32 research outputs found
Robust Transmission in Downlink Multiuser MISO Systems: A Rate-Splitting Approach
We consider a downlink multiuser MISO system with bounded errors in the
Channel State Information at the Transmitter (CSIT). We first look at the
robust design problem of achieving max-min fairness amongst users (in the
worst-case sense). Contrary to the conventional approach adopted in literature,
we propose a rather unorthodox design based on a Rate-Splitting (RS) strategy.
Each user's message is split into two parts, a common part and a private part.
All common parts are packed into one super common message encoded using a
public codebook, while private parts are independently encoded. The resulting
symbol streams are linearly precoded and simultaneously transmitted, and each
receiver retrieves its intended message by decoding both the common stream and
its corresponding private stream. For CSIT uncertainty regions that scale with
SNR (e.g. by scaling the number of feedback bits), we prove that a RS-based
design achieves higher max-min (symmetric) Degrees of Freedom (DoF) compared to
conventional designs (NoRS). For the special case of non-scaling CSIT (e.g.
fixed number of feedback bits), and contrary to NoRS, RS can achieve a
non-saturating max-min rate. We propose a robust algorithm based on the
cutting-set method coupled with the Weighted Minimum Mean Square Error (WMMSE)
approach, and we demonstrate its performance gains over state-of-the art
designs. Finally, we extend the RS strategy to address the Quality of Service
(QoS) constrained power minimization problem, and we demonstrate significant
gains over NoRS-based designs.Comment: Accepted for publication in IEEE Transactions on Signal Processin
Coordinated Per-Antenna Power Minimization for Multicell Massive MIMO Systems with Low-Resolution Data Converters
A multicell-coordinated beamforming solution for massive multiple-input
multiple-output orthogonal frequency-division multiplexing (OFDM) systems is
presented when employing low-resolution data converters and per-antenna level
constraints. For a more realistic deployment, we aim to find the downlink (DL)
beamformer that minimizes the maximum power on transmit antenna array of each
basestation under received signal quality constraints while minimizing
per-antenna transmit power. We show that strong duality holds between the
primal DL formulation and its manageable Lagrangian dual problem which can be
interpreted as the virtual uplink (UL) problem with adjustable noise covariance
matrices. For a fixed set of noise covariance matrices, we claim that the
virtual UL solution is effectively used to compute the DL beamformer and noise
covariance matrices can be subsequently updated with an associated subgradient.
Our primary contributions are then (1) formulating the quantized DL OFDM
antenna power minimax problem and deriving its associated dual problem, (2)
showing strong duality and interpreting the dual as a virtual quantized UL OFDM
problem, and (3) developing an iterative minimax algorithm based on the dual
problem. Simulations validate the proposed algorithm in terms of the maximum
antenna transmit power and peak-to-average-power ratio.Comment: submitted for possible IEEE journal publicatio
Design of discrete-time filters for efficient implementation
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 325-333).The cost of implementation of discrete-time filters is often strongly dependent on the number of non-zero filter coefficients or the precision with which the coefficients are represented. This thesis addresses the design of sparse and bit-efficient filters under different constraints on filter performance in the context of frequency response approximation, signal estimation, and signal detection. The results have applications in several areas, including the equalization of communication channels, frequency-selective and frequency-shaping filtering, and minimum-variance distortionless-response beamforming. The design problems considered admit efficient and exact solutions in special cases. For the more difficult general case, two approaches are pursued. The first develops low-complexity algorithms that are shown to yield optimal or near-optimal designs in many instances, but without guarantees. The second focuses on optimal algorithms based on the branch-and-bound procedure. The complexity of branch-and-bound is reduced through the use of bounds that are good approximations to the true optimal cost. Several bounding methods are developed, many involving relaxations of the original problem. The approximation quality of the bounds is characterized and efficient computational methods are discussed. Numerical experiments show that the bounds can result in substantial reductions in computational complexity.by Dennis Wei.Ph.D
