Optimal Precoder Designs for Sum-utility Maximization in SWIPT-enabled Multi-user MIMO Cognitive Radio Networks

In this paper, we propose a generalized framework that combines the cognitive radio (CR) techniques for spectrum sharing and the simultaneous wireless information and power transfer (SWIPT) for energy harvesting (EH) in the conventional multi-user MIMO (MuMIMO) channels, which leads to an MuMIMO-CR-SWIPT network. In this system, we have one secondary base-station (S-BS) that supports multiple secondary information decoding (S-ID) and secondary EH (S-EH) users simultaneously under the condition that interference power that affects the primary ID (P-ID) receivers should stay below a certain threshold. The goal of the paper is to develop a generalized precoder design that maximizes the sum-utility cost function under the transmit power constraint at the S-BS, and the EH constraint at each S-EH user, and the interference power constraint at each P-ID user. Therefore, the previous studies for the CR and SWIPT systems are casted as particular solutions of the proposed framework. The problem is inherently non-convex and even the weighted minimum mean squared error (WMMSE) transformation does not resolve the non-convexity of the original problem. To tackle the problem, we find a solution from the dual optimization via sub-gradient ellipsoid method based on the observation that the WMMSE transformation raises zero-duality gap between the primal and the dual problems. We also propose a simplified algorithm for the case of a single S-ID user, which is shown to achieve the global optimum. Finally, we demonstrate the optimality and efficiency of the proposed algorithms through numerical simulation results.Comment: 12pages, 9 figures, submitted to IEEE Systems Journa

Capacity Enhancement of Multiuser Wireless Communication System through Adaptive Non-Linear Pre coding

Multiuser multiple-input multiple-output (MIMO) nonlinear pre coding techniques face the issue of poor computational scalability of the size of the network. But by this nonlinear pre coding technique the interference is pre-cancelled automatically and also provides better capacity. So in order to reduce the computational burden in this paper, a definitive issue of MU-MIMO scalability is tackled through a non-linear adaptive optimum vector perturbation technique. Unlike the conventional (Vector Perturbation) VP methods, here a novel anterograde tracing is utilized which is usually recognized in the nervous system thus reducing complexity. The tracing of distance can be done through an iterative-optimization procedure. By this novel non-linear technique the capacity is improved to a greater extend which is explained practically. By means of this, the computational complexity is managed to be in the cubic order of the size of MUMIMO, and this mainly derives from the inverse of the channel matrix. The proposed signal processing system has been implemented in the working platform of MATLAB/SIMULINK. The simulation results of proposed communication system and comparison with existing systems shows the significance of the proposed work

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

Recent Advances in Acquiring Channel State Information in Cellular MIMO Systems

In cellular multi-user multiple input multiple output (MU-MIMO) systems the quality of the available channel state information (CSI) has a large impact on the system performance. Specifically, reliable CSI at the transmitter is required to determine the appropriate modulation and coding scheme, transmit power and the precoder vector, while CSI at the receiver is needed to decode the received data symbols. Therefore, cellular MUMIMO systems employ predefined pilot sequences and configure associated time, frequency, code and power resources to facilitate the acquisition of high quality CSI for data transmission and reception. Although the trade-off between the resources used user data transmission has been known for long, the near-optimal configuration of the vailable system resources for pilot and data transmission is a topic of current research efforts. Indeed, since the fifth generation of cellular systems utilizes heterogeneous networks in which base stations are equipped with a large number of transmit and receive antennas, the appropriate configuration of pilot-data resources becomes a critical design aspect. In this article, we review recent advances in system design approaches that are designed for the acquisition of CSI and discuss some of the recent results that help to dimension the pilot and data resources specifically in cellular MU-MIMO systems

Interference Mitigation Framework for Cellular Mobile Radio Networks

For today's cellular mobile communication networks, the needed capacity is hard to realize without much more of (expensive) bandwidth. Thus new standards like LTE were developed. LTE advanced is in discussion as the successor of LTE and cooperative multipoint transmission (CoMP) is one of the hot topics to increase the system's capacity. System simulations often show only weak gains of the signal-to-interference ratio due to high interference from noncooperating cells in the downlink. This paper presents an interference mitigation framework to overcome the hardest issue, that is, the low penetration rate of mobile stations that can be served from a cluster composed of their strongest cells in the network. The results obtained from simulation tools are discussed with values resulting from testbed on the TU Dresden. They show that the theoretical ideas can be transferred into gains on real systems

