Exploiting statistical and outdated CSI in multiuser downlink transmission

In this paper, we propose a multiuser downlink transmission scheme, which exploits both the statistical and outdated channel state information (CSI) at the transmitter. The proposed scheme extends the outdated CSI-aided scheme, first introduced by Maddah-Ali and Tse in [1] (denoted as MAT), by sending symbols demanded by a user along its statistical eigenmodes, instead of directly sending the symbols through separate antennas, and we refer to it as statistical eigenmode-MAT (SE-MAT). Considering zero-forcing receiver, we explicitly prove that the proposed SE-MAT scheme can achieve a higher ergodic sum-rate compared to the original MAT scheme, under different correlation conditions. Moreover, a user selection method which selects statistically orthogonal users for the SE-MAT transmission is proposed to further improve the system performance

Multiple Access in Aerial Networks: From Orthogonal and Non-Orthogonal to Rate-Splitting

Recently, interest on the utilization of unmanned aerial vehicles (UAVs) has aroused. Specifically, UAVs can be used in cellular networks as aerial users for delivery, surveillance, rescue search, or as an aerial base station (aBS) for communication with ground users in remote uncovered areas or in dense environments requiring prompt high capacity. Aiming to satisfy the high requirements of wireless aerial networks, several multiple access techniques have been investigated. In particular, space-division multiple access(SDMA) and power-domain non-orthogonal multiple access (NOMA) present promising multiplexing gains for aerial downlink and uplink. Nevertheless, these gains are limited as they depend on the conditions of the environment. Hence, a generalized scheme has been recently proposed, called rate-splitting multiple access (RSMA), which is capable of achieving better spectral efficiency gains compared to SDMA and NOMA. In this paper, we present a comprehensive survey of key multiple access technologies adopted for aerial networks, where aBSs are deployed to serve ground users. Since there have been only sporadic results reported on the use of RSMA in aerial systems, we aim to extend the discussion on this topic by modelling and analyzing the weighted sum-rate performance of a two-user downlink network served by an RSMA-based aBS. Finally, related open issues and future research directions are exposed.Comment: 16 pages, 6 figures, submitted to IEEE Journa

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

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-

Multiple Access Techniques for Next Generation Wireless: Recent Advances and Future Perspectives

The advances in multiple access techniques has been one of the key drivers in moving from one cellular generation to another. Starting from the first generation, several multiple access techniques have been explored in different generations and various emerging multiplexing/multiple access techniques are being investigated for the next generation of cellular networks. In this context, this paper first provides a detailed review on the existing Space Division Multiple Access (SDMA) related works. Subsequently, it highlights the main features and the drawbacks of various existing and emerging multiplexing/multiple access techniques. Finally, we propose a novel concept of clustered orthogonal signature division multiple access for the next generation of cellular networks. The proposed concept envisions to employ joint antenna coding in order to enhance the orthogonality of SDMA beams with the objective of enhancing the spectral efficiency of future cellular networks

Spectral Efficiency and Energy Efficiency Tradeoff in Massive MIMO Downlink Transmission with Statistical CSIT

As a key technology for future wireless networks, massive multiple-input multiple-output (MIMO) can significantly improve the energy efficiency (EE) and spectral efficiency (SE), and the performance is highly dependant on the degree of the available channel state information (CSI). While most existing works on massive MIMO focused on the case where the instantaneous CSI at the transmitter (CSIT) is available, it is usually not an easy task to obtain precise instantaneous CSIT. In this paper, we investigate EE-SE tradeoff in single-cell massive MIMO downlink transmission with statistical CSIT. To this end, we aim to optimize the system resource efficiency (RE), which is capable of striking an EE-SE balance. We first figure out a closed-form solution for the eigenvectors of the optimal transmit covariance matrices of different user terminals, which indicates that beam domain is in favor of performing RE optimal transmission in massive MIMO downlink. Based on this insight, the RE optimization precoding design is reduced to a real-valued power allocation problem. Exploiting the techniques of sequential optimization and random matrix theory, we further propose a low-complexity suboptimal two-layer water-filling-structured power allocation algorithm. Numerical results illustrate the effectiveness and near-optimal performance of the proposed statistical CSI aided RE optimization approach.Comment: Typos corrected. 14 pages, 7 figures. Accepted for publication on IEEE Transactions on Signal Processing. arXiv admin note: text overlap with arXiv:2002.0488

Rate-Splitting Multiple Access for Uplink Massive MIMO With Electromagnetic Exposure Constraints

Over the past few years, the prevalence of wireless devices has become one of the essential sources of electromagnetic (EM) radiation to the public. Facing with the swift development of wireless communications, people are skeptical about the risks of long-term exposure to EM radiation. As EM exposure is required to be restricted at user terminals, it is inefficient to blindly decrease the transmit power, which leads to limited spectral efficiency and energy efficiency (EE). Recently, rate-splitting multiple access (RSMA) has been proposed as an effective way to provide higher wireless transmission performance, which is a promising technology for future wireless communications. To this end, we propose using RSMA to increase the EE of massive MIMO uplink while limiting the EM exposure of users. In particularly, we investigate the optimization of the transmit covariance matrices and decoding order using statistical channel state information (CSI). The problem is formulated as non-convex mixed integer program, which is in general difficult to handle. We first propose a modified water-filling scheme to obtain the transmit covariance matrices with fixed decoding order. Then, a greedy approach is proposed to obtain the decoding permutation. Numerical results verify the effectiveness of the proposed EM exposure-aware EE maximization scheme for uplink RSMA.Comment: to appear in IEEE Journal on Selected Areas in Communication