Search

The generalized eigenvalue decomposition (GEVD) of a pair of matrices generalizes the concept of the eigenvalue decomposition (EVD) of a single matrix. It is a widely used tool in signal processing applications, in particular in a context of spatial filtering and subspace estimation. In this paper, we describe a distributed adaptive algorithm to estimate generalized eigenvectors (GEVCs) of a pair of sensor signal covariance matrices in a fully connected wireless sensor network. The algorithm computes these GEVCs in an iterative fashion without explicitly constructing the full network-wide covariance matrices. Instead, the nodes only exchange compressed sensor signal observations, providing a significant reduction in per-node communication and computational cost compared to the scenario where all the raw sensor signal observations are collected and processed in a fusion center. [ABSTRACT FROM AUTHOR]

Abstract: We describe a distributed adaptive algorithm to estimate the eigenvectors corresponding to the Q largest or smallest eigenvalues of the network-wide sensor signal covariance matrix in a wireless sensor network. The proposed algorithm recursively updates the eigenvector estimates without explicitly constructing the full covariance matrix that defines them, i.e., without centralizing all the raw sensor signal observations. By only sharing fused Q-dimensional observations, each node obtains estimates of (a) the node-specific entries of the Q covariance matrix eigenvectors, and (b) Q-dimensional projections of the full set of sensor signal observations onto the Q eigenvectors. We also explain how the latter can be used for, e.g., compression and reconstruction of the sensor signal observations based on principal component analysis (PCA), in which each node acts as a data sink. We describe a version of the algorithm for fully-connected networks, as well as for partially-connected networks. In the latter case, we assume that the network has been pruned to a tree topology to avoid cycles in the network. We provide convergence proofs, as well as numerical simulations to demonstrate the convergence and optimality of the algorithm. [Copyright &y& Elsevier]

Abstract: Binaural hearing aids allow for a wireless exchange of microphone signals between a left and a right device. A significant noise reduction performance improvement can be achieved compared to a monaural configuration (a single device) or a bilateral configuration (in which the devices work independently). In addition, the binaural localization cues, i.e. the Interaural Time Differences and Interaural Level Differences, can also be better preserved in a binaural procedure. It was previously proven that a binaural noise reduction procedure based on the Speech Distortion Weighted Multi-channel Wiener Filter (SDW-MWF) indeed preserves the speech localization cues, if all microphone signals can be exchanged. However, in practice, it may not be feasible to exchange all microphone signals between the devices, so that reduced-bandwidth SDW-MWF schemes (where only filtered combinations of microphone signals are exchanged) have to be utilized. This paper demonstrates that a straightforward reduced-bandwidth SDW-MWF scheme still preserves the speech ITD cues, but distorts the speech ILD cues, in a single speech source scenario. Novel reduced-bandwidth SDW-MWF schemes, which make use of a common spectral postfilter, are therefore introduced. Experiments in a reverberant environment demonstrate that the novel schemes reduce the ILD distortion, without severely degrading the noise reduction performance. [Copyright &y& Elsevier]

Abstract: Per-tone equalization has been proposed as an alternative to time domain equalization for DMT receivers in DSL modems. It optimizes the bit rate performance of the receiver as each tone can be equalized independently. It has also been shown that using variable length equalizers can significantly reduce the total number of equalizer taps and hence the run-time complexity, without compromising performance. For a given transmit power loading, it has been shown that the equalizer taps can be allocated optimally using a dual decomposition based approach with per-tone exhaustive searches over all possible equalizer lengths. However, a more general approach is needed when optimal transmit power allocation is also considered to maximize the overall bit rate, where in addition the per-tone exhaustive searches are replaced by a more efficient procedure. In this paper, a sparse approximation based resource allocation algorithm is presented to allocate equalizer taps and transmit power over tones and maximize the overall bit rate. This algorithm is shown to provide efficient allocations at a relatively low computational cost. [Copyright &y& Elsevier]

