24 research outputs found

    Sum-Rate Maximization for Linearly Precoded Downlink Multiuser MISO Systems with Partial CSIT: A Rate-Splitting Approach

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    This paper considers the Sum-Rate (SR) maximization problem in downlink MU-MISO systems under imperfect Channel State Information at the Transmitter (CSIT). Contrary to existing works, we consider a rather unorthodox transmission scheme. In particular, the message intended to one of the users is split into two parts: a common part which can be recovered by all users, and a private part recovered by the corresponding user. On the other hand, the rest of users receive their information through private messages. This Rate-Splitting (RS) approach was shown to boost the achievable Degrees of Freedom (DoF) when CSIT errors decay with increased SNR. In this work, the RS strategy is married with linear precoder design and optimization techniques to achieve a maximized Ergodic SR (ESR) performance over the entire range of SNRs. Precoders are designed based on partial CSIT knowledge by solving a stochastic rate optimization problem using means of Sample Average Approximation (SAA) coupled with the Weighted Minimum Mean Square Error (WMMSE) approach. Numerical results show that in addition to the ESR gains, the benefits of RS also include relaxed CSIT quality requirements and enhanced achievable rate regions compared to conventional transmission with NoRS.Comment: accepted to IEEE Transactions on Communication

    Pilot Contamination Mitigation Techniques in Massive MIMO Systems: A Precoding Approach

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    A massive MIMO system comprises of base stations with a very large number of antennas serving a considerably smaller number of users and providing substantial gains in spectral and energy efficiency in comparison to conventional MIMO systems. However, these benefits are limited by pilot contamination which is caused by the use of training sequences for channel estimation. This negative effect has given rise to various research works on schemes to mitigate pilot contamination and among them are precoding techniques. This thesis reviews some of the precoding techniques that mitigate pilot contamination and studies the effect of pilot contamination on the performance of massive MIMO systems through simulations. It was found that pilot contamination leads to a severe degradation of the network performance. Furthermore, as the number of antennas at the base station increases, the effect of pilot contamination is more prominent on the probability of outage and the bit error rate but this is not the case for the average sum capacity. With the average sum capacity, the effect diminishes very gradually as the antenna array at the base station grows. However, overall, the presence of pilot contamination further lowers the network performance as the number of antennas at the base station increases.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

    On Linear Transmission Systems

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    This thesis is divided into two parts. Part I analyzes the information rate of single antenna, single carrier linear modulation systems. The information rate of a system is the maximum number of bits that can be transmitted during a channel usage, and is achieved by Gaussian symbols. It depends on the underlying pulse shape in a linear modulated signal and also the signaling rate, the rate at which the Gaussian symbols are transmitted. The object in Part I is to study the impact of both the signaling rate and the pulse shape on the information rate. Part II of the thesis is devoted to multiple antenna systems (MIMO), and more specifically to linear precoders for MIMO channels. Linear precoding is a practical scheme for improving the performance of a MIMO system, and has been studied intensively during the last four decades. In practical applications, the symbols to be transmitted are taken from a discrete alphabet, such as quadrature amplitude modulation (QAM), and it is of interest to find the optimal linear precoder for a certain performance measure of the MIMO channel. The design problem depends on the particular performance measure and the receiver structure. The main difficulty in finding the optimal precoders is the discrete nature of the problem, and mostly suboptimal solutions are proposed. The problem has been well investigated when linear receivers are employed, for which optimal precoders were found for many different performance measures. However, in the case of the optimal maximum likelihood (ML) receiver, only suboptimal constructions have been possible so far. Part II starts by proposing new novel, low complexity, suboptimal precoders, which provide a low bit error rate (BER) at the receiver. Later, an iterative optimization method is developed, which produces precoders improving upon the best known ones in the literature. The resulting precoders turn out to exhibit a certain structure, which is then analyzed and proved to be optimal for large alphabets

    Multiuser Optimal Transmit Beamforming: Performance Studies, Antennas Selection, A Genetic Algorithm Approach

