## Reduced-Complexity Adaptive Filtering Techniques for Communications Applications (2013)

Adaptive interference suppression algorithms for DS-UWB systems

In multiuser ultra-wideband (UWB) systems, a large number of multipath components (MPCs) are introduced by the channel. One of the main challenges for the receiver is to effectively suppress the interference with affordable complexity. In this thesis, we focus on the linear adaptive interference suppression algorithms for the direct-sequence ultrawideband (DS-UWB) systems in both time-domain and frequency-domain. In the time-domain, symbol by symbol transmission multiuser DS-UWB systems are considered. We first investigate a generic reduced-rank scheme based on the concept of joint and iterative optimization (JIO) that jointly optimizes a projection vector and a reduced-rank filter by using the minimum mean-squared error (MMSE) criterion. A low-complexity scheme, named Switched Approximations of Adaptive Basis Functions (SAABF), is proposed as a modification of the generic scheme, in which the complexity reduction is achieved by using a multi-branch framework to simplify the structure ...

Sheng Li — University of York

On Ways to Improve Adaptive Filter Performance

Adaptive filtering techniques are used in a wide range of applications, including echo cancellation, adaptive equalization, adaptive noise cancellation, and adaptive beamforming. The performance of an adaptive filtering algorithm is evaluated based on its convergence rate, misadjustment, computational requirements, and numerical robustness. We attempt to improve the performance by developing new adaptation algorithms and by using "unconventional" structures for adaptive filters. Part I of this dissertation presents a new adaptation algorithm, which we have termed the Normalized LMS algorithm with Orthogonal Correction Factors (NLMS-OCF). The NLMS-OCF algorithm updates the adaptive filter coefficients (weights) on the basis of multiple input signal vectors, while NLMS updates the weights on the basis of a single input vector. The well-known Affine Projection Algorithm (APA) is a special case of our NLMS-OCF algorithm. We derive convergence and tracking properties of NLMS-OCF using a simple model ...

Sankaran, Sundar G. — Virginia Tech

Recently emerging techniques like wave field synthesis (WFS) or Higher-Order Ambisonics (HOA) allow for high-quality spatial audio reproduction, which makes them candidates for the audio reproduction in future telepresence systems or interactive gaming environments with acoustic human-machine interfaces. In such scenarios, acoustic echo cancellation (AEC) will generally be necessary to remove the loudspeaker echoes in the recorded microphone signals before further processing. Moreover, the reproduction quality of WFS or HOA can be improved by adaptive pre-equalization of the loudspeaker signals, as facilitated by listening room equalization (LRE). However, AEC and LRE require adaptive filters, where the large number of reproduction channels of WFS and HOA imply major computational and algorithmic challenges for the implementation of adaptive filters. A technique called wave-domain adaptive filtering (WDAF) promises to master these challenges. However, known literature is still far away from providing sufficient insight ...

Schneider, Martin — Friedrich-Alexander-University Erlangen-Nuremberg

Distributed Space-Time Coding Techniques with Limited Feedback in Cooperative MIMO Networks

Multi-input multi-output (MIMO) wireless networks and distributed MIMO relaying wireless networks have attracted significant attention in current generation of wireless communication networks, and will play a key role in the next generation of wireless net- works. The improvement of network capacity, data rate and reliability can be achieved at the cost of increasing computational complexity of employing space-time coding (STC) and distributed STC (DSTC) in MIMO and distributed MIMO relaying networks, respectively. Efficient designs and algorithms to achieve high diversity and coding gains with low computational complexity in encoding and decoding of STC and DSTC schemes are essential. In this thesis, DSTC designs with high diversity and coding gains and efficient detection and code matrices optimization algorithms in cooperative MIMO networks are proposed. Firstly, adaptive power allocation (PA) algorithms with different criteria for a coop- erative MIMO network equipped with ...

Peng, Tong — University of York

Signal processing algorithms for wireless acoustic sensor networks

Recent academic developments have initiated a paradigm shift in the way spatial sensor data can be acquired. Traditional localized and regularly arranged sensor arrays are replaced by sensor nodes that are randomly distributed over the entire spatial field, and which communicate with each other or with a master node through wireless communication links. Together, these nodes form a so-called ‘wireless sensor network’ (WSN). Each node of a WSN has a local sensor array and a signal processing unit to perform computations on the acquired data. The advantage of WSNs compared to traditional (wired) sensor arrays, is that many more sensors can be used that physically cover the full spatial field, which typically yields more variety (and thus more information) in the signals. It is likely that future data acquisition, control and physical monitoring, will heavily rely on this type of ...

