential waveforms for the fast emerging next generation (xG) of wireless networks (especially the fifth generation (5G) networks). Some examples of the considered waveforms are orthogonal frequency division multiplexing with offset quadrature amplitude modulation based filter bank, universal filtered multicarrier (UFMC), bi-orthogonal frequency division multiplexing (BFDM) and generalized frequency division multiplexing (GFDM). In perfect reconstruction (PR) or near perfect reconstruction (NPR) filter bank designs, these aforementioned FBMC waveforms adopt the use of well-designed prototype filters (which are used for designing the synthesis and analysis filter banks) so as to either replace or minimize the CP usage of the 4G networks in order to provide higher spectral efficiencies for the overall increment in data rates. The accurate designing of the FIR low-pass prototype filter in NPR filter banks results in minimal signal distortions thus, making the analysis filter bank a time-reversed version of the corresponding synthesis filter bank. However, in non-perfect reconstruction (Non-PR) the analysis filter bank is not directly a time-reversed version of the corresponding synthesis filter bank as the prototype filter impulse response for this system is formulated (in this dissertation) by the introduction of randomly generated errors. Hence, aliasing and amplitude distortions are more prominent for Non-PR. Channel estimation (CE) is used to predict the behaviour of the frequency selective channel and is usually adopted to ensure excellent reconstruction of the transmitted symbols. These techniques can be broadly classified as pilot based, semi-blind and blind channel estimation schemes. In this dissertation, two linear pilot based CE techniques namely the least square (LS) and linear minimum mean square error (LMMSE), and three adaptive channel estimation schemes namely least mean square (LMS), normalized least mean square (NLMS) and recursive least square (RLS) are presented, analyzed and documented. These are implemented while exploiting the near orthogonality properties of offset quadrature amplitude modulation (OQAM) to mitigate the effects of interference for two filter bank waveforms (i.e. OFDM/OQAM and GFDM/OQAM) for the next generation of wireless networks assuming conditions of both NPR and Non-PR in slow and fast frequency selective Rayleigh fading channel. Results obtained from the computer simulations carried out showed that the channel estimation schemes performed better in an NPR filter bank system as compared with Non-PR filter banks. The low performance of Non-PR system is due to the amplitude distortion and aliasing introduced from the random errors generated in the system that is used to design its prototype filters. It can be concluded that RLS, NLMS, LMS, LMMSE and LS channel estimation schemes offered the best normalized mean square error (NMSE) and bit error rate (BER) performances (in decreasing order) for both waveforms assuming both NPR and Non-PR filter banks. Keywords: Channel estimation, Filter bank, OFDM/OQAM, GFDM/OQAM, NPR, Non-PR, 5G, Frequency selective channel.CK201

Channel estimation techniques for next generation mobile communication systems

Mención Internacional en el título de doctorWe are witnessing a revolution in wireless technology, where the society is demanding new services, such as smart cities, autonomous vehicles, augmented reality, etc. These challenging services not only are demanding an enormous increase of data rates in the range of 1000 times higher, but also they are real-time applications with an important delay constraint. Furthermore, an unprecedented number of different machine-type devices will be also connected to the network, known as Internet of Things (IoT), where they will be transmitting real-time measurements from different sensors. In this context, the Third Generation Partnership Project (3GPP) has already developed the new Fifth Generation (5G) of mobile communication systems, which should be capable of satisfying all the requirements. Hence, 5G will provide three key aspects, such as: enhanced mobile broad-band (eMBB) services, massive machine type communications (mMTC) and ultra reliable low latency communications (URLLC). In order to accomplish all the mentioned requirements, it is important to develop new key radio technologies capable of exploiting the wireless environment with a higher efficiency. Orthogonal frequency division multiplexing (OFDM) is the most widely used waveform by the industry, however, it also exhibits high side lobes reducing considerably the spectral efficiency. Therefore, filter-bank multi-carrier combined with offset quadrature amplitude modulation (FBMC-OQAM) is a waveform candidate to replace OFDM due to the fact that it provides extremely low out-ofband emissions (OBE). The traditional spectrum frequencies range is close to saturation, thus, there is a need to exploit higher bands, such as millimeter waves (mm-Wave), making possible the deployment of ultra broad-band services. However, the high path loss in these bands increases the blockage probability of the radio-link, forcing us to use massive