21 research outputs found
Advances in Multi-User Scheduling and Turbo Equalization for Wireless MIMO Systems
Nach einer Einleitung behandelt Teil 2 Mehrbenutzer-Scheduling fĂŒr die
AbwÀrtsstrecke von drahtlosen MIMO Systemen mit einer Sendestation und
kanaladaptivem precoding: In jeder Zeit- oder Frequenzressource kann eine
andere Nutzergruppe gleichzeitig bedient werden, rÀumlich getrennt durch
unterschiedliche Antennengewichte. Nutzer mit korrelierten KanÀlen sollten
nicht gleichzeitig bedient werden, da dies die rÀumliche Trennbarkeit
erschwert. Die Summenrate einer Nutzermenge hÀngt von den Antennengewichten
ab, die wiederum von der Nutzerauswahl abhÀngen. Zur Entkopplung des
Problems schlÀgt diese Arbeit Metriken vor basierend auf einer geschÀtzten
Rate mit ZF precoding. Diese lÀsst sich mit Hilfe von wiederholten
orthogonalen Projektionen abschÀtzen, wodurch die Berechnung von
Antennengewichten beim Scheduling entfÀllt. Die RatenschÀtzung kann
basierend auf momentanen Kanalmessungen oder auf gemittelter Kanalkenntnis
berechnet werden und es können Datenraten- und Fairness-Kriterien
berĂŒcksichtig werden. Effiziente Suchalgorithmen werden vorgestellt, die
die gesamte Systembandbreite auf einmal bearbeiten können und zur
KomplexitĂ€tsreduktion die Lösung in Zeit- und Frequenz nachfĂŒhren können.
Teil 3 zeigt wie mehrere Sendestationen koordiniertes Scheduling und
kooperative Signalverarbeitung einsetzen können. Mittels orthogonalen
Projektionen ist es möglich, Inter-Site Interferenz zu schÀtzen, ohne
Antennengewichte berechnen zu mĂŒssen. 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 SchÀtzung der Summenrate eines
Systems ohne Koordination besprochen. Teil4 entwickelt Optimierungen fĂŒr
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
InterferenzunterdrĂŒckung 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 KanalschĂ€tzung im EXIT chart berĂŒcksichtigen kann.
In Computersimulationen werden alle Verfahren basierend auf
4G-Systemparametern ĂŒberprĂŒft.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 erhÀltlich:
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-
Novel feedback and signalling mechanisms for interference management and efficient modulation
In order to meet the ever-growing demand for mobile data, a number of different technologies
have been adopted by the fourth generation standardization bodies. These include multiple access
schemes such as spatial division multiple access (SDMA), and efficient modulation techniques
such as orthogonal frequency division multiplexing (OFDM)-based modulation. The
specific objectives of this theses are to develop an effective feedback method for interference
management in smart antenna SDMA systems and to design an efficient OFDM-based modulation
technique, where an additional dimension is added to the conventional two-dimensional
modulation techniques such as quadrature amplitude modulation (QAM).
In SDMA time division duplex (TDD) systems, where channel reciprocity is maintained, uplink
(UL) channel sounding method is considered as one of the most promising feedback methods
due to its bandwidth and delay efficiency. Conventional channel sounding (CCS) only conveys
the channel state information (CSI) of each active user to the base station (BS). Due to
the limitation in system performance because of co-channel interference (CCI) from adjacent
cells in interference-limited scenarios, CSI is only a suboptimal metric for multiuser spatial
multiplexing optimization. The first major contribution of this theses is a novel interference
feedback method proposed to provide the BS with implicit knowledge about the interference
level received by each mobile station (MS). More specifically, it is proposed to weight the
conventional channel sounding pilots by the level of the experienced interference at the userâs
side. Interference-weighted channel sounding (IWCS) acts as a spectrally efficient feedback
technique that provides the BS with implicit knowledge about CCI experienced by each MS,
and significantly improves the downlink (DL) sum capacity for both greedy and fair scheduling
policies. For the sake of completeness, a novel procedure is developed to make the IWCS pilots
usable for UL optimization. It is proposed to divide the optimization metric obtained from the
IWCS pilots by the interference experienced at the BSâs antennas. The resultant new metric, the
channel gain divided by the multiplication of DL and UL interference, provides link-protection
awareness and is used to optimize both UL and DL. Using maximum capacity scheduling criterion,
the link-protection aware metric results in a gain in the median system sum capacity of
26.7% and 12.5% in DL and UL respectively compared to the case when conventional channel
sounding techniques are used. Moreover, heuristic algorithm has been proposed in order to
facilitate a practical optimization and to reduce the computational complexity.
