Decomposition by Successive Convex Approximation: A Unifying Approach for Linear Transceiver Design in Heterogeneous Networks

We study the downlink linear precoder design problem in a multi-cell dense heterogeneous network (HetNet). The problem is formulated as a general sum-utility maximization (SUM) problem, which includes as special cases many practical precoder design problems such as multi-cell coordinated linear precoding, full and partial per-cell coordinated multi-point transmission, zero-forcing precoding and joint BS clustering and beamforming/precoding. The SUM problem is difficult due to its non-convexity and the tight coupling of the users' precoders. In this paper we propose a novel convex approximation technique to approximate the original problem by a series of convex subproblems, each of which decomposes across all the cells. The convexity of the subproblems allows for efficient computation, while their decomposability leads to distributed implementation. {Our approach hinges upon the identification of certain key convexity properties of the sum-utility objective, which allows us to transform the problem into a form that can be solved using a popular algorithmic framework called BSUM (Block Successive Upper-Bound Minimization).} Simulation experiments show that the proposed framework is effective for solving interference management problems in large HetNet.Comment: Accepted by IEEE Transactions on Wireless Communicatio

Multi-user MIMO wireless communications

Mehrantennensysteme sind auf Grund der erhöhten Bandbreiteneffizienz und Leistung eine Schlüsselkomponente von Mobilfunksystemen der Zukunft. Diese ermöglichen das gleichzeitige Senden von mehreren, räumlich getrennten Datenströmen zu verschiedenen Nutzern. Die zentrale Fragestellung in der Praxis ist, ob der ursprünglich vorausgesagte Kapazitätsgewinn in realistischen Szenarios erreicht wird und welche spezifischen Gewinne durch zusätzliche Antennen und das Ausnutzen von Kanalkenntnis am Sender und Empfänger erzielt werden, was andererseits einen Zuwachs an Overhead oder nötiger Rechenleistung bedeutet. In dieser Arbeit werden neue lineare und nicht-lineare MU-MIMO Precoding- Verfahren vorgestellt. Der verfolgte Ansatz zur Bestimmung der Precoding- Matrizen ist allgemein anwendbar und die entstandenen Algorithmen können zur Optimierung von verschiedenen Kriterien mit beliebig vielen Antennen an der Mobilstation eingesetzt werden. Das wurde durch die Berechnung der Precoding- Matrix in zwei Schritten erreicht. Im ersten Schritt wird die Überschneidung der Zeilenräume minimiert, die durch die effektiven Kanalmatrizen verschiedener Nutzer aufgespannt werden. Basierend auf mehreren parallelen Einzelnutzer-MIMO- Kanälen wird im zweiten Schritt die Systemperformanz bezüglich bestimmter Kriterien optimiert. Aus der gängigen Literatur ist bereits bekannt, dass für Nutzer mit nur einer Antenne das MMSE Kriterium beim precoding optimal aber nicht bei Nutzern mit mehreren Antennen. Deshalb werden in dieser Arbeit zwei neue Mehrnutzer MIMO Strategien vorgestellt, die vom MSE Kriterium abgeleitet sind, nämlich sukzessives MMSE und RBD. Bei der sukzessiven Verarbeitung mit einer entsprechenden Anpassung der Sendeleistungsverteilung kann die volle Diversität des Systems ausgeschöpft werden. Die Kapazität nähert sich dabei der maximalen Summenrate des Systems an. Bei gemeinsamer Verarbeitung der MIMO Kanäle wird unabhängig vom Grad der Mehrnutzerinterferenz die maximale Diversität erreicht. Die genannten Techniken setzen entweder eine aktuelle oder eine über einen längeren Zeitraum gemittelte Kanalkenntnis voraus. Aus diesem Grund müssen die Auswirkungen von Kanal-Schätzfehlern und Einflüsse des Transceiver Front-Ends auf die Verfahren näher untersucht werden. Für eine weitergehende Abschätzung der Mehrantennensysteme muss die Performanz des Gesamtsystems untersucht werden, da viele Einflüsse auf die räumliche Signalverarbeitung bei Betrachtung eines einzelnen Links nicht erkennbar sind. Es wurde gezeigt, dass mit MIMO Precoding Strategien ein Vielfaches der Datenrate eines Systems mit nur einer Antenne erzielt werden kann, während der Overhead durch Pilotsymbole und Steuersignale nur geringfügig zunimmt.Multiple-input, multiple-output (MIMO) systems are a key component of future wireless communication systems, because of their promising improvement in terms of performance and bandwidth efficiency. An important research topic is the study of multi-user (MU) MIMO systems. Such systems have the potential to combine the high throughput achievable with MIMO processing with the benefits of space division multiple access (SDMA). The main question from a practical standpoint is whether the initially predicted capacity gains can be obtained in more realistic scenarios and what specific gains result from adding more antennas and overhead or computational power to obtain channel state information (CSI) at the transceivers. In this thesis we introduce new linear and non-linear MU MIMO processing techniques. The approach used for the design of the precoding matrix is general and the resulting algorithms can address several optimization criteria with an arbitrary number of antennas at the user terminals (UTs). This is achieved by designing the precoding matrices in two steps. In the first step we minimize the overlap of the row spaces spanned by the effective channel matrices of different users. In the next step, we optimize the system performance with respect to the specific optimization criterion assuming a set of parallel single-user MIMO channels. As it was previously reported in the literature, minimum mean-squared-error (MMSE) processing is optimum for single-antenna UTs. However, MMSE suffers from a performance loss when users are equipped with more than one antenna. The two MU MIMO processing techniques that result from the two different MSE criteria that are proposed in this thesis are successive MMSE and regularized block diagonalization. By iterating the closed form solution with appropriate power loading we are able to extract the full diversity in the system and empirically approach the maximum sum-rate capacity in case of high multi-user interference. Joint processing of MIMO channels yields maximum diversity regardless of the level of multi-user interference. As these techniques rely on the fact that there is either instantaneous or long- term CSI available at the base station to perform precoding and decoding, it was very important to investigate the influence of the transceiver front-end imperfections and channel estimation errors on their performance. For a comprehensive assessment of multi-antenna techniques, it is mandatory to consider the performance at system level, since many effects of spatial processing are not tractable at the link level. System level investigations have shown that MU MIMO precoding techniques provide several times higher data rates than single-input single-output systems with only slightly increased pilot and control overhead