multiple-input multiple-output (MIMO) systems in order to increase either the diversity or capacity of the overall link. All these emergent radio technologies can make 5G a reality. However, all their benefits can be only exploited under the knowledge and availability of the channel state information (CSI) in order to compensate the effects produced by the channel. The channel estimation process is a well known procedure in the area of signal processing for communications, where it is a challenging task due to the fact that we have to obtain a good estimator, maintaining at the same time the efficiency and reduced complexity of the system and obtaining the results as fast as possible. In FBMC-OQAM, there are several proposed channel estimation techniques, however, all of them required a high number of operations in order to deal with the self-interference produced by the prototype filter, hence, increasing the complexity. The existing channel estimation and equalization techniques for massive MIMO are in general too complex due to the large number of antennas, where we must estimate the channel response of each antenna of the array and perform some prohibitive matrix inversions to obtain the equalizers. Besides, for the particular case of mm-Wave, the existing techniques either do not adapt well to the dynamic ranges of signal-to-noise ratio (SNR) scenarios or they assume some approximations which reduce the quality of the estimator. In this thesis, we focus on the channel estimation for different emerging techniques that are capable of obtaining a better performance with a lower number of operations, suitable for low complexity devices and for URLLC. Firstly, we proposed new pilot sequences for FBMC-OQAM enabling the use of a simple averaging process in order to obtain the CSI. We show that our technique outperforms the existing ones in terms of complexity and performance. Secondly, we propose an alternative low-complexity way of computing the precoding/postcoding equalizer under the scenario of massive MIMO, keeping the quality of the estimator. Finally, we propose a new channel estimation technique for massive MIMO for mm-Wave, capable of adapting to very variable scenarios in terms of SNR and outperforming the existing techniques. We provide some analysis of the mean squared error (MSE) and complexity of each proposed technique. Furthermore, some numerical results are given in order to provide a better understanding of the problem and solutions.Programa de Doctorado en Multimedia y Comunicaciones por la Universidad Carlos III de Madrid y la Universidad Rey Juan CarlosPresidente: Antonia María Tulino.- Secretario: Máximo Morales Céspedes.- Vocal: Octavia A. Dobr

Advanced multi-dimensional signal processing for wireless systems

Die florierende Entwicklung der drahtlosen Kommunikation erfordert innovative und fortschrittliche Signalverarbeitungsalgorithmen, die auf eine verbesserte Performance hinsichtlich der Zuverlässigkeit, des Durchsatzes, der Effizienz und weiterer Faktoren abzielen. Die vorliegende Arbeit befasst sich mit der Lösung dieser Herausforderungen und präsentiert neue und faszinierende Fortschritte, um diesen Herausforderungen zu erfüllen. Hauptsächlich konzentrieren wir uns auf zwei innovative Aspekte der mehrdimensionalen Signalverarbeitung für drahtlose Systeme, denen in den letzten Jahren große Aufmerksamkeit in der Forschung geschenkt wurde. Das sind Mehrträgerverfahren für Multiple-Input Multiple-Output (MIMO) Systeme und die mehrdimensionale harmonische Schätzung (Harmonic Retrieval). Da es sich bei MIMO-Systemen und Mehrträgerverfahren um Schlüsseltechnologien der drahtlosen Kommunikation handelt, sind ihre zahlreichen Vorteile seit langem bekannt und haben ein großes Forschungsinteresse geweckt. Zu diesen Vorteilen zählen zum Beispiel die Steigerung der Datenrate und die Verbesserung der Verbindungszuverlässigkeit. Insbesondere OFDM-basierte MIMO Downlink Systeme für mehrere Teilnehmer (Multi-User MIMO Downlink Systems), die durch SDMA (Space-Division Multiple Access) getrennt werden, kombinieren die Vorteile von MIMO-Systemen mit denen von Mehrträger-Modulationsverfahren. Sie sind wesentliche Elemente des IEEE 802.11ac Standards und werden ebenfalls für 5G (die fünfte Mobilfunkgeneration) ausschlaggebend sein. Obwohl die bisherigen Arbeiten über das Precoding (Vorcodierung) für solche Multi-User MIMO Downlink Systeme schon fruchtbare Ergebnisse zeigten, werden neue Fortschritte benötigt, die den Mehrträger-Charakter des Systems in einer effizienteren Weise ausnutzen oder auf eine höhere spektrale Effizienz des Gesamtsystems abzielen. Andererseits gilt die Filterbank-basierte Mehrträger Modulation (Filter Bank-based Multi-Carrier modulation, FBMC) mit einem gut konzentrierten Spektrum und einer somit niedrigen Out-of-band Leackage als eine vielversprechende Alternative zu OFDM. FBMC ermöglicht eine effiziente Nutzung von Fragmenten im Frequenzspektrums, z. B. in 5G oder Breitband Professional Mobile Radio (PMR) Netzwerken. Jedoch leiden die vorhandenen Verfahren zur Sende- und-Empfangs-Verarbeitung für FBMC-basierte MIMO Systeme unter Einschränkungen in Bezug auf mehrere Aspekte, wie