Semi-blind CFO estimation and ICA based equalization for wireless communication systems

In this thesis, a number of semi-blind structures are proposed for Orthogonal Frequency Division Multiplexing (OFDM) based wireless communication systems, with Carrier Frequency Offset (CFO) estimation and Independent Component Analysis (ICA) based equalization. In the first contribution, a semi-blind non-redundant single-user Multiple-Input Multiple-Output (MIMO) OFDM system is proposed, with a precoding aided CFO estimation approach and an ICA based equalization structure. A number of reference data sequences are carefully designed and selected from a pool of orthogonal sequences, killing two birds with one stone. On the one hand, the precoding based CFO estimation is performed by minimizing the sum cross-correlations between the CFO compensated signals and the rest of the orthogonal sequences in the pool. On the other hand, the same reference data sequences enable the elimination of permutation and quadrant ambiguities in the ICA equalized signals. Simulation results show that the proposed semi-blind MIMO OFDM system can achieve a Bit Error Rate (BER) performance close to the ideal case with perfect Channel State Information (CSI) and no CFO. In the second contribution, a low-complexity semi-blind structure, with a multi-CFO estimation method and an ICA based equalization scheme, is proposed for multiuser Coordinated Multi-Point (CoMP) OFDM systems. A short pilot is carefully designed offline for each user and has a two-fold advantage. On the one hand, using the pilot structure, a complex multi-dimensional search for multiple CFOs is divided into a number of low-complexity mono-dimensional searches. On the other hand, the cross-correlation between the transmitted and received pilots is explored to allow the simultaneous elimination of permutation and quadrant ambiguities in the ICA equalized signals. Simulation results show that the proposed semi-blind CoMP OFDM system can provide a BER performance close to the ideal case with perfect CSI and no CFO. In the third contribution, a semi-blind structure is proposed for Carrier Aggregation (CA) based CoMP Orthogonal Frequency Division Multiple Access (OFDMA) systems, with an ICA based joint Inter-Carrier Interference (ICI) mitigation and equalization scheme. The CFO-induced ICI is mitigated implicitly via ICA based equalization, without introducing feedback overhead for CFO correction. The permutation and quadrant ambiguities in the ICA equalized signals can be eliminated by a small number of pilots. Simulation results show that with a low training overhead, the proposed semi-blind equalization scheme can provide a BER performance close to the ideal case with perfect CSI and no CFO

Timing and Carrier Synchronization in Wireless Communication Systems: A Survey and Classification of Research in the Last 5 Years

Timing and carrier synchronization is a fundamental requirement for any wireless communication system to work properly. Timing synchronization is the process by which a receiver node determines the correct instants of time at which to sample the incoming signal. Carrier synchronization is the process by which a receiver adapts the frequency and phase of its local carrier oscillator with those of the received signal. In this paper, we survey the literature over the last 5 years (2010–2014) and present a comprehensive literature review and classification of the recent research progress in achieving timing and carrier synchronization in single-input single-output (SISO), multiple-input multiple-output (MIMO), cooperative relaying, and multiuser/multicell interference networks. Considering both single-carrier and multi-carrier communication systems, we survey and categorize the timing and carrier synchronization techniques proposed for the different communication systems focusing on the system model assumptions for synchronization, the synchronization challenges, and the state-of-the-art synchronization solutions and their limitations. Finally, we envision some future research directions