Application of integer quadratic programming in detection of high-dimensional wireless systems
High-dimensional wireless systems have recently generated a great deal of interest due to their ability to accommodate increasing demands for high transmission data rates with high communication reliability. Examples of such large-scale systems include single-input, single-output symbol spread OFDM system, large-scale single-user multi-input multi-output (MIMO) OFDM systems, and large-scale multiuser MIMO systems. In these systems, the number of symbols required to be jointly detected at the receiver is relatively large. The challenge with the practical realization of these systems is to design a detection scheme that provides high communication reliability with reasonable computational complexity, even as the number of simultaneously transmitted independent communication signals becomes very large.^ Most of the optimal or near-optimal detection techniques that have been proposed in the literature of relatively low-dimensional wireless systems, such as MIMO systems in which number of antennas is less than 10, become problematic for high-dimensional detection problems. That is, their performance degrades or the computational complexity becomes prohibitive, especially when higher-order QAM constellations are employed.^ In the first part of this thesis, we propose a near-optimal detection technique which offers a flexible trade-off between complexity and performance. The proposed technique formulates the detection problem in terms of Integer Quadratic Programming (IQP), which is then solved through a controlled Branch and Bound (BB) search tree algorithm. In addition to providing good performance, an important feature of this approach is that its computational complexity remains roughly the same even as we increase the constellation order from 4-QAM to 256-QAM. The performance of the proposed algorithm is investigated for both symbol spread OFDM systems and large-scale MIMO systems with both frequency selective and at fading channels.^ The second part of this work focuses on a reduced complexity version of IQP referred to as relaxed quadratic programming (QP). In particular, QP is used to reformulate two widely used detection schemes for MIMO OFDM: (1) Successive Interference Cancellation (SIC) and (2) Iterative Detecting and Decoding (IDD). First, SIC-based algorithms are derived via a QP formulation in contrast to using a linear MMSE detector at each stage. The resulting QP-SIC algorithms offer lower computational complexity than the SIC schemes that employ linear MMSE at each stage, especially when the dimension of the received signal vector is high. Three versions of QP-SIC are proposed based on various trade-offs between complexity and receiver performance; each of the three QP-SIC algorithms outperforms existing SIC techniques. Second, IDD-based algorithms are developed using a QP detector. We show how the soft information, in terms of the Log Likelihood Ratio (LLR), can be extracted from the QP detector. Further, the procedure for incorporating the a-priori information that is passed from the channel decoder to the QP detector is developed. Simulation results are presented demonstrating that the use of QP in IDD offers improved performance at the cost of a reasonable increase in complexity compared to linear detectors
Multi-user spatial diversity techniques for wireless communication systems
Multiple antennas at the transmitter and receiver, formally known as multiple-input
multiple-output (MIMO) systems have the potential to either increase the data rates
through spatial multiplexing or enhance the quality of services through exploitation
of diversity. In this thesis, the problem of downlink spatial multiplexing, where a
base station (BS) serves multiple users simultaneously in the same frequency band is
addressed. Spatial multiplexing techniques have the potential to make huge saving
in the bandwidth utilization. We propose spatial diversity techniques with and without
the assumption of perfect channel state information (CSI) at the transmitter.
We start with proposing improvement to signal-to-leakage ratio (SLR) maximization
based spatial multiplexing techniques for both fiat fading and frequency selective
channels. [Continues.
