Power Allocation in Wireless Relay Networks

This thesis is mainly concerned with power allocation issues in wireless relay networks where a single or multiple relays assist transmission from a single or multiple sources to a destination. First, a network model with a single source and multiple relays is considered, in which both cases of orthogonal and non--orthogonal relaying are investigated. For the case of orthogonal relaying, two power allocation schemes corresponding to two partial channel state information (CSI) assumptions are proposed. Given the lack of full and perfect CSI, appropriate signal processing at the relays and/or destination is also developed. The performance behavior of the system with power allocation between the source and the relays is also analyzed. For the case of non-orthogonal relaying, it is demonstrated that optimal power allocation is not sufficiently effective. Instead, a relay beamforming scheme is proposed. A comprehensive comparison between the orthogonal relaying with power allocation scheme and the non-orthogonal relaying with beamforming scheme is then carried out, which reveals several interesting conclusions with respect to both error performance and system throughput. In the second part of the thesis, a network model with multiple sources and a single relay is considered. The transmission model is applicable for uplink channels in cellular mobile systems in which multiple mobile terminals communicate with the base station with the help of a single relay station. Single-carrier frequency division multiple access (SC-FDMA) technique with frequency domain equalization is adopted in order to avoid the amplification of the multiple access interference at the relay. Minimizing the transmit power at the relay and optimizing the fairness among the sources in terms of throughput are the two objectives considered in implementing power allocation schemes. The problems are visualized as water-filling and water-discharging models and two optimal power allocation schemes are proposed, accordingly. Finally, the last part of the thesis is extended to a network model with multiple sources and multiple relays. The orthogonal multiple access technique is employed in order to avoid multiple access interference. Proposed is a joint optimal beamforming and power allocation scheme in which an alternative optimization technique is applied to deal with the non-convexity of the power allocation problem. Furthermore, recognizing the high complexity and large overhead information exchange when the number of sources and relays increases, a relay selection scheme is proposed. Since each source is supported by at most one relay, the feedback information from the destination to each relay can be significantly reduced. Using an equal power allocation scheme, relay selection is still an NP-hard combinatorial optimization problem. Nevertheless, the proposed sub-optimal scheme yields a comparable performance with a much lower computational complexity and can be well suited for practical systems

Cooperative Diversity in CDMA over Nakagami−m Fading Channels

Spatial diversity can be employed by sending copies of the transmitted signal using multiple antennas at the transmitter/receiver, as implemented in multiple-input multipleoutput (MIMO) systems. Spatial receive diversity has already been used in many applications with centralized systems where base station receivers are equipped with multiple antennas. However, due to the power constraints and the small size of the mobile terminal, it may not be feasible to deploy multiple transmit antennas. User cooperation diversity, a new form of space diversity, has been developed to address these limitations. Recently, user cooperative diversity has gained more attention as a less complex alternative to centralized MIMO wireless systems. It revealed the ability to improve wireless communications through reliable reception. One common network of the user cooperation diversity is the direct sequence code division multiple access (DS-CDMA) in which the Rayleigh fading channels are adopted and the orthogonality between users is assumed. The Rayleigh fading channels are unrealistic since they cannot represent the statistical characteristics of the complex indoor environments. On the other hand, Nakagami-m fading model is well known as a generalized distribution, where many fading environments can be modeled. It can be used to model fading conditions ranging from severe, light to no fading, by changing its fading parameter m. The bit-error-rate (BER) and outage probability of uplink cooperative DS-CDMA over Nakagami-m has not been addressed in the literature. Thus, in this thesis, the performance of both decode-and-forward (DF) and amplify-and-forward (AF) cooperative asynchronous DS-CDMA system over Nakagami-m fading channels is investigated. The Rake receiver is used to exploit the advantages of multipath propagation. Besides, multiuser detection (MUD) is used to mitigate the effect of multiple-access interference (MAI). We show that our proposed multi-user system achieves the full system diversity gain. The first part of the thesis introduces a new closed-form expression for the outage probability and the error probability of the DF cooperative DS-CDMA over asynchronous transmission over independent non-identical Nakagami-m fading channels. The underlying system employs MUD such as minimum mean square error (MMSE) and decorrelator detector (DD) to achieve the full diversity. The aforementioned closed-form expression is obtained through the moment generating function (MGF) for the total signal-to-noise ratio (SNR) at the base station where the cumulative density function (CDF) is obtained. Furthermore, we investigate the asymptotic behavior of the system at high SNR to calculate the achievable diversity gain. The results demonstrate that the system diversity gain is fulfilled when MUD is used to mitigate the effect of MAI. In the second part of the thesis, we study the performance of cooperative CDMA system using AF relaying over independent non-identical distribution (i.n.i) Nakagami-m fading channels. Using the MGF of the total SNR at the base station, we derive the outage probability of the system. This enables us to derive the asymptotic outage probability for any arbitrary value of the fading parameter m. The last part of the thesis investigates the optimum power allocation and optimum relay location in AF cooperative CDMA systems over i.n.i Nakagami-m fading channels. Moreover, we introduce the joint optimization of both power allocation and relay location under the transmit power constraint to minimize the outage probability of the system. The joint optimization of both power allocation and relay location is used to minimize the outage performance of the system, thereby achieving full diversity gain