Abstract: This paper presents weighted approaches for integrated active noise control and noise reduction in hearing aids. The unweighted integrated active noise control and noise reduction scheme introduced in the previous work does not allow to trade-off between the active noise control and the noise reduction. In some circumstances it will, however, be useful to emphasize one of the functional blocks. Changing the original optimisation problem to a constrained optimisation problem leads to a scheme based on a weighted mean squared error criterion that allows to focus either on the active noise control or on the noise reduction. It is similarly possible to derive a scheme that allows to focus either on reducing the speech distortion or on reducing the residual noise at the eardrum. In a single speech source scenario and when the number of sound sources (speech plus noise sources) is less than or equal to the number of microphones, it is possible to derive a simple formula for the output signal-to-noise ratio of the latter scheme. It can then be shown that this scheme delivers a constant signal-to-noise ratio at the eardrum for any weighting factor. [Copyright &y& Elsevier]

Abstract: The Fiedler vector of a graph is the eigenvector corresponding to the smallest non-trivial eigenvalue of the graph''s Laplacian matrix. The entries of the Fiedler vector are known to provide a powerful heuristic for topology inference, e.g., to identify densely connected node clusters, to search for bottleneck links in the information dissemination, or to increase the overall connectivity of the network. In this paper, we consider ad hoc networks where the nodes can process and exchange data in a synchronous fashion, and we propose a distributed algorithm for in-network estimation of the Fiedler vector and the algebraic connectivity of the corresponding network graph. The algorithm is fully scalable with respect to the network size in terms of per-node computational complexity and data transmission. Simulation results demonstrate the performance of the algorithm. [Copyright &y& Elsevier]

Abstract: Per-tone pulse shaping has been proposed as an alternative to time domain spectral shaping for DMT transmitters. It shapes the spectrum of individual tones such that their stop band energy contribution can be minimized. In per-tone pulse shaping based DMT transmitters a fixed order non-sparse pulse shaping filter is typically used for every tone. Furthermore, no specific power loading scheme is used. However, the contribution of a particular tone to the stop band energy depends on the amount of power transmitted on the tone and the distance of the tone from the band edges. Tones with sufficiently low power as well as tones sufficiently away from the band edges could be assigned a sparse pulse shaping filter, which could then help to reduce the overall number of filter taps. In general the combination of power loading and sparse pulse shaping filters can be used to achieve a high data rate under given resource constraints. In this paper we present an algorithm to optimally allocate the available resources, i.e., power and filter taps, under PSD mask constraints, which is based on a dual problem formulation. This algorithm achieves a high performance with relatively low complexity, which is also demonstrated by simulations. [Copyright &y& Elsevier]

Abstract: In this paper, we consider distributed signal estimation in sensor networks where the nodes exchange compressed sensor signal observations to estimate different node-specific signals. In particular, we revisit the so-called distributed adaptive node-specific signal estimation (DANSE) algorithm, which applies to the case where the nodes share a so-called ‘common interest’, and cast it in the more general setting where the nodes have ‘different interests’. We prove existence of an equilibrium state for such a setting by using a result from fixed point theory. By establishing a link between the DANSE algorithm and game theory, we point out that any equilibrium of the DANSE algorithm is a Nash equilibrium of the corresponding game. This provides an intuitive interpretation to the resulting signal estimators. The equilibrium state existence proof also reveals a problem with discontinuities in the DANSE update function, which may result in non-convergence of the algorithm. However, since these discontinuities are identifiable, they can easily be avoided by applying a minor heuristic modification to the algorithm. We demonstrate the effectiveness of this modification by means of numerical examples. [Copyright &y& Elsevier]

Abstract: In current DSL systems, crosstalk is a major source of performance degradation. For upstream VDSL scenarios with in-domain crosstalk and AWGN, it has been shown that the crosstalk can be effectively mitigated using a linear zero-forcing canceler. Furthermore, the complexity can be reduced by only canceling the crosstalk from major crosstalkers, which is referred to as partial crosstalk cancellation. However, such approach does not work well in scenarios that also have out-of-domain (alien) crosstalk. As alien crosstalk is spatially correlated, the zero-forcing canceler performs very poorly, hence alternative structures for the canceler have to be examined. In this paper, we first demonstrate that an MMSE-based linear and nonlinear crosstalk canceler provides improved performance compared to the zero-forcing canceler in this scenario and then present efficient algorithms to perform partial crosstalk cancellation with these MMSE-based cancelers. [Copyright &y& Elsevier]