Advanced Algebraic Concepts for Efficient Multi-Channel Signal Processing

Unsere moderne Gesellschaft ist Zeuge eines fundamentalen Wandels in der Art und Weise wie wir mit Technologie interagieren. Geräte werden zunehmend intelligenter - sie verfügen über mehr und mehr Rechenleistung und häufiger über eigene Kommunikationsschnittstellen. Das beginnt bei einfachen Haushaltsgeräten und reicht über Transportmittel bis zu großen überregionalen Systemen wie etwa dem Stromnetz. Die Erfassung, die Verarbeitung und der Austausch digitaler Informationen gewinnt daher immer mehr an Bedeutung. Die Tatsache, dass ein wachsender Anteil der Geräte heutzutage mobil und deshalb batteriebetrieben ist, begründet den Anspruch, digitale Signalverarbeitungsalgorithmen besonders effizient zu gestalten. Dies kommt auch dem Wunsch nach einer Echtzeitverarbeitung der großen anfallenden Datenmengen zugute. Die vorliegende Arbeit demonstriert Methoden zum Finden effizienter algebraischer Lösungen für eine Vielzahl von Anwendungen mehrkanaliger digitaler Signalverarbeitung. Solche Ansätze liefern nicht immer unbedingt die bestmögliche Lösung, kommen dieser jedoch häufig recht nahe und sind gleichzeitig bedeutend einfacher zu beschreiben und umzusetzen. Die einfache Beschreibungsform ermöglicht eine tiefgehende Analyse ihrer Leistungsfähigkeit, was für den Entwurf eines robusten und zuverlässigen Systems unabdingbar ist. Die Tatsache, dass sie nur gebräuchliche algebraische Hilfsmittel benötigen, erlaubt ihre direkte und zügige Umsetzung und den Test unter realen Bedingungen. Diese Grundidee wird anhand von drei verschiedenen Anwendungsgebieten demonstriert. Zunächst wird ein semi-algebraisches Framework zur Berechnung der kanonisch polyadischen (CP) Zerlegung mehrdimensionaler Signale vorgestellt. Dabei handelt es sich um ein sehr grundlegendes Werkzeug der multilinearen Algebra mit einem breiten Anwendungsspektrum von Mobilkommunikation über Chemie bis zur Bildverarbeitung. Verglichen mit existierenden iterativen Lösungsverfahren bietet das neue Framework die Möglichkeit, den Rechenaufwand und damit die Güte der erzielten Lösung zu steuern. Es ist außerdem weniger anfällig gegen eine schlechte Konditionierung der Ausgangsdaten. Das zweite Gebiet, das in der Arbeit besprochen wird, ist die unterraumbasierte hochauflösende Parameterschätzung für mehrdimensionale Signale, mit Anwendungsgebieten im RADAR, der Modellierung von Wellenausbreitung, oder bildgebenden Verfahren in der Medizin. Es wird gezeigt, dass sich derartige mehrdimensionale Signale mit Tensoren darstellen lassen. Dies erlaubt eine natürlichere Beschreibung und eine bessere Ausnutzung ihrer Struktur als das mit Matrizen möglich ist. Basierend auf dieser Idee entwickeln wir eine tensor-basierte Schätzung des Signalraums, welche genutzt werden kann um beliebige existierende Matrix-basierte Verfahren zu verbessern. Dies wird im Anschluss exemplarisch am Beispiel der ESPRIT-artigen Verfahren gezeigt, für die verbesserte Versionen vorgeschlagen werden, die die mehrdimensionale Struktur der Daten (Tensor-ESPRIT), nichzirkuläre Quellsymbole (NC ESPRIT), sowie beides gleichzeitig (NC Tensor-ESPRIT) ausnutzen. Um die endgültige Schätzgenauigkeit objektiv einschätzen zu können wird dann ein Framework für die analytische Beschreibung der Leistungsfähigkeit beliebiger ESPRIT-artiger Algorithmen diskutiert. Verglichen mit existierenden analytischen Ausdrücken ist unser Ansatz allgemeiner, da keine Annahmen über die statistische Verteilung von Nutzsignal und Rauschen benötigt werden und die Anzahl der zur Verfügung stehenden Schnappschüsse beliebig klein sein kann. Dies führt auf vereinfachte Ausdrücke für den mittleren quadratischen Schätzfehler, die Schlussfolgerungen über die Effizienz der Verfahren unter verschiedenen Bedingungen zulassen. Das dritte Anwendungsgebiet ist der bidirektionale Datenaustausch mit Hilfe von Relay-Stationen. Insbesondere liegt hier der Fokus auf Zwei-Wege-Relaying mit Hilfe von Amplify-and-Forward-Relays mit mehreren Antennen, da dieser Ansatz ein besonders gutes Kosten-Nutzen-Verhältnis verspricht. Es wird gezeigt, dass sich die nötige Kanalkenntnis mit einem einfachen algebraischen Tensor-basierten Schätzverfahren gewinnen lässt. Außerdem werden Verfahren zum Finden einer günstigen Relay-Verstärkungs-Strategie diskutiert. Bestehende Ansätze basieren entweder auf komplexen numerischen Optimierungsverfahren oder auf Ad-Hoc-Ansätzen die keine zufriedenstellende Bitfehlerrate oder Summenrate liefern. Deshalb schlagen wir algebraische Ansätze zum Finden der Relayverstärkungsmatrix vor, die von relevanten Systemmetriken inspiriert sind und doch einfach zu berechnen sind. Wir zeigen das algebraische ANOMAX-Verfahren zum Erreichen einer niedrigen Bitfehlerrate und seine Modifikation RR-ANOMAX