High Capacity CDMA and Collaborative Techniques

The thesis investigates new approaches to increase the user capacity and improve the error performance of Code Division Multiple Access (CDMA) by employing adaptive interference cancellation and collaborative spreading and space diversity techniques. Collaborative Coding Multiple Access (CCMA) is also investigated as a separate technique and combined with CDMA. The advantages and shortcomings of CDMA and CCMA are analysed and new techniques for both the uplink and downlink are proposed and evaluated. Multiple access interference (MAI) problem in the uplink of CDMA is investigated first. The practical issues of multiuser detection (MUD) techniques are reviewed and a novel blind adaptive approach to interference cancellation (IC) is proposed. It exploits the constant modulus (CM) property of digital signals to blindly suppress interference during the despreading process and obtain amplitude estimation with minimum mean squared error for use in cancellation stages. Two new blind adaptive receiver designs employing successive and parallel interference cancellation architectures using the CM algorithm (CMA) referred to as ‘CMA-SIC’ and ‘BA-PIC’, respectively, are presented. These techniques have shown to offer near single user performance for large number of users. It is shown to increase the user capacity by approximately two fold compared with conventional IC receivers. The spectral efficiency analysis of the techniques based on output signal-to interference-and-noise ratio (SINR) also shows significant gain in data rate. Furthermore, an effective and low complexity blind adaptive subcarrier combining (BASC) technique using a simple gradient descent based algorithm is proposed for Multicarrier-CDMA. It suppresses MAI without any knowledge of channel amplitudes and allows large number of users compared with equal gain and maximum ratio combining techniques normally used in practice. New user collaborative schemes are proposed and analysed theoretically and by simulations in different channel conditions to achieve spatial diversity for uplink of CCMA and CDMA. First, a simple transmitter diversity and its equivalent user collaborative diversity techniques for CCMA are designed and analysed. Next, a new user collaborative scheme with successive interference cancellation for uplink of CDMA referred to as collaborative SIC (C-SIC) is investigated to reduce MAI and achieve improved diversity. To further improve the performance of C-SIC under high system loading conditions, Collaborative Blind Adaptive SIC (C-BASIC) scheme is proposed. It is shown to minimize the residual MAI, leading to improved user capacity and a more robust system. It is known that collaborative diversity schemes incur loss in throughput due to the need of orthogonal time/frequency slots for relaying source’s data. To address this problem, finally a novel near-unity-rate scheme also referred to as bandwidth efficient collaborative diversity (BECD) is proposed and evaluated for CDMA. Under this scheme, pairs of users share a single spreading sequence to exchange and forward their data employing a simple superposition or space-time encoding methods. At the receiver collaborative joint detection is performed to separate each paired users’ data. It is shown that the scheme can achieve full diversity gain at no extra bandwidth as inter-user channel SNR becomes high. A novel approach of ‘User Collaboration’ is introduced to increase the user capacity of CDMA for both the downlink and uplink. First, collaborative group spreading technique for the downlink of overloaded CDMA system is introduced. It allows the sharing of the same single spreading sequence for more than one user belonging to the same group. This technique is referred to as Collaborative Spreading CDMA downlink (CS-CDMA-DL). In this technique T-user collaborative coding is used for each group to form a composite codeword signal of the users and then a single orthogonal sequence is used for the group. At each user’s receiver, decoding of composite codeword is carried out to extract the user’s own information while maintaining a high SINR performance. To improve the bit error performance of CS-CDMA-DL in Rayleigh fading conditions, Collaborative Space-time Spreading (C-STS) technique is proposed by combining the collaborative coding multiple access and space-time coding principles. A new scheme for uplink of CDMA using the ‘User Collaboration’ approach, referred to as CS-CDMA-UL is presented next. When users’ channels are independent (uncorrelated), significantly higher user capacity can be achieved by grouping multiple users to share the same spreading sequence and performing MUD on per group basis followed by a low complexity ML decoding at the receiver. This approach has shown to support much higher number of users than the available sequences while also maintaining the low receiver complexity. For improved performance under highly correlated channel conditions, T-user collaborative coding is also investigated within the CS-CDMA-UL system