Abstract: This paper analyses the output signal-to-noise ratio for a standard noise reduction scheme based on the multichannel Wiener filter and for an integrated active noise control and noise reduction scheme based on the filtered-X multichannel Wiener filter, both applied in a hearing aid framework that includes the effects of signal leakage through an open fitting and secondary path effects. In previous work, integrating noise reduction and active noise control has been shown to allow to compensate for effects of signal leakage and secondary path effects. These experimental results are now verified theoretically. The output signal-to-noise ratios are derived under a single speech source scenario. Theoretical results are then compared to simulations for a single noise source scenario and a multiple noise sources scenario. [Copyright &y& Elsevier]

Abstract: The direct-conversion architecture is an attractive front-end design for multi-input multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. These systems are typically small in size and provide a good flexibility to support growing number of wireless standards. However, direct-conversion based OFDM systems are generally very sensitive to front-end component imperfections. These imperfections are unavoidable especially when cheaper components are used in the manufacturing process and can lead to radio frequency (RF) impairments such as in-phase/quadrature-phase (IQ) imbalance. These RF impairments can result in a severe performance degradation. In this paper, we propose training based efficient compensation schemes for MIMO OFDM systems impaired with transmitter and receiver frequency selective IQ imbalance. The proposed schemes can decouple the compensation of the transmitter and receiver IQ imbalance from the compensation of the channel distortion. It is shown that the proposed schemes result in an overall lower training overhead and a lower computational requirement as compared to a joint estimation/compensation of IQ imbalance and the channel distortion. [Copyright &y& Elsevier]

Abstract: Multi-input multi-output (MIMO) systems are often realized with low cost front-end architectures, e.g. the so-called direct conversion (or zero IF) architectures. However, such systems are very sensitive to imperfections in the analog front-end resulting in radio frequency (RF) impairments such as in-phase/quadrature-phase (IQ) imbalance and carrier frequency offset (CFO). These RF impairments can result in a severe performance degradation. In this paper we propose RF impairment compensation techniques for orthogonal frequency division multiplexing (OFDM) based MIMO systems. We consider a digital compensation scheme for joint transmitter/receiver frequency selective IQ imbalance, CFO and channel distortion. We also show that in the case where there is no transmitter IQ imbalance, the receiver IQ imbalance compensation can be de-coupled from the channel equalization resulting in a compensation in two stages. The two-stage scheme results in an overall lower computational requirement. The various compensation schemes are demonstrated to provide a performance close to the ideal case without RF impairments. [Copyright &y& Elsevier]

Abstract: In this paper, we consider a noise-free blind source separation problem with independent non-negative source signals, also known as non-negative independent component analysis (NICA). We assume that the source signals are well-grounded, which means that they have a non-vanishing pdf in a positive neighborhood of zero. We propose a novel algorithm, referred to as multiplicative NICA (M-NICA), which uses multiplicative updates together with a subspace projection based correction step to reconstruct the original source signals from the observed linear mixtures, and which is based only on second order statistics. A multiplicative update has the facilitating property that it preserves non-negativity, and does not depend on a user-defined learning rate, as opposed to gradient based updates such as in the non-negative PCA (NPCA) algorithm. We provide batch mode simulations of M-NICA and compare its performance to NPCA, for different types of signals. It is observed that M-NICA generally yields a better unmixing accuracy, but converges slower than NPCA. Especially when the amount of data samples is small, M-NICA significantly outperforms NPCA. Furthermore, a sliding window implementation of both algorithms is described and simulated, where M-NICA is observed to provide the best results. [Copyright &y& Elsevier]