The second major contribution of this theses is an innovative transmission approach, referred
to as subcarrier-index modulation (SIM), which is proposed to be integrated with OFDM. The
key idea of SIM is to employ the subcarrier-index to convey information to the receiver. Furthermore,
a closed-form analytical bit error ratio (BER) of SIM OFDM in Rayleigh channel
is derived. Simulation results show BER performance gain of 4 dB over 4-QAM OFDM for
both coded and uncoded data without power saving policy. Alternatively, power saving policy
maintains an average gain of 1 dB while only using half OFDM symbol transmit power
Multi-user MIMO wireless communications
Mehrantennensysteme sind auf Grund der erhöhten Bandbreiteneffizienz und
Leistung eine SchlĂŒsselkomponente von Mobilfunksystemen der Zukunft. Diese
ermöglichen das gleichzeitige Senden von mehreren, rÀumlich getrennten
Datenströmen zu verschiedenen Nutzern. Die zentrale Fragestellung in der Praxis
ist, ob der ursprĂŒnglich vorausgesagte KapazitĂ€tsgewinn in realistischen
Szenarios erreicht wird und welche spezifischen Gewinne durch zusÀtzliche
Antennen und das Ausnutzen von Kanalkenntnis am Sender und EmpfÀnger 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 Ăberschneidung der
ZeilenrÀume minimiert, die durch die effektiven Kanalmatrizen verschiedener
Nutzer aufgespannt werden. Basierend auf mehreren parallelen Einzelnutzer-MIMO-
KanĂ€len wird im zweiten Schritt die Systemperformanz bezĂŒglich bestimmter
Kriterien optimiert.
Aus der gĂ€ngigen Literatur ist bereits bekannt, dass fĂŒr 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, nÀmlich
sukzessives MMSE und RBD. Bei der sukzessiven Verarbeitung mit einer
entsprechenden Anpassung der Sendeleistungsverteilung kann die volle DiversitÀt
des Systems ausgeschöpft werden. Die KapazitÀt nÀhert sich dabei der maximalen
Summenrate des Systems an. Bei gemeinsamer Verarbeitung der MIMO KanÀle wird
unabhÀngig vom Grad der Mehrnutzerinterferenz die maximale DiversitÀt erreicht.
Die genannten Techniken setzen entweder eine aktuelle oder eine ĂŒber einen
lĂ€ngeren Zeitraum gemittelte Kanalkenntnis voraus. Aus diesem Grund mĂŒssen die
Auswirkungen von Kanal-SchĂ€tzfehlern und EinflĂŒsse des Transceiver Front-Ends
auf die Verfahren nÀher untersucht werden.
FĂŒr eine weitergehende AbschĂ€tzung der Mehrantennensysteme muss die Performanz
des Gesamtsystems untersucht werden, da viele EinflĂŒsse auf die rĂ€umliche
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, wÀhrend der
Overhead durch Pilotsymbole und Steuersignale nur geringfĂŒgig 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
Dynamic User Grouping and Joint Resource Allocation with Multi-Cell Cooperation for Uplink Virtual MIMO Systems
This paper proposes a novel joint resource allocation algorithm combining dynamic user grouping, multi-cell cooperation and resource block (RB) allocation for single carrier-frequency division multiple access (SC-FDMA) uplink in multicell virtual MIMO systems. We first develop the dynamic multicell user grouping criteria using minimum mean square error (MMSE) equalization and adaptive modulation (AM) with bit error rate (BER) constraint. Then, we formulate and solve a new throughput maximization problem whose resource allocation includes cell selection, dynamic user grouping and RB pattern assignment. Furthermore, to reduce the computational complexity significantly, especially in the case of large numbers of users and RBs, we present an efficient iterative Hungarian algorithm based on user and resource partitions (IHA_URP) to solve the problem by decomposing the large scale problem into a series of small scale sub-problems, which can obtain close-to-optimal solution with much lower complexity. The simulation results show that our proposed joint resource allocation algorithm with dynamic multicell user grouping scheme achieves better system throughput with BER guarantee than fixed user grouping algorithm and other proposed schemes in the literature
Massive Access for Future Wireless Communication Systems
Multiple access technology played an important role in wireless communication
in the last decades: it increases the capacity of the channel and allows
different users to access the system simultaneously. However, the conventional
multiple access technology, as originally designed for current human-centric
wireless networks, is not scalable for future machine-centric wireless
networks.