Optimal Jammer Placement in Wireless Localization Systems
In this study, the optimal jammer placement problem is proposed and analyzed for wireless localization systems. In particular, the optimal location of a jammer node is obtained by maximizing the minimum of the Cramér-Rao lower bounds (CRLBs) for a number of target nodes under location related constraints for the jammer node. For scenarios with more than two target nodes, theoretical results are derived to specify conditions under which the jammer node is located as close to a certain target node as possible, or the optimal location of the jammer node is determined by two of the target nodes. Also, explicit expressions are provided for the optimal location of the jammer node in the presence of two target nodes. In addition, in the absence of distance constraints for the jammer node, it is proved, for scenarios with more than two target nodes, that the optimal jammer location lies on the convex hull formed by the locations of the target nodes and is determined by two or three of the target nodes, which have equalized CRLBs. Numerical examples are presented to provide illustrations of the theoretical results in different scenarios. © 1991-2012 IEEE
IIR Digital Filter Design Using Convex Optimization
Digital filters play an important role in digital signal processing and communication. From the 1960s, a considerable number of design algorithms have been proposed for finite-duration impulse response (FIR) digital filters and infinite-duration impulse response (IIR) digital filters. Compared with FIR digital filters, IIR digital filters have better approximation capabilities under the same specifications. Nevertheless, due to the presence of the denominator in its rational transfer function, an IIR filter design problem cannot be easily formulated as an equivalent convex optimization problem. Furthermore, for stability, all the poles of an IIR digital filter must be constrained within a stability domain, which, however, is generally nonconvex. Therefore, in practical designs, optimal solutions cannot be definitely attained. In this dissertation, we focus on IIR filter design problems under the weighted least-squares (WLS) and minimax criteria. Convex optimization will be utilized as the major mathematical tool to formulate and analyze such IIR filter design problems. Since the original IIR filter design problem is essentially nonconvex, some approximation and convex relaxation techniques have to be deployed to achieve convex formulations of such design problems. We first consider the stability issue. A sufficient and necessary stability condition is derived from the argument principle. Although the original stability condition is in a nonconvex form, it can be appropriately approximated by a quadratic constraint and readily combined with sequential WLS design procedures. Based on the sufficient and necessary stability condition, this approximate stability constraint can achieve an improved description of the nonconvex stability domain. We also address the nonconvexity issue of minimax design of IIR digital filters. Convex relaxation techniques are applied to obtain relaxed design problems, which are formulated, respectively, as second-order cone programming (SOCP) and semidefinite programming (SDP) problems. By solving these relaxed design problems, we can estimate lower bounds of minimum approximation errors, which are useful in subsequent design procedures to achieve real minimax solutions. Since the relaxed design problems are independent of local information, compared with many prevalent design methods which employ local search, the proposed design methods using the convex relaxation techniques have an increased chance to obtain an optimal design
Spectrally efficient FDM communication signals and transceivers: design, mathematical modelling and system optimization
This thesis addresses theoretical, mathematical modelling and design issues of Spectrally Efficient
FDM (SEFDM) systems. SEFDM systems propose bandwidth savings when compared to
Orthogonal FDM (OFDM) systems by multiplexing multiple non-orthogonal overlapping carriers.
Nevertheless, the deliberate collapse of orthogonality poses significant challenges on the
SEFDM system in terms of performance and complexity, both issues are addressed in this work.
This thesis first investigates the mathematical properties of the SEFDM system and reveals the
links between the system conditioning and its main parameters through closed form formulas
derived for the Intercarrier Interference (ICI) and the system generating matrices. A rigorous
and efficient mathematical framework, to represent non-orthogonal signals using Inverse Discrete
Fourier Transform (IDFT) blocks, is proposed. This is subsequently used to design simple
SEFDM transmitters and to realize a new Matched Filter (MF) based demodulator using the
Discrete Fourier Transforms (DFT), thereby substantially simplifying the transmitter and demodulator
design and localizing complexity at detection stage with no premium at performance.
Operation is confirmed through the derivation and numerical verification of optimal detectors
in the form of Maximum Likelihood (ML) and Sphere Decoder (SD). Moreover, two new linear
detectors that address the ill conditioning of the system are proposed: the first based on
the Truncated Singular Value Decomposition (TSVD) and the second accounts for selected ICI
terms and termed Selective Equalization (SelE). Numerical investigations show that both detectors
substantially outperform existing linear detection techniques. Furthermore, the use of the
Fixed Complexity Sphere Decoder (FSD) is proposed to further improve performance and avoid
the variable complexity of the SD. Ultimately, a newly designed combined FSD-TSVD detector
is proposed and shown to provide near optimal error performance for bandwidth savings of 20%
with reduced and fixed complexity.
The thesis also addresses some practical considerations of the SEFDM systems. In particular,
mathematical and numerical investigations have shown that the SEFDM signal is prone to high
Peak to Average Power Ratio (PAPR) that can lead to significant performance degradations.