Abstract: Acoustic feedback occurs in many audio applications involving musical sound signals. However, research efforts in acoustic feedback control have mainly been focused on speech applications. Since sound quality is of prime importance in audio applications, a proactive approach to acoustic feedback control is preferred to avoid ringing, howling, and excessive reverberation. Adaptive feedback cancellation (AFC) using a prediction-error-method (PEM)-based approach is a promising proactive solution, but existing algorithms are again designed for speech applications only. We propose to replace the all-pole near-end speech signal model in the PEM-based approach with a cascade of two near-end signal models: a tonal components model and a noise components model. We derive the identifiability conditions for joint identification of the acoustic feedback path and the cascaded near-end signal models. Depending on the model structure that is used for the near-end tonal components, three different PEM-based AFC algorithms are considered. By applying some relevant model approximations, the computational overhead of the proposed algorithms compared to the normalized least mean squares (NLMS) algorithm can be reduced to 25% of the NLMS complexity. Simulation results for both room acoustic and hearing aid scenarios indicate a significant performance improvement in terms of the misadjustment and the maximum stable gain increase. [Copyright &y& Elsevier]

Abstract: We describe an approach to speech signal enhancement where acoustic echo cancellation and noise reduction, which are traditionally handled separately, are combined in one integrated scheme. The optimization problem defined by this scheme is solved adaptively using a QRD-based least squares lattice (QRD-LSL) algorithm. We show that the performance of the integrated scheme is superior to the performance of traditional (cascading) schemes, while complexity is kept at an affordable level. [Copyright &y& Elsevier]

This paper discusses two novel non-iterative design procedures based on eigenfilters for designing broadband beamformers with an arbitrary spatial directivity pattern for an arbitrary microphone configuration. In the conventional eigenfilter technique a reference frequency-angle point is required, whereas in the eigenfilter technique based on a TLS (total least squares) error criterion, no reference point is required. It is shown how to design broadband beamformers in the far-field, near-field and mixed near-field far-field of the microphone array. Both eigenfilter techniques are compared with other broadband beamformer design procedures (least-squares, maximum energy array, non-linear criterion). It will be shown by simulations that among the considered non-iterative design procedures the TLS eigenfilter technique has the best performance, i.e. best resembling the performance of the non-linear design procedure but having a significantly lower computational complexity. [Copyright &y& Elsevier]

We describe a new adaptive filtering algorithm based upon QR-decomposition for optimal multichannel filtering with an “unknown” desired signal, as well as its application to multi-channel acoustic noise reduction. A recursively calculated adaptive filter then optimally estimates the speech component in a noisy signal. The complexity of this algorithm is about 7 times lower than that of existing related algorithms, which are mainly based upon GSVD-decompositions, while performance is kept at the same level. Finally, it is shown how a parameter can be introduced which can be tuned to tradeoff noise reduction for signal distortion. [Copyright &y& Elsevier]

• Fusion rules for distributed adaptive node-specific signal estimation (DANSE) are not optimal when communication links are noisy in a wireless sensor network. • Fusion rules which take noisy links into account are developed, resulting in new algorithm named N-DANSE. • The strategy to prove convergence of N-DANSE is different from the strategy used for DANSE without noisy links, and includes the latter as a special case. • N-DANSE performs better than DANSE in scenarios with noisy links. • N-DANSE is consistently closer to the optimal performance than DANSE. We consider a distributed signal estimation problem in a wireless sensor network where each node aims to estimate a node-specific desired signal using all sensor signals available in the network. In this setting, the distributed adaptive node-specific signal estimation (DANSE) algorithm is able to learn optimal fusion rules with which the nodes fuse their sensor signals, as the fused signals are then transmitted between the nodes. Under the assumption of transmission without errors, DANSE achieves the performance of centralized estimation. However, noisy communication links introduce errors in these transmitted signals, e.g., due to quantization or communication errors. In this paper we show fusion rules which take additive noise in the transmitted signals into account at almost no increase in computational complexity, resulting in a new algorithm denoted as 'noisy-DANSE' (N-DANSE). As the convergence proof for DANSE cannot be straightforwardly generalized to the case with noisy links, we use a different strategy to prove convergence of N-DANSE, which also proves convergence of DANSE without noisy links as a special case. We validate the convergence of N-DANSE and compare its performance with the original DANSE through numerical simulations, which demonstrate the superiority of N-DANSE over the original DANSE in noisy links scenarios. [ABSTRACT FROM AUTHOR]