z. B. der erlaubten Dimensionalität des Systems und der zulässigen Frequenzselektivität des Kanals. Die Formen der MIMO Einstellungen, die in der Literatur untersucht wurden, sind noch begrenzt auf MIMO-Systeme für einzelne Teilnehmer und vereinfachte Multi-User MIMO Systeme. Fortschrittlichere Techniken sind daher erforderlich, die diese Einschränkungen der existierenden Verfahren aufheben. MIMO-Szenarien, die weniger Einschränkungen unterliegen, müssen außerdem untersucht werden, um die Vorteile von FBMC zu weiter herauszuarbeiten. Im Rahmen der mehrdimensionalen harmonischen Schätzung (Harmonic Retrieval) hat sich gezeigt, dass eine höhere Genauigkeit bei der Schätzung durch Tensoren erreicht werden kann. Das liegt daran, dass die Darstellung mehrdimensionaler Signale mit Tensoren eine natürlichere Beschreibung und eine gute Ausnutzung ihrer mehrdimensionalen Struktur erlaubt, z. B. für die Modellordnungsschätzung und die Unterraumschätzung. Wichtige offene Themen umfassen die statistische Robustheit und wie man die Schätzung in zeitlich variierenden Szenarien adaptiv gestalten kann. In Teil I dieser Arbeit präsentieren wir zunächst eine effiziente und flexible Übertragungsstrategie für OFDM-basierten Multi-User MIMO Downlink Systeme. Sie besteht aus einer räumlichen Scheduling-Methode, der effizienten Mehrträger ProSched (Efficient Multi-Carrier ProSched, EMC-ProSched) Erweiterung mit einer effektiven Scheduling-Metrik, die auf Mehrträger-Systeme zugeschnitten wird. Weiterhin werden zwei neuartige Precoding Algorithmen vorgestellt, die lineare Precoding-basierte geometrische Mittelwert-Zerlegung (Linear Precoding-based Geometric Mean Decomposition, LP-GMD) und ein Coordinated Beamforming Algorithmus geringer Komplexität (Low Complexity Coordinated Beamforming, LoCCoBF). Diese beiden neuen Precoding-Verfahren können flexibel entsprechend den Abmessungen des Systems gewählt werden. Wir entwickeln auch einen System Level-Simulator, in dem die Parameter für das Link-to-System Level Interface kalibriert werden können. Diese Kalibrierung ist Standard-spezifisch, z. B. kann der Standard IEEE 802.11ac gewählt werden. Numerische Ergebnisse zeigen, dass diese Übertragungsstrategie Scheduling Fairness garantiert, einen weitaus höheren Durchsatz als die existierenden Verfahren erzielt, eine geringere Komplexität besitzt und nur einen geringen Signalisierungsoverhead erfordert. Der Schwerpunkt des Rests von Teil I bilden MIMO Systeme basierend auf Filter Bank-basierten Mehrträger-Verfahren mit Offset Quadrature Amplitude Modulation (FBMC/OQAM). Es wird ein umfassender Überblick über FBMC gegeben. Nachfolgend werden für verschiedene FBMC/OQAM-basierte MIMO Varianten neue Verfahren zur Sende- und Empfangs-Verarbeitung entwickelt, die unterschiedliche Grade von Frequenz-Selektivität des Kanals voraussetzen. Zunächst wird die Verwendung von weitgehend linearer Verarbeitung (widely linear processing) untersucht. Ein Zwei-Schritt-Empfänger wird für FBMC/OQAM-basierte MIMO Systeme mit einzelnen Teilnehmern entwickelt. Hierbei ist die Frequenz-Selektivität des Kanals niedrig. Verglichen mit linearen MMSE-Empfänger ist die Leistung des Zwei-Schritt-Empfängers viel besser. Das Grundprinzip dieser Zwei-Schritt-Empfänger ist zuerst die Verringerung der intrinsischen Interferenz, um die Ausnutzung von nicht-zirkulären Signalen zu ermöglichen. Es motiviert weitere Studien über weitgehend lineare Verfahren für FBMC/OQAM-basierte Systeme. Darüber hinaus werden zwei Coordinated Beamforming-Algorithmen für FBMC/OQAM-basierte MIMO Systeme mit einzelnen Teilnehmern entwickelt. Sie verzichten auf die Einschränkung der Dimensionalität der bestehenden Methode, bei der die Anzahl der Sendeantennen größer als die Anzahl der Empfangsantennen sein muss. Der Kanal auf jedem Träger wird als flacher Schwund (Flat Fading) modelliert, was einer Klassifizierung als „intermediate frequency selective channel“ entspricht. Unter der Kenntnis der Kanalzustandsinformation am Sender (Channel-State-Information at the Transmitter, CSIT) basiert die Vorcodierung entweder auf einem Zero Forcing (ZF) Kriterium oder auf der Maximierung der Signal-to-Leackage-plus-Noise-Ratio (SLNR). Die Vorcodierungsvektoren und die Empfangsvektoren werden gemeinsam und iterativ berechnet. Daher führen die zwei Coordinated Beamforming-Algorithmen zu einer wirksamen Verringerung der intrinsischen Interferenz in FBMC/OQAM-basierten Systemen. Die Vorteile der Coordinated Beamforming-Konzepte werden in FBMC/OQAM-basierten Multi-User MIMO Downlink Systeme und koordinierte Mehrpunktverbindung (Coordinated Multi-Point, CoMP-Konzepte) eingebracht. Dafür werden drei intrinsische Interferenz mildernde koordinierte Beamforming-Verfahren (Intrinsic Interference Mitigating Coordinated Beamforming, IIM-CBF) vorgeschlagen. Die ersten beiden IIM-CBF Algorithmen werden für die FBMC/OQAM-basierten Multi-User MIMO Downlink Varianten mit unterschiedlichen Dimensionen entwickelt. Es wird gezeigt, dass diese Verfahren zu einer Abschwächung der Multi-User-Interferenz (MUI) sowie einer Verringerung der intrinsischen Interferenz führen. Bei der dritten IIM-CBF Methode wird ein neuartiges