Random Beamforming for Multi-cell Multiple-Input Multi-Output (MIMO) Systems

Ph.DDOCTOR OF PHILOSOPH

Transmit antenna selection and user selection in multiuser MIMO downlink systems

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University LondonMultiuser multiple input multiple output (MU-MIMO) systems play essential role in improving throughput performance and link reliability in wireless communications. This improvement can be achieved by exploiting the spatial domain and without the need of additional power and bandwidth. In this thesis, three main issues which are of importance to the data rate transmission have been investigated. Firstly, antenna selection in MU-MIMO downlink systems has been considered, where this technique can be e fficiently used to reduce the complexity and cost caused by radio frequency chains, associated with antennas, while keeping most of the diversity advantages of the system. We proposed a transmit antenna selection algorithm which can select an optimal set of antennas for transmission in descending order depending on the product of eigenvalues of users' effective channels. The capacity achieved by the proposed algorithm is about 99:6% of the capacity of the optimum search method, with much lower complexity. Secondly, user selection technology in MU-MIMO downlink systems has been studied. Based on the QR decomposition, we proposed a greedy suboptimal user selection algorithm which adopts the product of singular values of users' effective channels as a selection metric. The performance achieved by the proposed algorithm is identical to that of the capacity-based algorithm, with significant reduction in complexity. Finally, a proportional fairness scheduling algorithm for MU-MIMO downlink systems has been proposed. By utilising the upper triangular matrix obtained by applying the QRD on the users' effective channel matrices, two selection metrics have been proposed to achieve the scheduling process. The first metric is based on the maximum entry of the upper triangular matrix, while the second metric is designed using the ratio between the maximum and minimum entries of the triangular matrix multiplied by the product of singular values of effective channels. The two metric provide significant degrees of fairness. For each of these three issues, a different precoding method has been used in order to cancel the interuser interference before starting the selection process. This allows to investigate each precoding design separately and to evaluate the computational burden required for each design.Ministry of Higher Education-Ira

Multibeam Joint Processing in Satellite Communications

Cooperative Satellite Communications (SatComs) involve multi-antenna satellites enabled for the joint transmission and reception of signals. This joint processing of baseband signals is realized amongst the distinct but interconnected antennas. Advanced signal processing techniques –namely precoding and Multiuser Detection (MUD)– are herein examined in the multibeam satellite context. The aim of this thesis is to establish the prominence of such methods in the next generation of broadband satellite networks. To this end, two approaches are followed. On one hand, the performance of the well established and theoretically concrete MUD is analysed over the satellite environments. On the other, optimal signal processing designs are developed and evaluated for the forward link. In more detail, the present dissertation begins by introducing the topic of multibeam joint processing. Thus, the most significant practical constraints that hinder the application of advanced interference mitigation techniques in satellite networks are identified and discussed. Prior to presenting the contributions of this work, the multi-antenna joint processing problem is formulated using the generic Multiuser (MU) Multiple InputMultiple Output (MIMO) baseband signal model. This model is also extended to apply in the SatComs context. A detailed presentation of the related work, starting from a generic signal processing perspective and then focusing on the SatComs field, is then given. With this review, the main open research topics are identified. Following the comprehensive literature review, the first contribution of this work, is presented. This involves the performance evaluation of MUD in the Return Link (RL) of multiuser multibeam SatComs systems. Novel, analytical expressions are derived to describe the information theoretic channel capacity as well as the performance of practical receivers over realistic satellite channels. Based on the derived formulas, significant insights for the design of the RL of next generation cooperative satellite systems are provided. In the remaining of this thesis, the focus is set on the Forward Link (FL) of multibeam SatComs, where precoding, combined with aggressive frequency reuse configurations, are proposed to enhance the offered throughput. In this context, the alleviation of practical constraints imposed by the satellite channel is the main research challenge. Focusing on the rigid framing structure of the legacy SatCom standards, the fundamental frame-based precoding problem is examined. Based on the necessity to serve multiple users by a single transmission, the connection of the frame-based precoding and the fundamental signal processing problem of physical layer multigroup multicasting is established. In this framework and to account for the power limitations imposed by a dedicated High Power Amplifier (HPA) per transmit element, a novel solution for multigroup multicasting under Per Anntenna Constraints (PACs) is derived. Therefore, the gains offered by multigroup multicasting in frame-based systems are quantified over an accurate simulation setting. Finally, advanced multicast and interference aware scheduling algorithms are proposed to glean significant gains in the rich multiuser satellite environment. The thesis concludes with the main research findings and the identification of new research challenges, which will pave the way for the deployment of cooperative multibeam satellite systems

Optimisation de la gestion des ressources voie retour

L'optimisation de l'utilisation des liens satellites est un enjeu majeur pour augmenter la rentabilité des systèmes satellites. L'augmentation de la réutilisation des fréquences est une des approches les plus prometteuses. La réutilisation des fréquences permet de transmettre plus d'informations sur une même fréquence, pour peu que les interférences entre les deux signaux ne soient pas trop importantes. Il est donc capital de contrôler l'impact de ces interférences, que ce soit via l'utilisation de schémas de réutilisation de fréquences, ou encore via des techniques de coordination dynamique des interférences, où la sélection des utilisateurs qui peuvent transmettre sur les mêmes fréquences est faite en prenant les interférences en compt