Massive access (studied in the literature under such names as massive-device
multiple access, unsourced massive random access, massive connectivity, massive
machine-type communication, and many-access channels) exhibits a clean break
with current networks by potentially supporting millions of devices in each
cellular network. The tremendous growth in the number of connected devices
requires a fundamental rethinking of the conventional multiple access
technologies in favor of new schemes suited for massive random access. Among
the many new challenges arising in this setting, the most relevant are: the
fundamental limits of communication from a massive number of bursty devices
transmitting simultaneously with short packets, the design of low complexity
and energy-efficient massive access coding and communication schemes, efficient
methods for the detection of a relatively small number of active users among a
large number of potential user devices with sporadic transmission pattern, and
the integration of massive access with massive MIMO and other important
wireless communication technologies. This paper presents an overview of the
concept of massive access wireless communication and of the contemporary
research on this important topic.Comment: A short version has been accepted by IEEE Wireless Communication
Linear Transmit-Receive Strategies for Multi-user MIMO Wireless Communications
Die Notwendigkeit zur Unterdrueckung von Interferenzen auf der einen Seite
und zur Ausnutzung der durch Mehrfachzugriffsverfahren erzielbaren Gewinne
auf der anderen Seite rueckte die raeumlichen Mehrfachzugriffsverfahren
(Space Division Multiple Access, SDMA) in den Fokus der Forschung. Ein
Vertreter der raeumlichen Mehrfachzugriffsverfahren, die lineare
Vorkodierung, fand aufgrund steigender Anzahl an Nutzern und Antennen in
heutigen und zukuenftigen Mobilkommunikationssystemen besondere Beachtung,
da diese Verfahren das Design von Algorithmen zur Vorcodierung
vereinfachen. Aus diesem Grund leistet diese Dissertation einen Beitrag zur
Entwicklung linearer Sende- und Empfangstechniken fuer MIMO-Technologie mit
mehreren Nutzern. Zunaechst stellen wir ein Framework zur Approximation des
Datendurchsatzes in Broadcast-MIMO-Kanaelen mit mehreren Nutzern vor. In
diesem Framework nehmen wir das lineare Vorkodierverfahren regularisierte
Blockdiagonalisierung (RBD) an. Durch den Vergleich von Dirty Paper Coding
(DPC) und linearen Vorkodieralgorithmen (z.B. Zero Forcing (ZF) und
Blockdiagonalisierung (BD)) ist es uns moeglich, untere und obere Schranken
fuer den Unterschied bezueglich Datenraten und bezueglich Leistung zwischen
beiden anzugeben. Im Weiteren entwickeln wir einen Algorithmus fuer
koordiniertes Beamforming (Coordinated Beamforming, CBF), dessen Loesung
sich in geschlossener Form angeben laesst. Dieser CBF-Algorithmus basiert
auf der SeDJoCo-Transformation und loest bisher vorhandene Probleme im
Bereich CBF. Im Anschluss schlagen wir einen iterativen CBF-Algorithmus
namens FlexCoBF (flexible coordinated beamforming) fuer
MIMO-Broadcast-Kanaele mit mehreren Nutzern vor. Im Vergleich mit bis dato
existierenden iterativen CBF-Algorithmen kann als vielversprechendster
Vorteil die freie Wahl der linearen Sende- und Empfangsstrategie
herausgestellt werden. Das heisst, jede existierende Methode der linearen
Vorkodierung kann als Sendestrategie genutzt werden, waehrend die Strategie
zum Empfangsbeamforming frei aus MRC oder MMSE gewaehlt werden darf. Im
Hinblick auf Szenarien, in denen Mobilfunkzellen in Clustern
zusammengefasst sind, erweitern wir FlexCoBF noch weiter. Hier wurde das
Konzept der koordinierten Mehrpunktverbindung (Coordinated Multipoint
(CoMP) transmission) integriert. Zuletzt stellen wir drei Moeglichkeiten
vor, Kanalzustandsinformationen (Channel State Information, CSI) unter
verschiedenen Kanalumstaenden zu erlangen. Die Qualitaet der
Kanalzustandsinformationen hat einen starken Einfluss auf die Guete des
Uebertragungssystems. Die durch unsere neuen Algorithmen erzielten