In multiple speaker scenarios, the linearly constrained minimum variance (LCMV) beamformer is a popular microphone array-based speech enhancement technique, as it allows minimizing the noise power while maintaining a set of desired responses towards different speakers. Here, we address the algorithmic challenges arising when applying the LCMV beamformer in wireless acoustic sensor networks (WASNs), which are a next-generation technology for audio acquisition and processing. We review three optimal distributed LCMV-based algorithms, which compute a network-wide LCMV beamformer output at each node without centralizing the microphone signals. Optimality here refers to equivalence to a centralized realization where a single processor has access to all signals. We derive and motivate the algorithms in an accessible top-down framework that reveals their underlying relations. We explain how their differences result from their different design criterion (node-specific versus common constraints sets), and their different priorities for communication bandwidth, computational power, and adaptivity. Furthermore, although originally proposed for a fully connected WASN, we also explain how to extend the reviewed algorithms to the case of a partially connected WASN, which is assumed to be pruned to a tree topology. Finally, we discuss the advantages and disadvantages of the various algorithms [ABSTRACT FROM AUTHOR]

In this paper, we consider cooperative node-specific direction-of-arrival (DOA) estimation in a fully connected wireless acoustic sensor network (WASN). We consider a scenario where each node is equipped with a local microphone array with a known geometry, but where the position of the nodes, as well as their relative geometry and hence the between-nodes signal coherence model is unknown. The local array geometry in each node defines node-specific DOAs with respect to a set of target speech sources and the aim is to estimate these in each node. We assume a noisy environment with localized and/or diffuse noise sources, i.e., the noise can be correlated over the different microphones. A distributed noise reduction algorithm can then be applied as a preprocessing step to denoise all the microphone signals of the WASN, based on the distributed adaptive node-specific signal estimation (DANSE) algorithm. The denoised local microphone signals can then be used in each node to estimate the node-specific DOAs by using a subspace-based DOA estimation, involving a (generalized) eigenvalue decomposition of the local microphone signal correlation matrices. It is seen that the fused microphone signals that are exchanged between the nodes in the DANSE algorithm can also be included in these correlation matrices to obtain improved DOA estimates, leading to a cooperative integrated noise reduction and DOA estimation scheme, where the noise reduction can actually be shortcut. The improved performance achieved by this cooperative DOA estimation is demonstrated by means of numerical simulations for two different subspace-based DOA estimation methods (MUSIC and ESPRIT). [ABSTRACT FROM AUTHOR]

Abstract: Double-talk (DT)-robust acoustic echo cancellation (AEC) and acoustic feedback cancellation (AFC) are needed in speech communication systems, e.g., in hands-free communication systems and hearing aids. In this paper, we derive a practical and computationally efficient algorithm based on the frequency-domain adaptive filter prediction error method using row operations (FDAF-PEM-AFROW) for DT-robust AEC and AFC. The proposed algorithm features two main modifications: (a) the Wiener variable step size (WVSS) and (b) the gradient spectral variance smoothing (GSVS). In AEC simulations, the WVSS-GSVS-FDAF-PEM-AFROW algorithm obtains outstanding robustness and smooth adaptation in highly adverse scenarios such as in bursting DT at high levels, and in a change of acoustic path during continuous DT. Similarly, in AFC simulations, the algorithm outperforms state-of-the-art algorithms when using a low-order near-end speech model and in colored non-stationary noise. [Copyright &y& Elsevier]