Bertrand, Alexander — Katholieke Universiteit Leuven

Efficient Interference Suppression and Resource Allocation in MIMO and DS-CDMA Wireless Networks

Direct-sequence code-divisionmultiple-access (DS-CDMA) and multiple-input multiple-output (MIMO) wireless networks form the physical layer of the current generation of mobile networks and are anticipated to play a key role in the next generation of mobile networks. The improvements in capacity, data-rates and robustness that these networks provide come at the cost of increasingly complex interference suppression and resource allocation. Consequently, efficient approaches to these tasks are essential if the current rate of progression in mobile technology is to be sustained. In this thesis, linear minimum mean-square error (MMSE) techniques for interference suppression and resource allocation in DS-CDMA and cooperative MIMO networks are considered and a set of novel and efficient algorithms proposed. Firstly, set-membership (SM) reduced-rank techniques for interference suppression in DS-CDMA systems are investigated. The principals of SM filtering are applied to the adaptation of the projection matrix and reduced-rank ...

Patrick Clarke — University of York

Array Signal Processing Algorithms for Beamforming and Direction Finding

Array processing is an area of study devoted to processing the signals received from an antenna array and extracting information of interest. It has played an important role in widespread applications like radar, sonar, and wireless communications. Numerous adaptive array processing algorithms have been reported in the literature in the last several decades. These algorithms, in a general view, exhibit a trade-off between performance and required computational complexity. In this thesis, we focus on the development of array processing algorithms in the application of beamforming and direction of arrival (DOA) estimation. In the beamformer design, we employ the constrained minimum variance (CMV) and the constrained constant modulus (CCM) criteria to propose full-rank and reduced-rank adaptive algorithms. Specifically, for the full-rank algorithms, we present two low-complexity adaptive step size mechanisms with the CCM criterion for the step size adaptation of the ...

Lei Wang — University of York

Adaptive Algorithms and Variable Structures for Distributed Estimation

The analysis and design of new non-centralized learning algorithms for potential application in distributed adaptive estimation is the focus of this thesis. Such algorithms should be designed to have low processing requirement and to need minimal communication between the nodes which would form a distributed network. They ought, moreover, to have acceptable performance when the nodal input measurements are coloured and the environment is dynamic. Least mean square (LMS) and recursive least squares (RLS) type incremental distributed adaptive learning algorithms are first introduced on the basis of a Hamiltonian cycle through all of the nodes of a distributed network. These schemes require each node to communicate only with one of its neighbours during the learning process. An original steady-steady performance analysis of the incremental LMS algorithm is performed by exploiting a weighted spatial-temporal energy conservation formulation. This analysis confirms that ...

Li, Leilei — Loughborough University

Multimedia consumer electronics are nowadays everywhere from teleconferencing, hands-free communications, in-car communications to smart TV applications and more. We are living in a world of telecommunication where ideal scenarios for implementing these applications are hard to find. Instead, practical implementations typically bring many problems associated to each real-life scenario. This thesis mainly focuses on two of these problems, namely, acoustic echo and acoustic feedback. On the one hand, acoustic echo cancellation (AEC) is widely used in mobile and hands-free telephony where the existence of echoes degrades the intelligibility and listening comfort. On the other hand, acoustic feedback limits the maximum amplification that can be applied in, e.g., in-car communications or in conferencing systems, before howling due to instability, appears. Even though AEC and acoustic feedback cancellation (AFC) are functional in many applications, there are still open issues. This means that ...

Gil-Cacho, Jose Manuel — KU Leuven

Computationally Efficient Equalisation of Broadband Multiple-Input Multiple-Output Systems

Multiple-input multiple-output (MIMO) systems are encountered for example in communications if several transmit and receive antennas are empoyed, such that a separate transmit channel exists between every possible pairing of transmitter and receiver antennas. As a results if this spatial diversity, the channel capacity is dramatically increased over the single-inout single-output (SISO) case. While this increase is desired, the use of high data rates requires sophistiocated equalisation and/or detection schemes in the receiver to compensate for spatial and temporal dispersion in broadband MIMO channels, since a time-dispersive, in addition ot spatially-dispersice channel, must be assumed. The estimation of the broadband MIMO channel or its inverse is in general difficult and calls for training sequences that reduce the slot time for the transmission of actual data, which may counteract the promised gain in channel capacity. Another problem can be the computational ...

