40 research outputs found
PERFORMANCE EVALUATION OF A MULTICARRIER MIMO SYSTEM BASED ON DFT-PRECODING AND SUBCARRIER MAPPING
The ever-increasing end user demands are instigating the development of innovative methods targeting not only data rate enhancement but additionally better service quality in each subsequent wireless communication standard. This quest to achieve higher data rates has compelled the next generation communication technologies to use multicarrier systems e.g. orthogonal frequency division multiplexing (OFDM), while also relying on the multiple-input multiple-output (MIMO) technology. This paper is focused on implementing a MIMO-OFDM system and on using various techniques to optimize it in terms of the bit-error rate performance. The test case considered is a system implementation constituting the enabling technologies for 4G and beyond communication systems. The bit-error rate optimizations considered are based on preceding the OFDM modulation step by Discrete Fourier Transform (DFT) while also considering various subcarrier mapping schemes. MATLAB-based simulation of a 2 × 2 MIMO-OFDM system exhibits a maximum of 2 to 5 orders of magnitude reduction in bit-error rate due to DFT-precoding and subcarrier mapping respectively at high signal-to-noise ratio values in various environments. A 2-3dBs reduction in peak-to-average power ratio due to DFT-precoding in different environments is also exhibited in the various simulations
A limited feedback scheme based on spatially correlated channels for coordinated multipoint systems
High spectral efficiency can be achieved in the downlink of multi-antenna coordinated multi-point systems provided that the multiuser interference is appropriately managed at the transmitter side. For this sake, downlink channel information needs to be sent back by the users, thus reducing the rate available at the uplink channel. The amount and type of feedback information required has been extensively studied and many limited feedback schemes have been proposed lately. A common pattern to all of them is that achieving low rates of feedback information is possible at the cost of increasing complexity at the user side and, sometimes, assuming that some statistics of the channel are known. In this article, we propose a simple and versatile limited feedback scheme that exploits the spatial correlation at each multi-antenna base station (BS) without requiring any previous statistical information of the channel and without adding significant computational complexity. It is based on the separate quantization of the channel impulse response modulus and phase and it shows better mean square error performance than the standard scheme based on quantization of real and imaginary parts. In order to evaluate the performance of the downlink regarding multiuser interference management, different precoding techniques at the BSs, such as zero-forcing (ZF), Tomlinson-Harashima precoding (THP) and lattice reduction Tomlinson- Harashima precoding (LRTHP), have been evaluated. Simulations results show that LRTHP and THP present a higher robustness than ZF precoding against channel quantization errors but at the cost of a higher complexity at the BS. Regarding sum-capacity and bit error rate performances, our versatile scheme achieves better results than the standard one in the medium and high SNR regime, that is, in the region where quantization errors are dominant against noise, for the same feedback cost measured in bits per user
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 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