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    RÉSUMÉ La formation de faisceaux est une technique très prometteuse utilisant un grand nombre d'antennes pour transmettre un signal vers un ou plusieurs utilisateurs. L'objectif est d'augmenter la puissance du signal chez l'utilisateur souhaité et de réduire la puissance d'interférence chez les utilisateurs non visés. Étant donné que la transmission de la formation de faisceaux augmente la puissance dans une direction spécifique, cela permet à un accès multiple par division spatiale de servir plusieurs utilisateurs simultanément. Cependant, le problème est de garder un équilibre entre maximiser la puissance du signal et minimiser la puissance d'interférence dans les systèmes multi-utilisateurs. Cette thèse décrit une structure simple qui fournit une base théorique pour un système de formation de faisceau optimal. Dans cette thèse, nous étudions les propriétés des systèmes linéaires et optimaux dans différents scénarios, tels que les rapports des signaux faibles et élevés au bruit, des nombres multiple d'antennes, le canal à évanouissement de Rayleigh et les retards multiples. Nous analysons les scénarios lorsque la formation de faisceaux linéaires fonctionnent comme une formation de faisceau optimale. Ensuite, nous proposons une méthode simple pour sélectionner le nombre minimum d'antennes suffisantes pour satisfaire aux exigences de qualité de service des utilisateurs. Lorsque le nombre d’antennes à la station de base est très grand, il ne sera peut-être pas nécessaire d’utiliser toutes les antennes pour desservir seulement quelques utilisateurs. Cette situation incite à choisir un nombre d’antennes limité. Cependant, le nombre choisi peut ne pas suffire à satisfaire les exigences de qualité de service des utilisateurs en raison de fortes interférences, de conditions de canal et du nombre d'utilisateurs. Pour résoudre ce problème NP-difficile, il faut faire une recherche exhaustive ou une recherche heuristique des méthodes itératives avec un coût de complexité informatique acceptable. Ainsi, nous proposons un cadre simple pour sélectionner un ensemble d'antennes suffisantes pour satisfaire les besoins de l'utilisateur. Enfin, nous proposons un algorithme génétique pour une formation de faisceaux optimale avec une complexité d'implémentation faible. Considérant l'algorithme de réduction de branche comme une référence, nous comparons la performance de l'algorithme proposé dans différents scénarios.---------- ABSTRACT Transmit beamforming is a very promising technique to transmit the signal from a large array of antennas to one or multiple users. The goal is to increase the signal power at the desired user and reduce the interference power at the non-intended users. Since transmit beamforming increases the power to a specific direction, it allows for space division multiple access to serve multiple users simultaneously. However, the problem is to keep the balance between maximizing the signal power and minimizing the interference power in multi-user systems. This thesis describes a simple structure that provides a theoretical foundation for optimal beamforming scheme. In this thesis, we study the properties of linear and optimal beamforming schemes in different scenarios such as low to high signal to noise ratio ranges, multiple number of antennas, simple Rayleigh fading channel, Rayleigh fading channel with Doppler effects. We analyze the scenarios when linear beamforming performs as an optimal beamforming. Next, we propose a simple method to select the minimum number of antennas that is enough to satisfy the quality of service requirements of the users. In case of massive number of antennas at base station, it may not be necessary to use all antennas to serve only few users. That situation motivates the selection of a set of limited number of antennas. However, the number of chosen antennas may not be enough to satisfy the quality of service requirements of the users due to strong interference, channel conditions and number of users. To solve this NP-hard problem, it requires an exhaustive search or heuristic search, iterative methods with a cost of computational complexity. Thus, we propose a simple framework to select a set of antennas that is enough to satisfy the user’s requirements. Finally, we propose a genetic algorithm for optimal beamforming with low implementation complexity. Considering the branch reduce and bound algorithm as a benchmark, we compare the performance of the proposed algorithm in different scenarios