zum Erreichen einer hohen Summenrate. Für den Spezialfall, in dem die Endgeräte nur eine Antenne verwenden, leiten wir eine semi-algebraische Lösung zum Finden der Summenraten-optimalen Strategie (RAGES) her. Anhand von numerischen Simulationen wird die Leistungsfähigkeit dieser Verfahren bezüglich Bitfehlerrate und erreichbarer Datenrate bewertet und ihre Effektivität gezeigt.Modern society is undergoing a fundamental change in the way we interact with technology. More and more devices are becoming "smart" by gaining advanced computation capabilities and communication interfaces, from household appliances over transportation systems to large-scale networks like the power grid. Recording, processing, and exchanging digital information is thus becoming increasingly important. As a growing share of devices is nowadays mobile and hence battery-powered, a particular interest in efficient digital signal processing techniques emerges. This thesis contributes to this goal by demonstrating methods for finding efficient algebraic solutions to various applications of multi-channel digital signal processing. These may not always result in the best possible system performance. However, they often come close while being significantly simpler to describe and to implement. The simpler description facilitates a thorough analysis of their performance which is crucial to design robust and reliable systems. The fact that they rely on standard algebraic methods only allows their rapid implementation and test under real-world conditions. We demonstrate this concept in three different application areas. First, we present a semi-algebraic framework to compute the Canonical Polyadic (CP) decompositions of multidimensional signals, a very fundamental tool in multilinear algebra with applications ranging from chemistry over communications to image compression. Compared to state-of-the art iterative solutions, our framework offers a flexible control of the complexity-accuracy trade-off and is less sensitive to badly conditioned data. The second application area is multidimensional subspace-based high-resolution parameter estimation with applications in RADAR, wave propagation modeling, or biomedical imaging. We demonstrate that multidimensional signals can be represented by tensors, providing a convenient description and allowing to exploit the multidimensional structure in a better way than using matrices only. Based on this idea, we introduce the tensor-based subspace estimate which can be applied to enhance existing matrix-based parameter estimation schemes significantly. We demonstrate the enhancements by choosing the family of ESPRIT-type algorithms as an example and introducing enhanced versions that exploit the multidimensional structure (Tensor-ESPRIT), non-circular source amplitudes (NC ESPRIT), and both jointly (NC Tensor-ESPRIT). To objectively judge the resulting estimation accuracy, we derive a framework for the analytical performance assessment of arbitrary ESPRIT-type algorithms by virtue of an asymptotical first order perturbation expansion. Our results are more general than existing analytical results since we do not need any assumptions about the distribution of the desired signal and the noise and we do not require the number of samples to be large. At the end, we obtain simplified expressions for the mean square estimation error that provide insights into efficiency of the methods under various conditions. The third application area is bidirectional relay-assisted communications. Due to its particularly low complexity and its efficient use of the radio resources we choose two-way relaying with a MIMO amplify and forward relay. We demonstrate that the required channel knowledge can be obtained by a simple algebraic tensor-based channel estimation scheme. We also discuss the design of the relay amplification matrix in such a setting. Existing approaches are either based on complicated numerical optimization procedures or on ad-hoc solutions that to not perform well in terms of the bit error rate or the sum-rate. Therefore, we propose algebraic solutions that are inspired by these performance metrics and therefore perform well while being easy to compute. For the MIMO case, we introduce the algebraic norm maximizing (ANOMAX) scheme, which achieves a very low bit error rate, and its extension Rank-Restored ANOMAX (RR-ANOMAX) that achieves a sum-rate close to an upper bound. Moreover, for the special case of single antenna terminals we derive the semi-algebraic RAGES scheme which finds the sum-rate optimal relay amplification matrix based on generalized eigenvectors. Numerical simulations evaluate the resulting system performance in terms of bit error rate and system sum rate which demonstrates the effectiveness of the proposed algebraic solutions

