85 research outputs found
MIMO channel capacity and configuration selection for switched parasitic antennas
MIMO systems offer a significant enhancement of data rate and channel capacity compared to traditional systems. But correlation degrades the system performance and puts a practical limit on the number of antennas that can be squeezed into portable wireless devices. Switched Parasitic Antennas (SPAs) is a possible solution especially where it is difficult to obtain enough signal decorrelation with conventional means. The covariance matrix represents the correlation present in the propagation channel and has significant impact on the MIMO channel capacity. The results of this work demonstrate a significant improvement in the MIMO channel capacity by using SPA with the knowledge of the covariance matrix for all pattern configurations. By employing the âWater-Pouring Algorithmâ (WPA) to modify the covariance matrix, the channel capacity is significantly improved as compared to traditional systems which just spread power equally among all the transmit antennas. A Condition Number (CN) is also proposed as a selection metric, to select the optimal pattern configuration for SPAs. CN is a channel quality indicator which represents the Eigen Value Spread (EVS) of the covariance matrix
Full-Duplex Cognitive Radio: A New Design Paradigm for Enhancing Spectrum Usage
With the rapid growth of demand for ever-increasing data rate, spectrum
resources have become more and more scarce. As a promising technique to
increase the efficiency of the spectrum utilization, cognitive radio (CR)
technique has the great potential to meet such a requirement by allowing
un-licensed users to coexist in licensed bands. In conventional CR systems, the
spectrum sensing is performed at the beginning of each time slot before the
data transmission. This unfortunately results in two major problems: 1)
transmission time reduction due to sensing, and 2) sensing accuracy impairment
due to data transmission. To tackle these problems, in this paper we present a
new design paradigm for future CR by exploring the full-duplex (FD) techniques
to achieve the simultaneous spectrum sensing and data transmission. With FD
radios equipped at the secondary users (SUs), SUs can simultaneously sense and
access the vacant spectrum, and thus, significantly improve sensing
performances and meanwhile increase data transmission efficiency. The aim of
this article is to transform the promising conceptual framework into the
practical wireless network design by addressing a diverse set of challenges
such as protocol design and theoretical analysis. Several application scenarios
with FD enabled CR are elaborated, and key open research directions and novel
algorithms in these systems are discussed
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
An Achievable Rate for the MIMO Individual Channel
We consider the problem of communicating over a multiple-input
multiple-output (MIMO) real valued channel for which no mathematical model is
specified, and achievable rates are given as a function of the channel input
and output sequences known a-posteriori. This paper extends previous results
regarding individual channels by presenting a rate function for the MIMO
individual channel, and showing its achievability in a fixed transmission rate
communication scenario.Comment: to be presented at ITW201
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-
Data retrieval in MIMO systems and the effects of correlation on the channel capacity
Multiple-input multiple-output (MIMO) antenna design as used in communication is today, easily the most important field in the wireless field; as capacities of data are increased based on the inherent capability of the technology, without an increase in spectrum bandwidth.This thesis analyses the ways through which data sent over some channel from a number of transmitters are recovered at the intended receivers; Maximum likelihood (ML) and Zero-forcing (ZF), are used for the data decoding; how effective these retrieval processes are and the imminent effects of correlation on the bit error rates as variants of signal to noise ratio, on the retrieved data capacities of the MIMO channels created, are all examined.This is simply very important as wireless systems continue to impact on lives globally.To drive the point home, the MIMO technology as it relates to this thesis is explicitly dissected to attempt a sound understanding of its modus operandi
Signal design for Multiple-Antenna Systems and Wireless Networks
This dissertation is concerned with the signal design problems for Multiple Input and Multiple Output (MIMO) antenna systems and wireless networks. Three related but distinct problems are considered.The first problem considered is the design of space time codes for MIMO systems in the case when neither the transmitter nor the receiver knows the channel. We present the theoretical concept of communicating over block fading channel using Layered Unitary Space Time Codes (LUSTC), where the input signal is formed as a product of a series of unitary matrices with corresponding dimensionality. We show the channel capacity using isotropically distributed (i.d.) input signaling and optimal decoding can be achieved by layered i.d. signaling scheme along with a low complexity successive decoding. The closed form layered channel capacity is obtained, which serves as a design guideline for practical LUSTC. In the design of LUSTC, a successive design method is applied to leverage the problem of optimizing over lots of parameters.The feedback of channel state information (CSI) to the transmitter in MIMO systems is known to increase the forward channel capacity. A suboptimal power allocation scheme for MIMO systems is then proposed for limited rate feedback of CSI. We find that the capacity loss of this simple scheme is rather small compared to the optimal water-filling solution. This knowledge is applied for the design of the feedback codebook. In the codebook design, a generalized Lloyd algorithm is employed, in which the computation of the centroid is formulated as an optimization problem and solved optimally. Numerical results show that the proposed codebook design outperforms the existing algorithms in the literature.While it is not feasible to deploy multiple antennas in a wireless node due to the space limitation, user cooperation is an alternative to increase performance of the wireless networks. To this end, a coded user cooperation scheme is considered in the dissertation, which is shown to be equivalent to a coding scheme with the encoding done in a distributive manner. Utilizing the coding theoretic bound and simulation results, we show that the coded user cooperation scheme has great advantage over the non-cooperative scheme
Energy Harvesting Wireless Communications: A Review of Recent Advances
This article summarizes recent contributions in the broad area of energy
harvesting wireless communications. In particular, we provide the current state
of the art for wireless networks composed of energy harvesting nodes, starting
from the information-theoretic performance limits to transmission scheduling
policies and resource allocation, medium access and networking issues. The
emerging related area of energy transfer for self-sustaining energy harvesting
wireless networks is considered in detail covering both energy cooperation
aspects and simultaneous energy and information transfer. Various potential
models with energy harvesting nodes at different network scales are reviewed as
well as models for energy consumption at the nodes.Comment: To appear in the IEEE Journal of Selected Areas in Communications
(Special Issue: Wireless Communications Powered by Energy Harvesting and
Wireless Energy Transfer
- âŠ