Bale, Viktor — University of Southampton

Stability of Coupled Adaptive Filters

Nowadays, many disciplines in science and engineering deal with problems for which a solution relies on knowledge about the characteristics of one or more given systems that can only be ascertained based on restricted observations. This requires the fitting of an adequately chosen model, such that it “best” conforms to a set of measured data. Depending on the context, this fitting procedure may resort to a huge amount of recorded data and abundant numerical power, or contrarily, to only a few streams of samples, which have to be processed on the fly at low computational cost. This thesis, exclusively focuses on the latter scenario. It specifically studies unexpected behaviour and reliability of the widely spread and computationally highly efficient class of gradient type algorithms. Additionally, special attention is paid to systems that combine several of them. Chapter 3 is dedicated ...

Dallinger, Robert — TU Wien

Orthonormal Bases for Adaptive filtering

In the field of adaptive filtering the most commonly applied filter structure is the transversal filter, also referred to as the tapped-delay line (TDL). The TDL is composed of a cascade of unit delay elements that are tapped, weighted and then summed. Thus, the output of a TDL is formed by a linear combination of its input signal at various delays. The weights in this linear combination are called the tap weights. The number of delay elements, or equivalently the number of tap weights, determines the duration of the impulse response of the TDL. For this reason, one often speaks of a finite impulse response (FIR) filter. In a general adaptive filtering scheme the adaptive filter aims to minimize a certain measure of error between its output and a desired signal. Usually, a quadratic cost criterion is taken: the so-called ...

Belt, harm — Eindhoven University of Technology

This dissertation deals with the distributed processing techniques for parameter estimation and efficient data-gathering in wireless communication and sensor networks. The estimation problem consists in inferring a set of parameters from temporal and spatial noisy observations collected by different nodes that monitor an area or field. The objective is to derive an estimate that is as accurate as the one that would be obtained if each node had access to the information across the entire network. With the aim of enabling an energy aware and low-complexity distributed implementation of the estimation task, several useful optimization techniques that generally yield linear estimators were derived in the literature. Up to now, most of the works considered that the nodes are interested in estimating the same vector of global parameters. This scenario can be viewed as a special case of a more general ...

Bogdanovic, Nikola — University of Patras

Robust Equalization of Multichannel Acoustic Systems

In most real-world acoustical scenarios, speech signals captured by distant microphones from a source are reverberated due to multipath propagation, and the reverberation may impair speech intelligibility. Speech dereverberation can be achieved by equalizing the channels from the source to microphones. Equalization systems can be computed using estimates of multichannel acoustic impulse responses. However, the estimates obtained from system identification always include errors; the fact that an equalization system is able to equalize the estimated multichannel acoustic system does not mean that it is able to equalize the true system. The objective of this thesis is to propose and investigate robust equalization methods for multichannel acoustic systems in the presence of system identification errors. Equalization systems can be computed using the multiple-input/output inverse theorem or multichannel least-squares method. However, equalization systems obtained from these methods are very sensitive to system ...

Zhang, Wancheng — Imperial College London

Algorithms and architectures for adaptive array signal processing

Antenna arrays sample propagating waves at multiple locations. They are employed e.g. in radar, sonar and wireless communication systems because of their capacity of spatial selectivity and localization of radiating sources. Current model-based algorithms make use of computationally demanding orthogonal matrix decompositions such as the singular value decomposition (SVD). On the other hand the data rates are often extremely high. Therefore, real-time execution of complex algorithms often requires parallel computing. We study the simultaneous design of new algorithms and parallel architectures for subspace tracking, for robust adaptive beamforming and for direction finding of narrow-band and wide-band sources. By structuring all recursive algorithms in a similar way, they can be mapped efficiently onto the Jacobi architecture, which was originally developed for SVD updating. The numerical and architectural aspects of this algorithm are improved by the use of a minimal parameterziation of ...

Vanpoucke, Filiep — Katholieke Universiteit Leuven

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