Energy E fficiency Oriented Full Duplex Wireless Communication Systems

Full-duplex (FD) transmission is a promising technique for fifth generation (5G) wireless communications, enabling significant spectral efficiency (SE) improvement over existing half-duplex (HD) systems. However, FD transmission consumes higher power than HD transmission, especially for millimetre wave band. Therefore, energy efficiency (EE) for FD systems is a critical yet inadequately addressed issue. This thesis addresses the critical EE challenges and demonstrates promising solutions for implementing FD systems, as detailed in the following contributions. In the first contribution, a comprehensive EE analysis of the FD and HD amplify-and-forward (AF) relay-assisted 60 GHz dual-hop indoor wireless systems is presented. An opportunistic relay mode selection scheme is developed, where FD relay with different self-interference (SIC) techniques or HD relay is opportunistically selected. Together with transmission power adaptation, EE is maximised with given channel gains. A counter-intuitive finding is shown that, with a relatively loose maximum transmission power constraint, FD relay with two-stage SIC is preferable to both FD relay with one-stage SIC and HD relay, resulting in a higher optimised EE. A full range of power consumption sources are considered to rationalise the analysis. The effects of imperfect SIC at relay, drain efficiency and static circuit power on EE are investigated. Simulation results verify the theoretical analysis. In the second contribution, EE oriented resource allocation for FD decode-of-forward (DF) relay-assisted 60 GHz multiuser systems is investigated. In contrast to the existing SE oriented designs, the proposed scheme maximises EE for FD relay systems under cross-layer constraints, addressing the typical problems at 60 GHz. A low-complexity EE-orientated resource allocation algorithm is proposed, by which the transmission power allocation, subcarrier allocation and throughput assignment are performed jointly across multiple users. Simulation results verify the analytical results and confirm that the FD relay systems with the proposed algorithm achieve a higher EE than the FD relay systems with SE oriented approaches, while offering a comparable SE. In addition, a much lower throughput outage probability is guaranteed by the proposed resource allocation algorithm, showing its robustness against channel estimation errors. In the third contribution, it is noticed that in wireless power transfer (WPT)-aided relay systems, the SE of the source-relay link plays a dominant role in the system SE due to limited transmission power at the WPT-aided relay. A novel asymmetric protocol for WPT-aided FD DF relay systems is proposed in multiuser scenario, where the time slot durations of the two hops are designed to be uneven, to enhance the degree of freedom and hence the system SE. A corresponding dynamic resource allocation algorithm is developed by jointly optimising the time slot durations, subcarriers and transmission power at the source and the relay. Simulation results con rm that, compared to the symmetric WPT-aided FD relay (Sym-WPT-FR) and the time-switching based WPT-aided FD relay (TS-WPT-FR) systems in the literature, the proposed asymmetric WPT-aided FD relay system achieves up to twice the SE and higher robustness against the relay's location and the number of users. In the final contribution, to strike the balance between high SE and low power consumption, a hybrid duplexing strategy is developed for distributed antennas (DAs) systems, where antennas are capable of working in hybrid FD, HD, and sleeping modes. To maximise the system EE with low complexity, activation/deactivation of transmit/receive chain is first performed, by a proposed channel-gain-based DA clustering algorithm, which highlights the characteristics of distributed deployment of antennas. Based on the DAs' con figuration, a novel distributed hybrid duplexing (D-HD)-based and EE oriented algorithm is proposed to further optimise the downlink beamformer and the uplink transmission power. To rationalise the system model, self-interference at DAs, co-channel interference from uplink users to downlink users, and multiuser interference in both uplink and downlink are taken into account. Simulation results confirm that the proposed system provides significant EE and SE enhancements over the colocated FD MIMO system, showing the advantages in alleviating high path loss as well as in cutting the carbon footprint. Compared to the sole-FD DA system, the proposed system shows much higher EE with marginal loss in SE. Also, the SIC operation in the proposed system is much more simplified compared to the two benchmarks