Abstract: The present study investigates the most important factors that limit the intelligibility of the cochlear implant (CI) processed speech in noisy environments. The electrical stimulation sequences provided in CIs are affected by the noise in the following three manners. First of all, the natural gaps in the speech are filled, which distorts the low-frequency ON/OFF modulations of the speech signal. Secondly, speech envelopes are distorted to include modulations of both speech and noise. Lastly, the N-of-M type of speech coding strategies may select the noise dominated channels instead of the dominant speech channels at low signal-to-noise ratio''s (SNRs). Different stimulation sequences are tested with CI subjects to study how these three noise effects individually limit the intelligibility of the CI processed speech. Tests are also conducted with normal hearing (NH) subjects using vocoded speech to identify any significant differences in the noise reduction requirements and speech distortion limitations between the two subject groups. Results indicate that compared to NH subjects CI subjects can tolerate significantly lower levels of steady state speech shaped noise in the speech gaps but at the same time can tolerate comparable levels of distortions in the speech segments. Furthermore, modulations in the stimulus current level have no effect on speech intelligibility as long as the channel selection remains ideal. Finally, wrong maxima selection together with the introduction of noise in the speech gaps significantly degrades the intelligibility. At low SNRs wrong maxima selection introduces interruptions in the speech and makes it difficult to fuse noisy and interrupted speech signals into a coherent speech stream. [Copyright &y& Elsevier]

Abstract: Noise reduction (NR) and dynamic range compression (DRC) are basic components in hearing aids, but generally these components are developed and evaluated independently of each other. Hearing aids typically use a serial concatenation of NR and DRC. However, the DRC in such a concatenation negatively affects the performance of the NR stage: the residual noise after NR receives more amplification compared to the speech, resulting in a signal-to-noise-ratio (SNR) degradation. The integration of NR and DRC has not received a lot of attention so far. In this paper, a multi-channel Wiener filter (MWF)-based approach is presented for speech and noise scenarios, where an MWF-based NR algorithm is combined with DRC. The proposed solution is based on modifying the MWF and the DRC to incorporate the conditional speech presence probability in order to avoid residual noise amplification. The goal is then to analyse any undesired interaction effects by means of objective measures. Experimental results indeed confirm that a serial concatenation of NR and DRC degrades the SNR improvement provided by the NR, whereas the combined approach proposed here shows less degradation of the SNR improvement at a low increase in distortion compared to a serial concatenation. [Copyright &y& Elsevier]

Abstract: We propose a combination of the well-known generalized sidelobe canceller (GSC) or Griffiths–Jim beamformer, and the so-called PEM-AFROW algorithm for joint estimation under closed loop conditions of a room impulse response and a desired speech signal model, resulting in a system for multimicrophone combined acoustic feedback and noise cancellation. For specific applications (e.g. public address systems), the computational complexity may be reduced dramatically compared to state-of-the-art proactive acoustic feedback cancellers, while feedback cancellation performance is only marginally degraded. [Copyright &y& Elsevier]

Abstract: In many room acoustic signal processing applications, a room impulse response identification is needed to eliminate undesired effects such as echo, feedback, or reverberation. This is typically done using an adaptive filter driven by a speech or audio input signal. However, such signals exhibit poor excitation properties, which cause standard adaptive filtering algorithms to be very sensitive to disturbing signals, especially in the underdetermined case. A popular remedy is regularization, which is usually implemented with a scaled identity regularization matrix. This type of regularization is governed by a single regularization parameter, the value of which is often chosen in an arbitrary way. We propose to regularize the adaptive filter using a non-identity regularization matrix, in which prior knowledge on the unknown room impulse response may be incorporated. When knowledge of the disturbing signal is also used to add prefiltering and weighting in the adaptation, a new family of regularized adaptive filtering algorithms is obtained, which is shown to be optimal in a mean square error sense. Existing regularized algorithms can then be obtained as special cases, assuming limited or no prior knowledge is available. When combined with a recently proposed method of extracting prior knowledge from the acoustic setup, our algorithms exhibit superior convergence behaviour compared to existing algorithms in different simulation scenarios, while the additional computational cost is small. [Copyright &y& Elsevier]