FBMC/OQAM-basiertes-CoMP Konzept vorgestellt. Dieses wird durch die gemeinsame Übertragung von benachbarten Zellen zu Teilnehmern, die sich am Zellenrand befinden, ermöglicht, um den Daten-Durchsatz am Zellenrand zu erhöhen. Die Leistungsfähigkeit der vorgeschlagenen Algorithmen wird durch umfangreiche numerische Simulationen evaluiert. Das Konvergenzverhalten wird untersucht sowie das Thema der Komplexität angesprochen. Außerdem wird die geringere Anfälligkeit von FBMC verglichen mit OFDM gegenüber Frequenzsynchronisationsfehlern demonstriert. Darüber hinaus wird auf die FBMC/OQAM-basierten Multi-User MIMO Downlink Systeme mit stark frequenzselektiven Kanälen eingegangen. Dafür werden Lösungen erarbeitet, die für die Unterdrückung der MUI, der Inter-Symbol Interferenz (ISI) sowie der Inter-Carrier Interferenz (ICI) anwendbar ist. Mehrere Kriterien der multi-tap Vorcodierung werden entwickelt, beispielsweise die Mean Squared Error (MSE) Minimierung sowie die Signal-to-Leakage-Ratio (SLR) und die SLNR Maximierung. An Endgeräten, die eine schwächere Rechenleistung besitzen als sie an der Basisstation vorhanden ist, wird dadurch nur ein single-tap Empfangsfilter benötigt. Teil II der Arbeit konzentriert sich auf die mehrdimensionale harmonische Schätzung (Harmonic Retrieval). Der Einbau von statistischer Robustheit in mehrdimensionale Modellordnungsschätzverfahren wird demonstriert.The thriving development of wireless communications calls for innovative and advanced signal processing techniques targeting at an enhanced performance in terms of reliability, throughput, robustness, efficiency, flexibility, etc.. This thesis addresses such a compelling demand and presents new and intriguing progress towards fulfilling it. We mainly concentrate on two advanced multi-dimensional signal processing challenges for wireless systems that have attracted tremendous research attention in recent years, multi-carrier Multiple-Input Multiple-Output (MIMO) systems and multi-dimensional harmonic retrieval. As the key technologies of wireless communications, the numerous benefits of MIMO and multi-carrier modulation, e.g., boosting the data rate and improving the link reliability, have long been identified and have ignited great research interest. In particular, the Orthogonal Frequency Division Multiplexing (OFDM)-based multi-user MIMO downlink with Space-Division Multiple Access (SDMA) combines the twofold advantages of MIMO and multi-carrier modulation. It is the essential element of IEEE 802.11ac and will also be crucial for the fifth generation of wireless communication systems (5G). Although past investigations on scheduling and precoding design for multi-user MIMO downlink systems have been fruitful, new advances are desired that exploit the multi-carrier nature of the system in a more efficient manner or aim at a higher spectral efficiency. On the other hand, a Filter Bank-based Multi-Carrier modulation (FBMC) featuring a well-concentrated spectrum and thus a low out-of-band radiation is regarded as a promising alternative multi-carrier scheme to OFDM for an effective utilization of spectrum fragments, e.g., in 5G or broadband Professional Mobile Radio (PMR) networks. Unfortunately, the existing transmit-receive processing schemes for FBMC-based MIMO systems suffer from limitations in several aspects, e.g., with respect to the number of supported receive antennas (dimensionality constraint) and channel frequency selectivity. The forms of MIMO settings that have been investigated are still limited to single-user MIMO and simplified multi-user MIMO systems. More advanced techniques are therefore demanded to alleviate the constraints imposed on the state-of-the-art. More sophisticated MIMO scenarios are yet to be explored to further corroborate the benefits of FBMC. In the context of multi-dimensional harmonic retrieval, it has been demonstrated that a higher estimation accuracy can be achieved by using tensors to preserve and exploit the multidimensional nature of the data, e.g., for model order estimation and subspace estimation. Crucial pending topics include how to further incorporate statistical robustness and how to handle time-varying scenarios in an adaptive manner. In Part I of this thesis, we first present an efficient and flexible transmission strategy for OFDM-based multi-user MIMO downlink systems. It consists of a spatial scheduling scheme, efficient multi-carrier ProSched (EMC-ProSched), with an effective scheduling metric tailored for multi-carrier systems and two new precoding algorithms, linear precoding-based geometric mean decomposition (LP-GMD) and low complexity coordinated beamforming (LoCCoBF). These two new precoding schemes can be flexibly chosen according to the dimensions of the system. We also develop a system-level simulator where the parameters for the link-to-system level interface can be calibrated according to a certain standardization framework, e.g., IEEE 802.11ac. Numerical results show that the proposed transmission strategy, apart from guaranteeing the scheduling fairness and a small signaling overhead, achieves a much higher throughput than the state-of-the-art and requires a lower