36 research outputs found
MIMO Systems
In recent years, it was realized that the MIMO communication systems seems to be inevitable in accelerated evolution of high data rates applications due to their potential to dramatically increase the spectral efficiency and simultaneously sending individual information to the corresponding users in wireless systems. This book, intends to provide highlights of the current research topics in the field of MIMO system, to offer a snapshot of the recent advances and major issues faced today by the researchers in the MIMO related areas. The book is written by specialists working in universities and research centers all over the world to cover the fundamental principles and main advanced topics on high data rates wireless communications systems over MIMO channels. Moreover, the book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity
Interference Exploitation via Symbol-Level Precoding: Overview, State-of-the-Art and Future Directions
Interference is traditionally viewed as a performance limiting factor in wireless communication systems, which is to be minimized or mitigated. Nevertheless, a recent line of work has shown that by manipulating the interfering signals such that they add up constructively at the receiver side, known interference can be made beneficial and further improve the system performance in a variety of wireless scenarios, achieved by symbol-level precoding (SLP). This paper aims to provide a tutorial on interference exploitation techniques from the perspective of precoding design in a multi-antenna wireless communication system, by beginning with the classification of constructive interference (CI) and destructive interference (DI). The definition for CI is presented and the corresponding mathematical characterization is formulated for popular modulation types, based on which optimization-based precoding techniques are discussed. In addition, the extension of CI precoding to other application scenarios as well as for hardware efficiency is also described. Proof-of-concept testbeds are demonstrated for the potential practical implementation of CI precoding, and finally a list of open problems and practical challenges are presented to inspire and motivate further research directions in this area
A Tutorial on Interference Exploitation via Symbol-Level Precoding: Overview, State-of-the-Art and Future Directions
IEEE Interference is traditionally viewed as a performance limiting factor in wireless communication systems, which is to be minimized or mitigated. Nevertheless, a recent line of work has shown that by manipulating the interfering signals such that they add up constructively at the receiver side, known interference can be made beneficial and further improve the system performance in a variety of wireless scenarios, achieved by symbol-level precoding (SLP). This paper aims to provide a tutorial on interference exploitation techniques from the perspective of precoding design in a multi-antenna wireless communication system, by beginning with the classification of constructive interference (CI) and destructive interference (DI). The definition for CI is presented and the corresponding mathematical characterization is formulated for popular modulation types, based on which optimization-based precoding techniques are discussed. In addition, the extension of CI precoding to other application scenarios as well as for hardware efficiency is also described. Proof-of-concept testbeds are demonstrated for the potential practical implementation of CI precoding, and finally a list of open problems and practical challenges are presented to inspire and motivate further research directions in this area
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
Rate-splitting multiple access for non-terrestrial communication and sensing networks
Rate-splitting multiple access (RSMA) has emerged as a powerful and flexible
non-orthogonal transmission, multiple access (MA) and interference management
scheme for future wireless networks. This thesis is concerned with the application of
RSMA to non-terrestrial communication and sensing networks. Various scenarios
and algorithms are presented and evaluated.
First, we investigate a novel multigroup/multibeam multicast beamforming strategy
based on RSMA in both terrestrial multigroup multicast and multibeam satellite
systems with imperfect channel state information at the transmitter (CSIT). The
max-min fairness (MMF)-degree of freedom (DoF) of RSMA is derived and shown
to provide gains compared with the conventional strategy. The MMF beamforming
optimization problem is formulated and solved using the weighted minimum mean
square error (WMMSE) algorithm. Physical layer design and link-level simulations
are also investigated. RSMA is demonstrated to be very promising for multigroup
multicast and multibeam satellite systems taking into account CSIT uncertainty
and practical challenges in multibeam satellite systems.
Next, we extend the scope of research from multibeam satellite systems to satellite-
terrestrial integrated networks (STINs). Two RSMA-based STIN schemes are
investigated, namely the coordinated scheme relying on CSI sharing and the co-
operative scheme relying on CSI and data sharing. Joint beamforming algorithms
are proposed based on the successive convex approximation (SCA) approach to
optimize the beamforming to achieve MMF amongst all users. The effectiveness and
robustness of the proposed RSMA schemes for STINs are demonstrated.
Finally, we consider RSMA for a multi-antenna integrated sensing and communications (ISAC) system, which simultaneously serves multiple communication users
and estimates the parameters of a moving target. Simulation results demonstrate
that RSMA is beneficial to both terrestrial and multibeam satellite ISAC systems by
evaluating the trade-off between communication MMF rate and sensing Cramer-Rao
bound (CRB).Open Acces