Investigations of PAPR control lead to the proposal of a new technique, termed SLiding Window
(SLW), utilizing the SEFDM signal structure which shows superior efficacy in PAPR control
over conventional techniques with lower complexity. The thesis also addresses the performance
of the SEFDM system in multipath fading channels confirming favourable performance and
practicability of implementation. In particular, a new Partial Channel Estimator (PCE) that
provides better estimation accuracy is proposed. Furthermore, several low complexity linear
and iterative joint channel equalizers and symbol detectors are investigated in fading channels
conditions with the FSD-TSVD joint equalization and detection with PCE obtained channel
estimate facilitating near optimum error performance, close to that of OFDM for bandwidth
savings of 25%. Finally, investigations of the precoding of the SEFDM signal demonstrate a
potential for complexity reduction and performance improvement.
Overall, this thesis provides the theoretical basis from which practical designs are derived to
pave the way to the first practical realization of SEFDM systems
Transmission strategies for broadband wireless systems with MMSE turbo equalization
This monograph details efficient transmission strategies for single-carrier wireless broadband communication systems employing iterative (turbo) equalization. In particular, the first part focuses on the design and analysis of low complexity and robust MMSE-based turbo equalizers operating in the frequency domain. Accordingly, several novel receiver schemes are presented which improve the convergence properties and error performance over the existing turbo equalizers. The second part discusses concepts and algorithms that aim to increase the power and spectral efficiency of the communication system by efficiently exploiting the available resources at the transmitter side based upon the channel conditions. The challenging issue encountered in this context is how the transmission rate and power can be optimized, while a specific convergence constraint of the turbo equalizer is guaranteed.Die vorliegende Arbeit beschäftigt sich mit dem Entwurf und der Analyse von
effizienten Übertragungs-konzepten für drahtlose, breitbandige
Einträger-Kommunikationssysteme mit iterativer (Turbo-) Entzerrung und
Kanaldekodierung. Dies beinhaltet einerseits die Entwicklung von
empfängerseitigen Frequenzbereichs-entzerrern mit geringer Komplexität
basierend auf dem Prinzip der Soft Interference Cancellation Minimum-Mean
Squared-Error (SC-MMSE) Filterung und andererseits den Entwurf von
senderseitigen Algorithmen, die durch Ausnutzung von
Kanalzustandsinformationen die Bandbreiten- und Leistungseffizienz in Ein-
und Mehrnutzersystemen mit Mehrfachantennen (sog. Multiple-Input
Multiple-Output (MIMO)) verbessern.
Im ersten Teil dieser Arbeit wird ein allgemeiner Ansatz für Verfahren zur
Turbo-Entzerrung nach dem Prinzip der linearen MMSE-Schätzung, der
nichtlinearen MMSE-Schätzung sowie der kombinierten MMSE- und
Maximum-a-Posteriori (MAP)-Schätzung vorgestellt. In diesem Zusammenhang
werden zwei neue Empfängerkonzepte, die eine Steigerung der
Leistungsfähigkeit und Verbesserung der Konvergenz in Bezug auf
existierende SC-MMSE Turbo-Entzerrer in verschiedenen Kanalumgebungen
erzielen, eingeführt. Der erste Empfänger - PDA SC-MMSE - stellt eine
Kombination aus dem Probabilistic-Data-Association (PDA) Ansatz und dem
bekannten SC-MMSE Entzerrer dar. Im Gegensatz zum SC-MMSE nutzt der PDA
SC-MMSE eine interne Entscheidungsrückführung, so dass zur Unterdrückung
von Interferenzen neben den a priori Informationen der Kanaldekodierung
auch weiche Entscheidungen der vorherigen Detektions-schritte
berücksichtigt werden. Durch die zusätzlich interne
Entscheidungsrückführung erzielt der PDA SC-MMSE einen wesentlichen Gewinn
an Performance in räumlich unkorrelierten MIMO-Kanälen gegenüber dem
SC-MMSE, ohne dabei die Komplexität des Entzerrers wesentlich zu erhöhen.
