137 research outputs found

    On the precoder design of flat fading MIMO systems equipped with MMSE receivers: a large system approach

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    This paper is devoted to the design of precoders maximizing the ergodic mutual information (EMI) of bi-correlated flat fading MIMO systems equiped with MMSE receivers. The channel state information and the second order statistics of the channel are assumed available at the receiver side and at the transmitter side respectively. As the direct maximization of the EMI needs the use of non attractive algorithms, it is proposed to optimize an approximation of the EMI, introduced recently, obtained when the number of transmit and receive antennas tt and rr converge to ∞\infty at the same rate. It is established that the relative error between the actual EMI and its approximation is a O(1t2)O(\frac{1}{t^{2}}) term. It is shown that the left singular eigenvectors of the optimum precoder coincide with the eigenvectors of the transmit covariance matrix, and its singular values are solution of a certain maximization problem. Numerical experiments show that the mutual information provided by this precoder is close from what is obtained by maximizing the true EMI, but that the algorithm maximizing the approximation is much less computationally intensive.Comment: Submitted to IEEE Transactions on Information Theor

    Multi-user MIMO wireless communications

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    Multi-user MIMO wireless communications

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    Mehrantennensysteme sind auf Grund der erhöhten Bandbreiteneffizienz und Leistung eine SchlĂŒsselkomponente von Mobilfunksystemen der Zukunft. Diese ermöglichen das gleichzeitige Senden von mehreren, rĂ€umlich 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 zusĂ€tzliche Antennen und das Ausnutzen von Kanalkenntnis am Sender und EmpfĂ€nger 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 ZeilenrĂ€ume 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, nĂ€mlich sukzessives MMSE und RBD. Bei der sukzessiven Verarbeitung mit einer entsprechenden Anpassung der Sendeleistungsverteilung kann die volle DiversitĂ€t des Systems ausgeschöpft werden. Die KapazitĂ€t nĂ€hert sich dabei der maximalen Summenrate des Systems an. Bei gemeinsamer Verarbeitung der MIMO KanĂ€le wird unabhĂ€ngig vom Grad der Mehrnutzerinterferenz die maximale DiversitĂ€t 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 nĂ€her 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, wĂ€hrend 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

    On MU-MIMO Precoding Techniques for WiMAX

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    Large-System Analysis of Correlated MIMO Multiple Access Channels with Arbitrary Signaling in the Presence of Interference

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    Presence of multiple antennas on both sides of a communication channel promises significant improvements in system throughput and power efficiency. In effect, a new clas s of large multiple-input multiple-output (MIMO) communication systems has recently emerged and attracted both scientific and industrial attention. To analyze these systems in realistic scenarios, one has to include such aspects as co-channel interference, multiple access and spatial correlation. In this paper, we study the properties of correlated MIMO multiple-access channels in the presence of external interference. Using the replica method from statistical physics, we derive the ergodic sum-rate of the communication for arbitrary signal constellations when the numbers of antennas at both ends of the channel grow large. Based on these asymptotic expressions, we also address the problem of sum-rate maximization using statistical channel information and linear precoding. The numerical results demonstrate that when the interfering terminals use discrete constellations, the resulting interference becomes easier to handle compared to Gaussian signals. Thus, it may be possible to accommodate more interfering transmitter-receiver pairs within the same area as compare d to the case of Gaussian signals. In addition, we demonstrate numerically for the Gaussian and QPSK signaling schemes that it is possible to design precoder matrices that significantly improve the achievable rates at low-to-mid range of signal-to-noise ratios when compared to isotropic precoding

    Interference Alignment and Cancellation in Wireless Communication Systems

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    The Shannon capacity of wireless networks has a fundamental importance for network information theory. This area has recently seen remarkable progress on a variety of problems including the capacity of interference networks, X networks, cellular networks, cooperative communication networks and cognitive radio networks. While each communication scenario has its own characteristics, a common reason of these recent developments is the new idea of interference alignment. The idea of interference alignment is to consolidate the interference into smaller dimensions of signal space at each receiver and use the remaining dimensions to transmit the desired signals without any interference. However, perfect alignment of interference requires certain assumptions, such as perfect channel state information at transmitter and receiver, perfect synchronization and feedback. Today’s wireless communication systems, on the other and, do not encounter such ideal conditions. In this thesis, we cover a breadth of topics of interference alignment and cancellation schemes in wireless communication systems such as multihop relay networks, multicell networks as well as cooperation and optimisation in such systems. Our main contributions in this thesis can be summarised as follows: ‱ We derive analytical expressions for an interference alignment scheme in a multihop relay network with imperfect channel state information, and investigate the impact of interference on such systems where interference could accumulate due to the misalignment at each hop. ‱ We also address the dimensionality problem in larger wireless communication systems such as multi-cellular systems. We propose precoding schemes based on maximising signal power over interference and noise. We show that these precoding vectors would dramatically improve the rates for multi-user cellular networks in both uplink and downlink, without requiring an excessive number of dimensions. Furthermore, we investigate how to improve the receivers which can mitigate interference more efficiently. ‱ We also propose partial cooperation in an interference alignment and cancellation scheme. This enables us to assess the merits of varying mixture of cooperative and non-cooperative users and the gains achievable while reducing the overhead of channel estimation. In addition to this, we analytically derive expressions for the additional interference caused by imperfect channel estimation in such cooperative systems. We also show the impact of imperfect channel estimation on cooperation gains. ‱ Furthermore, we propose jointly optimisation of interference alignment and cancellation for multi-user multi-cellular networks in both uplink and downlink. We find the optimum set of transceivers which minimise the mean square error at each base station. We demonstrate that optimised transceivers can outperform existing interference alignment and cancellation schemes. ‱ Finally, we consider power adaptation and user selection schemes. The simulation results indicate that user selection and power adaptation techniques based on estimated rates can improve the overall system performance significantly
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