complexity. The remainder of Part I is dedicated to Filter Bank-based Multi-Carrier with Offset Quadrature Amplitude Modulation (FBMC/OQAM)-based MIMO systems. We begin with a thorough overview of FBMC. Then we present new transmit-receive processing techniques for FBMC/OQAM-based MIMO settings ranging from the single-user MIMO case to the Coordinated Multi-Point (CoMP) downlink considering various degrees of channel frequency selectivity. The use of widely linear processing is first investigated. A two-step receiver is designed for FBMC/OQAM-based point-to-point MIMO systems with low frequency selective channels. It exhibits a significant performance superiority over the linear MMSE receiver. The rationale in this two-step receiver is that the intrinsic interference is first mitigated to facilitate the exploitation of the non-circularity residing in the signals. It sheds light upon further studies on widely linear processing for FBMC/OQAM-based systems. Moreover, two coordinated beamforming algorithms are devised for FBMC/OQAM-based point-to-point MIMO systems to relieve the dimensionality constraint of existing schemes that the number of transmit antennas must be larger than the number of receive antennas. The channel on each subcarrier is assumed to be flat fading, which is categorized as the class of intermediate frequency selective channels. With the Channel State Information at the Transmitter (CSIT) known, the precoder designed based on a Zero Forcing (ZF) criterion or the maximization of the Signal-to-Leakage-plus-Noise-Ratio (SLNR) is jointly and iteratively computed with the receiver, leading to an effective mitigation of the intrinsic interference inherent in FBMC/OQAM-based systems. The benefits of the coordinated beamforming concept are successfully translated into the FBMC/OQAM-based multi-user MIMO downlink and the CoMP downlink. Three intrinsic interference mitigating coordinated beamforming (IIM-CBF) schemes are developed. The first two IIM-CBF schemes are proposed for FBMC/OQAM-based multi-user MIMO downlink settings with different dimensions and are able to effectively suppress the Multi-User Interference (MUI) as well as the intrinsic interference. A novel FBMC/OQAM-based CoMP concept is established via the third IIM-CBF scheme which enables the joint transmission of adjacent cells to the cell edge users to combat the strong interference as well as the heavy path loss and to boost the cell edge throughput. The performance of the proposed algorithms is evaluated via extensive numerical simulations. Their convergence behavior is studied, and the complexity issue is also addressed. In addition, the stronger resilience of FBMC over OFDM against frequency misalignments is demonstrated. Furthermore, we cover the case of highly frequency selective channels and provide solutions to the very challenging task of suppressing the MUI, the Inter-Symbol Interference (ISI), as well as the Inter-Carrier Interference (ICI) and supporting per-user multi-stream transmissions. Several design criteria of the multi-tap precoders are devised including the Mean Squared Error (MSE) minimization as well as the Signal-to-Leakage-Ratio (SLR) and SLNR maximization. By rendering a larger computational load at the base station, only single-tap spatial receive filters are required at the user terminals with a weaker computational capability, which enhances the applicability of the proposed schemes in real-world multi-user MIMO downlink systems. Part II focuses on the context of multi-dimensional harmonic retrieval. We demonstrate the incorporation of statistical robustness into multi-dimensional model order estimation schemes by substituting the sample covariance matrices of the unfoldings of the measurement tensor with robust covariance estimates. It is observed that in the presence of a very severe contamination of the measurements due to brief sensor failures, the robustified tensor-based model order estimation schemes lead to a satisfactory estimation accuracy. This philosophy of introducing statistical robustness also inspires robust versions of parameter estimation algorithms. Last but not the least, we present a generic framework for Tensor-based subspace tracking via Kronecker-structured projections (TeTraKron) for time-varying multi-dimensional harmonic retrieval problems. It allows to extend arbitrary matrix-based subspace tracking schemes to track the tensor-based subspace estimate in an elegant and efficient manner. By including forward-backward-averaging, we show that TeTraKron can also be employed to devise real-valued tensor-based subspace tracking algorithms. Taking a few matrix-based subspace tracking approaches as an example, a remarkable improvement of the tracking accuracy is observed in case of the TeTraKron-based tensor extensions. The performance of ESPRIT-type parameter estimation schemes is also assessed where the subspace estimates obtained by the proposed TeTraKron-based subspace tracking algorithms are used. We observe that Tensor-ESPRIT combined with a tensor-based subspace tracking scheme significantly outperforms the combination of standard ESPRIT and the corresponding matrix-based subspace tracking method. These results open the way for robust multi-dimensional big data signal processing applications in time-varying environments