SMARAD - Centre of Excellence in Smart Radios and Wireless Research - Activity Report 2011 - 2013

Centre of Excellence in Smart Radios and Wireless Research (SMARAD), originally established with the name Smart and Novel Radios Research Unit, is aiming at world-class research and education in Future radio and antenna systems, Cognitive radio, Millimetre wave and THz techniques, Sensors, and Materials and energy, using its expertise in RF, microwave and millimeter wave engineering, in integrated circuit design for multi-standard radios as well as in wireless communications. SMARAD has the Centre of Excellence in Research status from the Academy of Finland since 2002 (2002-2007 and 2008-2013). Currently SMARAD consists of five research groups from three departments, namely the Department of Radio Science and Engineering, Department of Micro and Nanosciences, and Department of Signal Processing and Acoustics, all within the Aalto University School of Electrical Engineering. The total number of employees within the research unit is about 100 including 8 professors, about 30 senior scientists and about 40 graduate students and several undergraduate students working on their Master thesis. The relevance of SMARAD to the Finnish society is very high considering the high national income from exports of telecommunications and electronics products. The unit conducts basic research but at the same time maintains close co-operation with industry. Novel ideas are applied in design of new communication circuits and platforms, transmission techniques and antenna structures. SMARAD has a well-established network of co-operating partners in industry, research institutes and academia worldwide. It coordinates a few EU projects. The funding sources of SMARAD are diverse including the Academy of Finland, EU, ESA, Tekes, and Finnish and foreign telecommunications and semiconductor industry. As a by-product of this research SMARAD provides highest-level education and supervision to graduate students in the areas of radio engineering, circuit design and communications through Aalto University and Finnish graduate schools. During years 2011 – 2013, 18 doctor degrees were awarded to the students of SMARAD. In the same period, the SMARAD researchers published 197 refereed journal articles and 360 conference papers

Communication platform for inter-satellite links in distributed satellite systems

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

The drivers of Corporate Social Responsibility in the supply chain. A case study.

Purpose: The paper studies the way in which a SME integrates CSR into its corporate strategy, the practices it puts in place and how its CSR strategies reflect on its suppliers and customers relations. Methodology/Research limitations: A qualitative case study methodology is used. The use of a single case study limits the generalizing capacity of these findings. Findings: The entrepreneur’s ethical beliefs and value system play a fundamental role in shaping sustainable corporate strategy. Furthermore, the type of competitive strategy selected based on innovation, quality and responsibility clearly emerges both in terms of well defined management procedures and supply chain relations as a whole aimed at involving partners in the process of sustainable innovation. Originality/value: The paper presents a SME that has devised an original innovative business model. The study pivots on the issues of innovation and eco-sustainability in a context of drivers for CRS and business ethics. These values are considered fundamental at International level; the United Nations has declared 2011 the “International Year of Forestry”