An Overview of Massive MIMO Technology Components in METIS

As the standardization of full-dimension MIMO systems in the Third Generation Partnership Project progresses, the research community has started to explore the potential of very large arrays as an enabler technology for meeting the requirements of fifth generation systems. Indeed, in its final deliverable, the European 5G project METIS identifies massive MIMO as a key 5G enabler and proposes specific technology components that will allow the cost-efficient deployment of cellular systems taking advantage of hundreds of antennas at cellular base stations. These technology components include handling the inherent pilot-data resource allocation trade-off in a near optimal fashion, a novel random access scheme supporting a large number of users, coded channel state information for sparse channels in frequency-division duplexing systems, managing user grouping and multi-user beamforming, and a decentralized coordinated transceiver design. The aggregate effect of these components enables massive MIMO to contribute to the METIS objectives of delivering very high data rates and managing dense populations

Lights and Shadows: A Comprehensive Survey on Cooperative and Precoding Schemes to Overcome LOS Blockage and Interference in Indoor VLC

Visible light communications (VLC) have received significant attention as a way of moving part of the saturated indoor wireless traffic to the wide and unregulated visible optical spectrum. Nowadays, VLC are considered as a suitable technology, for several applications such as high-rate data transmission, supporting internet of things communications or positioning. The signal processing originally derived from radio-frequency (RF) systems such as cooperative or precoding schemes can be applied to VLC. However, its implementation is not straightforward. Furthermore, unlike RF transmission, VLC present a predominant line-of-sight link, although a weak non-LoS component may appear due to the reflection of the light on walls, floor, ceiling and nearby objects. Blocking effects may compromise the performance of the aforementioned transmission schemes. There exist several surveys in the literature focused on VLC and its applications, but the management of the shadowing and interference in VLC requires a comprehensive study. To fill this gap, this work introduces the implementation of cooperative and precoding schemes to VLC, while remarking their benefits and drawbacks for overcoming the shadowing effects. After that, the combination of both cooperative and precoding schemes is analyzed as a way of providing resilient VLC networks. Finally, we propose several open issues that the cooperative and precoding schemes must face in order to provide satisfactory VLC performance in indoor scenarios.This work has been supported partially by Spanish National Project TERESA-ADA(TEC2017-90093-C3-2-R) (MINECO/AEI/FEDER, UE), the research project GEOVEOLUZ-CM-UC3Mfunded by the call “Programa de apoyo a la realización de proyectos interdisciplinares de I+D parajóvenes investigadores de la Universidad Carlos III de Madrid 2019-2020” under the frame ofthe Convenio Plurianual Comunidad de Madrid-Universidad Carlos III de Madrid and projectMadrid Flight on Chip (Innovation Cooperative Projects Comunidad of Madrid - HUBS 2018/MadridFlightOnChip). Additionally, it has been supported partially by the Juan de la CiervaIncorporación grant IJC2019-040317-I and Juan de la Cierva Formación grant (FJC2019-039541-I/AEI/10.13039/501100011033)

Capacity Enhancement of Multiuser Wireless Communication System through Adaptive Non-Linear Pre coding

Multiuser multiple-input multiple-output (MIMO) nonlinear pre coding techniques face the issue of poor computational scalability of the size of the network. But by this nonlinear pre coding technique the interference is pre-cancelled automatically and also provides better capacity. So in order to reduce the computational burden in this paper, a definitive issue of MU-MIMO scalability is tackled through a non-linear adaptive optimum vector perturbation technique. Unlike the conventional (Vector Perturbation) VP methods, here a novel anterograde tracing is utilized which is usually recognized in the nervous system thus reducing complexity. The tracing of distance can be done through an iterative-optimization procedure. By this novel non-linear technique the capacity is improved to a greater extend which is explained practically. By means of this, the computational complexity is managed to be in the cubic order of the size of MUMIMO, and this mainly derives from the inverse of the channel matrix. The proposed signal processing system has been implemented in the working platform of MATLAB/SIMULINK. The simulation results of proposed communication system and comparison with existing systems shows the significance of the proposed work