Review of Recent Trends

This work was partially supported by the European Regional Development Fund (FEDER), through the Regional Operational Programme of Centre (CENTRO 2020) of the Portugal 2020 framework, through projects SOCA (CENTRO-01-0145-FEDER-000010) and ORCIP (CENTRO-01-0145-FEDER-022141). Fernando P. Guiomar acknowledges a fellowship from “la Caixa” Foundation (ID100010434), code LCF/BQ/PR20/11770015. Houda Harkat acknowledges the financial support of the Programmatic Financing of the CTS R&D Unit (UIDP/00066/2020).MIMO-OFDM is a key technology and a strong candidate for 5G telecommunication systems. In the literature, there is no convenient survey study that rounds up all the necessary points to be investigated concerning such systems. The current deeper review paper inspects and interprets the state of the art and addresses several research axes related to MIMO-OFDM systems. Two topics have received special attention: MIMO waveforms and MIMO-OFDM channel estimation. The existing MIMO hardware and software innovations, in addition to the MIMO-OFDM equalization techniques, are discussed concisely. In the literature, only a few authors have discussed the MIMO channel estimation and modeling problems for a variety of MIMO systems. However, to the best of our knowledge, there has been until now no review paper specifically discussing the recent works concerning channel estimation and the equalization process for MIMO-OFDM systems. Hence, the current work focuses on analyzing the recently used algorithms in the field, which could be a rich reference for researchers. Moreover, some research perspectives are identified.publishersversionpublishe

Estudo de formas de onda e conceção de algoritmos para operação conjunta de sistemas de comunicação e radar

The focus of this thesis is the processing of signals and design of algorithms that can be used to enable radar functions in communications systems. Orthogonal frequency division multiplexing (OFDM) is a popular multicarrier modulation waveform in communication systems. As a wideband signal, OFDM improves resolution and enables spectral efficiency in radar systems, while also improving detection performance thanks to its inherent frequency diversity. This thesis aims to use multicarrier waveforms for radar systems, to enable the simultaneous operation of radar and communication functions on the same device. The thesis is divided in two parts. The first part, studies the adaptation and application of other multicarrier waveforms to radar functions. At the present time many studies have been carried out to jointly use the OFDM signal for communication and radar functions, but other waveforms have shown to be possible candidates for communication applications. Therefore, studies on the evaluation of the application of these same signals to radar functions are necessary. In this thesis, to demonstrate that other multicarrier waveforms can overcome the OFDM waveform in radar/communication (RadCom) systems, we propose the adaptation of the filter bank multicarrier (FBMC), generalized frequency division multiplexing (GFDM) and universal filtering multicarrier (UFMC) waveforms for radar functions. These alternative waveforms were compared performance-wise regarding achievable target parameter estimation performance, amount of residual background noise in the radar image, impact of intersystem interference and flexibility of parameterization. In the second part of the thesis, signal processing techniques are explored to solve some of the limitations of the use of multicarrier waveforms for RadCom systems. Radar systems based on OFDM are promising candidates for future intelligent transport networks. Exploring the dual functionality enabled by OFDM, we presents cooperative methods for high-resolution delay-Doppler and direction-of-arrival estimation. High-resolution parameter estimation is an important requirement for automotive radar systems, especially in multi-target scenarios that require reliable target separation performance. By exploring the cooperation between vehicles, the studies presented in this thesis also enable the distributed tracking of targets. The result is a highly accurate multi-target tracking across the entire cooperative vehicle network, leading to improvements in transport reliability and safety.O foco desta tese é o processamento de sinais e desenvolvimento de algoritmos que podem ser utilizados para a habilitar a função de radar nos sistemas de comunicação. OFDM (Orthogonal Frequency Division Multiplexing) é uma forma de onda com modulação multi-portadora, popular em sistemas de comunicação. Para sistemas de radar, O OFDM melhora a resolução e fornece eficiência espectral, além disso sua diversidade de frequências melhora o desempenho na detecção do radar. Essa tese tem como objetivo utilizar formas de onda multi-portadoras para sistemas de radar, possibilitando a operação simultânea de funções de radar e de comunicação num mesmo dispositivo. A tese esta dividida em duas partes. Na