Der zweite Empfänger - hybrid SC-MMSE - bildet eine Verknüpfung von
gruppenbasierter SC-MMSE Frequenzbereichsfilterung und MAP-Detektion.
Dieser Empfänger besitzt eine skalierbare Berechnungskomplexität und weist
eine hohe Robustheit gegenüber räumlichen Korrelationen in MIMO-Kanälen
auf. Die numerischen Ergebnisse von Simulationen basierend auf Messungen
mit einem Channel-Sounder in Mehrnutzerkanälen mit starken räumlichen
Korrelationen zeigen eindrucksvoll die Überlegenheit des hybriden
SC-MMSE-Ansatzes gegenüber dem konventionellen SC-MMSE-basiertem Empfänger.
Im zweiten Teil wird der Einfluss von System- und Kanalmodellparametern auf
die Konvergenzeigenschaften der vorgestellten iterativen Empfänger mit
Hilfe sogenannter Korrelationsdiagramme untersucht. Durch semi-analytische
Berechnungen der Entzerrer- und Kanaldecoder-Korrelationsfunktionen wird
eine einfache Berechnungsvorschrift zur Vorhersage der
Bitfehlerwahrscheinlichkeit von SC-MMSE und PDA SC-MMSE Turbo Entzerrern
für MIMO-Fadingkanäle entwickelt. Des Weiteren werden zwei Fehlerschranken
für die Ausfallwahrscheinlichkeit der Empfänger vorgestellt. Die
semi-analytische Methode und die abgeleiteten Fehlerschranken ermöglichen
eine aufwandsgeringe Abschätzung sowie Optimierung der Leistungsfähigkeit
des iterativen Systems.
Im dritten und abschließenden Teil werden Strategien zur Raten- und
Leistungszuweisung in Kommunikationssystemen mit konventionellen iterativen
SC-MMSE Empfängern untersucht. Zunächst wird das Problem der Maximierung
der instantanen Summendatenrate unter der Berücksichtigung der Konvergenz
des iterativen Empfängers für einen Zweinutzerkanal mit fester
Leistungsallokation betrachtet. Mit Hilfe des Flächentheorems von
Extrinsic-Information-Transfer (EXIT)-Funktionen wird eine obere Schranke
für die erreichbare Ratenregion hergeleitet. Auf Grundlage dieser Schranke
wird ein einfacher Algorithmus entwickelt, der für jeden Nutzer aus einer
Menge von vorgegebenen Kanalcodes mit verschiedenen Codierraten denjenigen
auswählt, der den instantanen Datendurchsatz des Mehrnutzersystems
verbessert. Neben der instantanen Ratenzuweisung wird auch ein
ausfallbasierter Ansatz zur Ratenzuweisung entwickelt. Hierbei erfolgt die
Auswahl der Kanalcodes für die Nutzer unter Berücksichtigung der Einhaltung
einer bestimmten Ausfallwahrscheinlichkeit (outage probability) des
iterativen Empfängers. Des Weiteren wird ein neues Entwurfskriterium für
irreguläre Faltungscodes hergeleitet, das die Ausfallwahrscheinlichkeit von
Turbo SC-MMSE Systemen verringert und somit die Zuverlässigkeit der
Datenübertragung erhöht. Eine Reihe von Simulationsergebnissen von
Kapazitäts- und Durchsatzberechnungen werden vorgestellt, die die
Wirksamkeit der vorgeschlagenen Algorithmen und Optimierungsverfahren in
Mehrnutzerkanälen belegen. Abschließend werden außerdem verschiedene
Maßnahmen zur Minimierung der Sendeleistung in Einnutzersystemen mit
senderseitiger Singular-Value-Decomposition (SVD)-basierter Vorcodierung
untersucht. Es wird gezeigt, dass eine Methode, welche die Leistungspegel
des Senders hinsichtlich der Bitfehlerrate des iterativen Empfängers
optimiert, den konventionellen Verfahren zur Leistungszuweisung überlegen
ist