    Wireless Physical Layer Security: Towards Practical Assumptions and Requirements

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    The current research on physical layer security is far from implementations in practical networks, arguably due to impractical assumptions in the literature and the limited applicability of physical layer security. Aiming to reduce the gap between theory and practice, this thesis focuses on wireless physical layer security towards practical assumptions and requirements. In the first half of the thesis, we reduce the dependence of physical layer security on impractical assumptions. The secrecy enhancements and analysis based on impractical assumptions cannot lead to any true guarantee of secrecy in practical networks. The current study of physical layer security was often based on the idealized assumption of perfect channel knowledge on both legitimate users and eavesdroppers. We study the impact of channel estimation errors on secure transmission designs. We investigate the practical scenarios where both the transmitter and the receiver have imperfect channel state information (CSI). Our results show how the optimal transmission design and the achievable throughput vary with the amount of knowledge on the eavesdropper's channel. Apart from the assumption of perfect CSI, the analysis of physical layer security often ideally assumed the number of eavesdropper antennas to be known. We develop an innovative approach to study secure communication systems without knowing the number of eavesdropper antennas by introducing the concept of spatial constraint into physical layer security. That is, the eavesdropper is assumed to have a limited spatial region to place (possibly an infinite number of) antennas. We show that a non-zero secrecy rate is achievable with the help of a friendly jammer, even if the eavesdropper places an infinite number of antennas in its spatial region. In the second half of the thesis, we improve the applicability of physical layer security. The current physical layer security techniques to achieve confidential broadcasting were limited to application in single-cell systems. The primary challenge to achieve confidential broadcasting in the multi-cell network is to deal with not only the inter-cell but also the intra-cell information leakage and interference. To tackle this challenge, we design linear precoders performing confidential broadcasting in multi-cell networks. We optimize the precoder designs to maximize the secrecy sum rate with based on the large-system analysis. Finally, we improve the applicability of physical layer security from a fundamental aspect. The analysis of physical layer security based on the existing secrecy metric was often not applicable in practical networks. We propose new metrics for evaluating the secrecy of transmissions over fading channels to address the practical limitations of using existing secrecy metrics for such evaluations. The first metric establishes a link between the concept of secrecy outage and the eavesdropper's ability to decode confidential messages. The second metric provides an error-probability-based secrecy metric which is often used for the practical implementation of secure wireless systems. The third metric characterizes how much or how fast the confidential information is leaked to the eavesdropper. We show that the proposed secrecy metrics enable one to appropriately design secure communication systems with different views on how secrecy is measured

    Analysis and design of physical-layer network coding for relay networks

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    Physical-layer network coding (PNC) is a technique to make use of interference in wireless transmissions to boost the system throughput. In a PNC employed relay network, the relay node directly recovers and transmits a linear combination of its received messages in the physical layer. It has been shown that PNC can achieve near information-capacity rates. PNC is a new information exchange scheme introduced in wireless transmission. In practice, transmitters and receivers need to be designed and optimized, to achieve fast and reliable information exchange. Thus, we would like to ask: How to design the PNC schemes to achieve fast and reliable information exchange? In this thesis, we address this question from the following works: Firstly, we studied channel-uncoded PNC in two-way relay fading channels with QPSK modulation. The computation error probability for computing network coded messages at the relay is derived. We then optimized the network coding functions at the relay to improve the error rate performance. We then worked on channel coded PNC. The codes we studied include classical binary code, modern codes, and lattice codes. We analyzed the distance spectra of channel-coded PNC schemes with classical binary codes, to derive upper bounds for error rates of computing network coded messages at the relay. We designed and optimized irregular repeat-accumulate coded PNC. We modified the conventional extrinsic information transfer chart in the optimization process to suit the superimposed signal received at the relay. We analyzed and designed Eisenstein integer based lattice coded PNC in multi-way relay fading channels, to derive error rate performance bounds of computing network coded messages. Finally we extended our work to multi-way relay channels. We proposed a opportunistic transmission scheme for a pair-wise transmission PNC in a single-input single-output multi-way relay channel, to improve the sum-rate at the relay. The error performance of computing network coded messages at the relay is also improved. We optimized the uplink/downlink channel usage for multi-input multi-output multi-way relay channels with PNC to maximize the degrees of freedom capacity. We also showed that the system sum-rate can be further improved by a proposed iterative optimization algorithm