Advances in Multi-User Scheduling and Turbo Equalization for Wireless MIMO Systems

Nach einer Einleitung behandelt Teil 2 Mehrbenutzer-Scheduling für die Abwärtsstrecke von drahtlosen MIMO Systemen mit einer Sendestation und kanaladaptivem precoding: In jeder Zeit- oder Frequenzressource kann eine andere Nutzergruppe gleichzeitig bedient werden, räumlich getrennt durch unterschiedliche Antennengewichte. Nutzer mit korrelierten Kanälen sollten nicht gleichzeitig bedient werden, da dies die räumliche Trennbarkeit erschwert. Die Summenrate einer Nutzermenge hängt von den Antennengewichten ab, die wiederum von der Nutzerauswahl abhängen. Zur Entkopplung des Problems schlägt diese Arbeit Metriken vor basierend auf einer geschätzten Rate mit ZF precoding. Diese lässt sich mit Hilfe von wiederholten orthogonalen Projektionen abschätzen, wodurch die Berechnung von Antennengewichten beim Scheduling entfällt. Die Ratenschätzung kann basierend auf momentanen Kanalmessungen oder auf gemittelter Kanalkenntnis berechnet werden und es können Datenraten- und Fairness-Kriterien berücksichtig werden. Effiziente Suchalgorithmen werden vorgestellt, die die gesamte Systembandbreite auf einmal bearbeiten können und zur Komplexitätsreduktion die Lösung in Zeit- und Frequenz nachführen können. Teil 3 zeigt wie mehrere Sendestationen koordiniertes Scheduling und kooperative Signalverarbeitung einsetzen können. Mittels orthogonalen Projektionen ist es möglich, Inter-Site Interferenz zu schätzen, ohne Antennengewichte berechnen zu müssen. Durch ein Konzept virtueller Nutzer kann der obige Scheduling-Ansatz auf mehrere Sendestationen und sogar Relays mit SDMA erweitert werden. Auf den benötigten Signalisierungsaufwand wird kurz eingegangen und eine Methode zur Schätzung der Summenrate eines Systems ohne Koordination besprochen. Teil4 entwickelt Optimierungen für Turbo Entzerrer. Diese Nutzen Signalkorrelation als Quelle von Redundanz. Trotzdem kann eine Kombination mit MIMO precoding sinnvoll sein, da bei Annahme realistischer Fehler in der Kanalkenntnis am Sender keine optimale Interferenzunterdrückung möglich ist. Mit Hilfe von EXIT Charts wird eine neuartige Methode zur adaptiven Nutzung von a-priori-Information zwischen Iterationen entwickelt, die die Konvergenz verbessert. Dabei wird gezeigt, wie man semi-blinde Kanalschätzung im EXIT chart berücksichtigen kann. In Computersimulationen werden alle Verfahren basierend auf 4G-Systemparametern überprüft.After an introduction, part 2 of this thesis deals with downlink multi-user scheduling for wireless MIMO systems with one transmitting station performing channel adaptive precoding:Different user subsets can be served in each time or frequency resource by separating them in space with different antenna weight vectors. Users with correlated channel matrices should not be served jointly since correlation impairs the spatial separability.The resulting sum rate for each user subset depends on the precoding weights, which in turn depend on the user subset. This thesis manages to decouple this problem by proposing a scheduling metric based on the rate with ZF precoding such as BD, written with the help of orthogonal projection matrices. It allows estimating rates without computing any antenna weights by using a repeated projection approximation.This rate estimate allows considering user rate requirements and fairness criteria and can work with either instantaneous or long term averaged channel knowledge.Search algorithms are presented to efficiently solve user grouping or selection problems jointly for the entire system bandwidth while being able to track the solution in time and frequency for complexity reduction. Part 3 shows how multiple transmitting stations can benefit from cooperative scheduling or joint signal processing. An orthogonal projection based estimate of the inter-site interference power, again without computing any antenna weights, and a virtual user concept extends the scheduling approach to cooperative base stations and finally included SDMA half-duplex relays in the scheduling.Signalling overhead is discussed and a method to estimate the sum rate without coordination. Part 4 presents optimizations for Turbo Equalizers. There, correlation between user signals can be exploited as a source of redundancy. Nevertheless a combination with transmit precoding which aims at reducing correlation can be beneficial when the channel knowledge at the transmitter contains a realistic error, leading to increased correlation. A novel method for adaptive re-use of a-priori information between is developed to increase convergence by tracking the iterations online with EXIT charts.A method is proposed to model semi-blind channel estimation updates in an EXIT chart. Computer simulations with 4G system parameters illustrate the methods using realistic channel models.Im Buchhandel erhältlich: Advances in Multi-User Scheduling and Turbo Equalization for Wireless MIMO Systems / Fuchs-Lautensack,Martin Ilmenau: ISLE, 2009,116 S. ISBN 978-3-938843-43-