Verbesserungen haben wir mittels numerischer Simulationen von Summenraten
und Bitfehlerraten belegt.In order to combat interference and exploit large multiplexing gains of the
multi-antenna systems, a particular interest in spatial division multiple
access (SDMA) techniques has emerged. Linear precoding techniques, as one
of the SDMA strategies, have obtained more attention due to the fact that
an increasing number of users and antennas involved into the existing and
future mobile communication systems requires a simplification of the
precoding design. Therefore, this thesis contributes to the design of
linear transmit and receive strategies for multi-user MIMO broadcast
channels in a single cell and clustered multiple cells. First, we present a
throughput approximation framework for multi-user MIMO broadcast channels
employing regularized block diagonalization (RBD) linear precoding.
Comparing dirty paper coding (DPC) and linear precoding algorithms (e.g.,
zero forcing (ZF) and block diagonalization (BD)), we further quantify
lower and upper bounds of the rate and power offset between them as a
function of the system parameters such as the number of users and antennas.
Next, we develop a novel closed-form coordinated beamforming (CBF)
algorithm (i.e., SeDJoCo based closed-form CBF) to solve the existing open
problem of CBF. Our new algorithm can support a MIMO system with an
arbitrary number of users and transmit antennas. Moreover, the application
of our new algorithm is not only for CBF, but also for blind source
separation (BSS), since the same mathematical model has been used in BSS
application.Then, we further propose a new iterative CBF algorithm (i.e.,
flexible coordinated beamforming (FlexCoBF)) for multi-user MIMO broadcast
channels. Compared to the existing iterative CBF algorithms, the most
promising advantage of our new algorithm is that it provides freedom in the
choice of the linear transmit and receive beamforming strategies, i.e., any
existing linear precoding method can be chosen as the transmit strategy and
the receive beamforming strategy can be flexibly chosen from MRC or MMSE
receivers. Considering clustered multiple cell scenarios, we extend the
FlexCoBF algorithm further and introduce the concept of the coordinated
multipoint (CoMP) transmission. Finally, we present three strategies for
channel state information (CSI) acquisition regarding various channel
conditions and channel estimation strategies. The CSI knowledge is required
at the base station in order to implement SDMA techniques. The quality of
the obtained CSI heavily affects the system performance. The performance
enhancement achieved by our new strategies has been demonstrated by
numerical simulation results in terms of the system sum rate and the bit
error rate
Resource allocation and optimization techniques in wireless relay networks
Relay techniques have the potential to enhance capacity and coverage of a wireless network. Due to rapidly increasing number of smart phone subscribers and high demand for data intensive multimedia applications, the
useful radio spectrum is becoming a scarce resource. For this reason, two way relay network and cognitive radio technologies are required for better utilization of radio spectrum. Compared to the conventional one way relay
network, both the uplink and the downlink can be served simultaneously using a two way relay network. Hence the effective bandwidth efficiency is considered to be one time slot per transmission. Cognitive networks are wireless networks that consist of different types of users, a primary user (PU, the primary license holder of a spectrum band) and secondary users (SU, cognitive radios that opportunistically access the PU spectrum). The
secondary users can access the spectrum of the licensed user provided they do not harmfully affect to the primary user. In this thesis, various resource
allocation and optimization techniques have been investigated for wireless relay and cognitive radio networks