Low-complexity iterative soft detection for LDPC coded multi-relay channels

Next generation wireless communication applications require reliable transmission of data at high data rates and a guarantee of quality-of-service over wireless links. However, degradations inherent in wireless channels, such as multipath fading, shadowing, path loss, and noise lead to reduction in the communication capacity and range significantly. One way to combat these adverse limitations is to employ spatial diversity, which can be achieved, for example, by transmitting independent copies of the signal over relay nodes, resulting in improvements in the transmission rates, reliability, and the capacity of the channel under pre-mentioned detrimental effects. In addition to exploiting diversity, the capacity of the channel can be further increased by employing an error correction code such as low-density parity check (LDPC) codes and turbo codes, etc. Throughout this thesis, we consider LDPC coded full-duplex multi-relay channels using Estimate and Forward (EF) and Decode and Forward (DF) protocol. We focus on designing optimal and sub-optimal iterative soft detectors. Although the use of multirelaying improves the channel reliability, the performance of the system is degraded because of the interference caused by multiple received signals coming from all relay nodes. To reduce the effect of the interference, maximum a posteriori (MAP) detector can be employed. Unfortunately, the complexity of the MAP detector grows exponentially as the number of relays increases. In the literature, two computationally efficient sub-optimal detectors have been proposed based on Taylor expansion or Central Limit Theorem (CLT) assumption to alleviate this problem. However, we find out that the correlation between intrinsic and extrinsic information stemming from these suboptimal detectors is very high, and this correlation degrades the detector performance. To remedy that, in this thesis, we developed two new detectors: Soft Decorrelating Detection-Taylor (SODED-Taylor) and Soft Decorrelating Detection-CLT (SODEDCLT), which improves the performance of sub-optimal detectors about 0.8 dB - 1 dB

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

Transmit antenna selection and user selection in multiuser MIMO downlink systems

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University LondonMultiuser multiple input multiple output (MU-MIMO) systems play essential role in improving throughput performance and link reliability in wireless communications. This improvement can be achieved by exploiting the spatial domain and without the need of additional power and bandwidth. In this thesis, three main issues which are of importance to the data rate transmission have been investigated. Firstly, antenna selection in MU-MIMO downlink systems has been considered, where this technique can be e fficiently used to reduce the complexity and cost caused by radio frequency chains, associated with antennas, while keeping most of the diversity advantages of the system. We proposed a transmit antenna selection algorithm which can select an optimal set of antennas for transmission in descending order depending on the product of eigenvalues of users' effective channels. The capacity achieved by the proposed algorithm is about 99:6% of the capacity of the optimum search method, with much lower complexity. Secondly, user selection technology in MU-MIMO downlink systems has been studied. Based on the QR decomposition, we proposed a greedy suboptimal user selection algorithm which adopts the product of singular values of users' effective channels as a selection metric. The performance achieved by the proposed algorithm is identical to that of the capacity-based algorithm, with significant reduction in complexity. Finally, a proportional fairness scheduling algorithm for MU-MIMO downlink systems has been proposed. By utilising the upper triangular matrix obtained by applying the QRD on the users' effective channel matrices, two selection metrics have been proposed to achieve the scheduling process. The first metric is based on the maximum entry of the upper triangular matrix, while the second metric is designed using the ratio between the maximum and minimum entries of the triangular matrix multiplied by the product of singular values of effective channels. The two metric provide significant degrees of fairness. For each of these three issues, a different precoding method has been used in order to cancel the interuser interference before starting the selection process. This allows to investigate each precoding design separately and to evaluate the computational burden required for each design.Ministry of Higher Education-Ira

Cooperative Radio Communications for Green Smart Environments

The demand for mobile connectivity is continuously increasing, and by 2020 Mobile and Wireless Communications will serve not only very dense populations of mobile phones and nomadic computers, but also the expected multiplicity of devices and sensors located in machines, vehicles, health systems and city infrastructures. Future Mobile Networks are then faced with many new scenarios and use cases, which will load the networks with different data traffic patterns, in new or shared spectrum bands, creating new specific requirements. This book addresses both the techniques to model, analyse and optimise the radio links and transmission systems in such scenarios, together with the most advanced radio access, resource management and mobile networking technologies. This text summarises the work performed by more than 500 researchers from more than 120 institutions in Europe, America and Asia, from both academia and industries, within the framework of the COST IC1004 Action on "Cooperative Radio Communications for Green and Smart Environments". The book will have appeal to graduates and researchers in the Radio Communications area, and also to engineers working in the Wireless industry. Topics discussed in this book include: • Radio waves propagation phenomena in diverse urban, indoor, vehicular and body environments• Measurements, characterization, and modelling of radio channels beyond 4G networks• Key issues in Vehicle (V2X) communication• Wireless Body Area Networks, including specific Radio Channel Models for WBANs• Energy efficiency and resource management enhancements in Radio Access Networks• Definitions and models for the virtualised and cloud RAN architectures• Advances on feasible indoor localization and tracking techniques• Recent findings and innovations in antenna systems for communications• Physical Layer Network Coding for next generation wireless systems• Methods and techniques for MIMO Over the Air (OTA) testin