primeira parte da tese são realizados estudos da adaptabilidade de outras formas de onda multi-portadora para funções de radar. Nos dias atuais, muitos estudos sobre o uso do sinal OFDM para funções de comunicação e radar vêm sendo realizados, no entanto, outras formas de onda mostram-se possíveis candidatas a aplicações em sistemas de comunicação, e assim, avaliações para funções de sistema de radar se tornam necessárias. Nesta tese, com a intenção de demonstrar que formas de onda multi-portadoras alternativas podem superar o OFDM nos sistemas de Radar/comunicação (RadCom), propomos a adaptação das seguintes formas de onda: FBMC (Filter Bank Multicarrier); GFDM (Generalized Frequency Division Multiplexing); e UFMC (Universal Filtering Multicarrier) para funções de radar. Também produzimos uma análise de desempenho dessas formas de onda sobre o aspecto da estimativa de parâmetros-alvo, ruído de fundo, interferência entre sistemas e parametrização do sistema. Na segunda parte da tese serão explorados técnicas de processamento de sinal de forma a solucionar algumas das limitações do uso de formas de ondas multi-portadora para sistemas RadCom. Os sistemas de radar baseados no OFDM são candidatos promissores para futuras redes de transporte inteligentes, porque combinam funções de estimativa de alvo com funções de rede de comunicação em um único sistema. Explorando a funcionalidade dupla habilitada pelo OFDM, nesta tese, apresentamos métodos cooperativos de alta resolução para estimar o posição, velocidade e direção dos alvos. A estimativa de parâmetros de alta resolução é um requisito importante para sistemas de radar automotivo, especialmente em cenários de múltiplos alvos que exigem melhor desempenho de separação de alvos. Ao explorar a cooperação entre veículos, os estudos apresentados nesta tese também permitem o rastreamento distribuído de alvos. O resultado é um rastreamento multi-alvo altamente preciso em toda a rede de veículos cooperativos, levando a melhorias na confiabilidade e segurança do transporte.Programa Doutoral em Telecomunicaçõe

Resource Management in Multicarrier Based Cognitive Radio Systems

The ever-increasing growth of the wireless application and services affirms the importance of the effective usage of the limited radio spectrum. Existing spectrum management policies have led to significant spectrum under-utilization. Recent measurements showed that large range of the spectrum is sparsely used in both temporal and spatial manner. This conflict between the inefficient usage of the spectrum and the continuous evolution in the wireless communication calls upon the development of more flexible management policies. Cognitive radio (CR) with the dynamic spectrum access (DSA) is considered to be a key technology in making the best solution of this conflict by allowing a group of secondary users (SUs) to share the radio spectrum originally allocated to the primary user (PUs). The operation of CR should not negatively alter the performance of the PUs. Therefore, the interference control along with the highly dynamic nature of PUs activities open up new resource allocation problems in CR systems. The resource allocation algorithms should ensure an effective share of the temporarily available frequency bands and deliver the solutions in timely fashion to cope with quick changes in the network. In this dissertation, the resource management problem in multicarrier based CR systems is considered. The dissertation focuses on three main issues: 1) design of efficient resource allocation algorithms to allocate subcarriers and powers between SUs such that no harmful interference is introduced to PUs, 2) compare the spectral efficiency of using different multicarrier schemes in the CR physical layer, specifically, orthogonal frequency division multiplexing (OFDM) and filter bank multicarrier (FBMC) schemes, 3) investigate the impact of the different constraints values on the overall performance of the CR system. Three different scenarios are considered in this dissertation, namely downlink transmission, uplink transmission, and relayed transmission. For every scenario, the optimal solution is examined and efficient sub-optimal algorithms are proposed to reduce the computational burden of obtaining the optimal solution. The suboptimal algorithms are developed by separate the subcarrier and power allocation into two steps in downlink and uplink scenarios. In the relayed scenario, dual decomposition technique is used to obtain an asymptotically optimal solution, and a joint heuristic algorithm is proposed to find the suboptimal solution. Numerical simulations show that the proposed suboptimal algorithms achieve a near optimal performance and perform better than the existing algorithms designed for cognitive and non-cognitive systems. Eventually, the ability of FBMC to overcome the OFDM drawbacks and achieve more spectral efficiency is verified which recommends the consideration of FBMC in the future CR systems.El crecimiento continuo de las aplicaciones y servicios en sistemas inal´ambricos, indica la importancia y necesidad de una utilizaci´on eficaz del espectro radio. Las pol´ıticas actuales de gesti´on