    A Feasibility Test for Linear Interference Alignment in MIMO Channels with Constant Coefficients

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    In this paper, we consider the feasibility of linear interference alignment (IA) for multiple-input multiple-output (MIMO) channels with constant coefficients for any number of users, antennas and streams per user; and propose a polynomial-time test for this problem. Combining algebraic geometry techniques with differential topology ones, we first prove a result that generalizes those previously published on this topic. Specifically, we consider the input set (complex projective space of MIMO interference channels), the output set (precoder and decoder Grassmannians) and the solution set (channels, decoders and precoders satisfying the IA polynomial equations), not only as algebraic sets but also as smooth compact manifolds. Using this mathematical framework, we prove that the linear alignment problem is feasible when the algebraic dimension of the solution variety is larger than or equal to the dimension of the input space and the linear mapping between the tangent spaces of both smooth manifolds given by the first projection is generically surjective. If that mapping is not surjective, then the solution variety projects into the input space in a singular way and the projection is a zero-measure set. This result naturally yields a simple feasibility test, which amounts to checking the rank of a matrix. We also provide an exact arithmetic version of the test, which proves that testing the feasibility of IA for generic MIMO channels belongs to the bounded-error probabilistic polynomial (BPP) complexity class.Comment: To be published in IEEE Transactions on Information Theor

    Reduced Receivers for Faster-than-Nyquist Signaling and General Linear Channels

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    Fast and reliable data transmission together with high bandwidth efficiency are important design aspects in a modern digital communication system. Many different approaches exist but in this thesis bandwidth efficiency is obtained by increasing the data transmission rate with the faster-than-Nyquist (FTN) framework while keeping a fixed power spectral density (PSD). In FTN consecutive information carrying symbols can overlap in time and in that way introduce a controlled amount of intentional intersymbol interference (ISI). This technique was introduced already in 1975 by Mazo and has since then been extended in many directions. Since the ISI stemming from practical FTN signaling can be of significant duration, optimum detection with traditional methods is often prohibitively complex, and alternative equalization methods with acceptable complexity-performance tradeoffs are needed. The key objective of this thesis is therefore to design reduced-complexity receivers for FTN and general linear channels that achieve optimal or near-optimal performance. Although the performance of a detector can be measured by several means, this thesis is restricted to bit error rate (BER) and mutual information results. FTN signaling is applied in two ways: As a separate uncoded narrowband communication system or in a coded scenario consisting of a convolutional encoder, interleaver and the inner ISI mechanism in serial concatenation. Turbo equalization where soft information in the form of log likelihood ratios (LLRs) is exchanged between the equalizer and the decoder is a commonly used decoding technique for coded FTN signals. The first part of the thesis considers receivers and arising stability problems when working within the white noise constraint. New M-BCJR algorithms for turbo equalization are proposed and compared to reduced-trellis VA and BCJR benchmarks based on an offset label idea. By adding a third low-complexity M-BCJR recursion, LLR quality is improved for practical values of M. M here measures the reduced number of BCJR computations for each data symbol. An improvement of the minimum phase conversion that sharpens the focus of the ISI model energy is proposed. When combined with a delayed and slightly mismatched receiver, the decoding allows a smaller M without significant loss in BER. The second part analyzes the effect of the internal metric calculations on the performance of Forney- and Ungerboeck-based reduced-complexity equalizers of the M-algorithm type for both ISI and multiple-input multiple-output (MIMO) channels. Even though the final output of a full-complexity equalizer is identical for both models, the internal metric calculations are in general different. Hence, suboptimum methods need not produce the same final output. Additionally, new models working in between the two extremes are proposed and evaluated. Note that the choice of observation model does not impact the detection complexity as the underlying algorithm is unaltered. The last part of the thesis is devoted to a different complexity reducing approach. Optimal channel shortening detectors for linear channels are optimized from an information theoretical perspective. The achievable information rates of the shortened models as well as closed form expressions for all components of the optimal detector of the class are derived. The framework used in this thesis is more general than what has been previously used within the area
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