del espectro han conducido a una infrautilizaci´on del propio espectro radioel´ectrico. Recientes mediciones en diferentes entornos han mostrado que gran parte del espectro queda poco utilizado en sus ambas vertientes, la temporal, y la espacial. El permanente conflicto entre el uso ineficiente del espectro y la evoluci´on continua de los sistemas de comunicaci´on inal´ambrica, hace que sea urgente y necesario el desarrollo de esquemas de gesti´on del espectro m´as flexibles. Se considera el acceso din´amico (DSA) al espectro en los sistemas cognitivos como una tecnolog´ıa clave para resolver este conflicto al permitir que un grupo de usuarios secundarios (SUs) puedan compartir y acceder al espectro asignado inicialmente a uno o varios usuarios primarios (PUs). Las operaciones de comunicaci´on llevadas a cabo por los sistemas radio cognitivos no deben en ning´un caso alterar (interferir) los sistemas primarios. Por tanto, el control de la interferencia junto al gran dinamismo de los sistemas primarios implica nuevos retos en el control y asignaci´on de los recursos radio en los sistemas de comunicaci´on CR. Los algoritmos de gesti´on y asignaci´on de recursos (Radio Resource Management-RRM) deben garantizar una participaci´on efectiva de las bandas con frecuencias disponibles temporalmente, y ofrecer en cada momento oportunas soluciones para hacer frente a los distintos cambios r´apidos que influyen en la misma red. En esta tesis doctoral, se analiza el problema de la gesti´on de los recursos radio en sistemas multiportadoras CR, proponiendo varias soluciones para su uso eficaz y coexistencia con los PUs. La tesis en s´ı, se centra en tres l´ıneas principales: 1) el dise˜no de algoritmos eficientes de gesti´on de recursos para la asignaci´on de sub-portadoras y distribuci´on de la potencia en sistemas segundarios, evitando asi cualquier interferencia que pueda ser perjudicial para el funcionamiento normal de los usuarios de la red primaria, 2) analizar y comparar la eficiencia espectral alcanzada a la hora de utilizar diferentes esquema de transmisi´on multiportadora en la capa f´ısica del sistema CR, espec´ıficamente en sistemas basados en OFDM y los basados en banco de filtros multiportadoras (Filter bank Multicarrier-FBMC), 3) investigar el impacto de las diferentes limitaciones en el rendimiento total del sistema de CR. Los escenarios considerados en esta tesis son tres, es decir; modo de transmisi´on descendente (downlink), modo de transmisi´on ascendente (uplink), y el modo de transmisi´on ”Relay”. En cada escenario, la soluci´on ´optima es examinada y comparada con algoritmos sub- ´optimos que tienen como objetivo principal reducir la carga computacional. Los algoritmos sub-´optimos son llevados a cabo en dos fases mediante la separaci´on del propio proceso de distribuci´on de subportadoras y la asignaci´on de la potencia en los modos de comunicaci´on descendente (downlink), y ascendente (uplink). Para los entornos de tipo ”Relay”, se ha utilizado la t´ecnica de doble descomposici´on (dual decomposition) para obtener una soluci´on asint´oticamente ´optima. Adem´as, se ha desarrollado un algoritmo heur´ıstico para poder obtener la soluci´on ´optima con un reducido coste computacional. Los resultados obtenidos mediante simulaciones num´ericas muestran que los algoritmos sub-´optimos desarrollados logran acercarse a la soluci´on ´optima en cada uno de los entornos analizados, logrando as´ı un mayor rendimiento que los ya existentes y utilizados tanto en entornos cognitivos como no-cognitivos. Se puede comprobar en varios resultados obtenidos en la tesis la superioridad del esquema multiportadora FBMC sobre los sistemas basados en OFDM para los entornos cognitivos, causando una menor interferencia que el OFDM en los sistemas primarios, y logrando una mayor eficiencia espectral. Finalmente, en base a lo analizado en esta tesis, podemos recomendar al esquema multiportadora FBMC como una id´onea y potente forma de comunicaci´on para las futuras redes cognitivas

D4.1 Draft air interface harmonization and user plane design

The METIS-II project envisions the design of a new air interface in order to fulfil all the performance requirements of the envisioned 5G use cases including some extreme low latency use cases and ultra-reliable transmission, xMBB requiring additional capacity that is only available in very high frequencies, as well as mMTC with extremely densely distributed sensors and very long battery life requirements. Designing an adaptable and flexible 5G Air Interface (AI), which will tackle these use cases while offering native multi-service support, is one of the key tasks of METIS-II WP4. This deliverable will highlight the challenges of designing an AI required to operate in a wide range of spectrum bands and cell sizes, capable of addressing the diverse services with often diverging requirements, and propose a design and suitability assessment framework for 5G AI candidates.Aydin, O.; Gebert, J.; Belschner, J.; Bazzi, J.; Weitkemper, P.; Kilinc, C.; Leonardo Da Silva, I.... (2016). D4.1 Draft air interface harmonization and user plane design. https://doi.org/10.13140/RG.2.2.24542.0288