Abstract: In modern DSL systems, crosstalk is a major source of performance degradation. Crosstalk cancellation techniques have been proposed to mitigate the effect of crosstalk. However, the run-time complexity of these crosstalk cancellation techniques grows with the square of the number of lines. Therefore one has to be selective in cancelling crosstalk to reduce complexity. Secondly, crosstalk cancellation requires signal-level coordination between transmitters or receivers, which is not always available. Because of accessibility constraints, crosstalk between certain lines cannot be cancelled and so has to be mitigated through spectrum management. After a complexity study, this paper presents a solution for the joint spectrum management and constrained partial crosstalk cancellation problem. The complexity of the partial crosstalk cancellation part of the problem is reduced based on a line selection and user independence observation. However, to fully benefit from these observations, power loading has to be applied in the spectrum management part. We therefore also consider ON/OFF power loading, which has a low complexity and shows only a minor performance degradation compared to normal power loading. The resulting algorithm will be compared to currently available algorithms for independent spectrum management and partial crosstalk cancellation. [Copyright &y& Elsevier]

Abstract: In modern DSL systems, multi-user crosstalk is a major source of performance degradation. Optimal spectrum balancing (OSB) is a centralized algorithm that mitigates the effect of crosstalk by allocating optimal transmit spectra to all interfering DSL modems. By the use of Lagrange multipliers the algorithm decouples the spectrum management problem into per-tone optimization problems. The remaining issues are then finding the Lagrange multipliers that enforce the constraints and solving the per-tone optimization problems. Finding the optimal Lagrange multipliers can become complex when more than two users are considered. Starting from the single-user case, this paper presents a number of properties, which are then extended to the multi-user case and lead to an efficient search algorithm for the Lagrange multipliers. Simulations show that the number of Lagrange multiplier evaluations is as small as 20–50, independent of the number of users. Secondly, the complexity of the per-tone optimization problems grows exponentially with the number of lines in the binder. For multiple-user scenarios this becomes computationally intractable. This paper presents an efficient branch-and-bound approach for the per-tone optimization problem. Simulations show enormous complexity reductions, especially for a large number of users. [Copyright &y& Elsevier]

Abstract: A user-friendly and versatile research platform for use in auditory experiments, referred to as APEX (Application for PsychoElectrical eXperiments), is described. The platform takes care of automatic stimulus presentation and collection of the subject''s responses. Acoustical auditory, as well as electrical auditory experiments with CI recipients can be conducted. The platform currently supports LAURA, Nucleus CI22 and Nucleus CI24 cochlear implants. The graphical user interface for the subjects has been extended to allow for testing very young children, by embedding the psychophysical procedures in a computer game. The research platform is available free of charge. [Copyright &y& Elsevier]

In this paper, we propose new time- and frequency-domain per-tone equalization techniques for orthogonal frequency division multiplexing (OFDM) transmission over time- and frequency-selective channels. We present one mixed time- and frequency-domain equalizer (MTFEQ) and one frequency-domain per-tone equalizer. The MTFEQ consists of a one-tap time-varying (TV) time-domain equalizer (TEQ), which converts the doubly selective channel into a purely frequency-selective channel, followed by a one-tap frequency-domain equalizer (FEQ), which then equalizes the resulting frequency-selective channel in the frequency-domain. The frequency-domain per-tone equalizer (PTEQ) is then obtained by transferring the TEQ operation to the frequency-domain. While the one-tap TEQ of the MTFEQ optimizes the performance on all subcarriers in a joint fashion, the PTEQ optimizes the performance on each subcarrier separately. This results into a significant performance improvement of the PTEQ over the MTFEQ, at the cost of a slight increase in complexity. Through computer simulations we show that the MTFEQ suffers from an early and high error floor, while the PTEQ outperforms the MMSE equalizer for OFDM over purely frequency-selective channels, it can approach the performance of the block MMSE equalizer. An important feature of the proposed techniques is that no bandwidth expansion or redundancy insertion is required except for the cyclic prefix. [Copyright &y& Elsevier]

Very high bit-rate digital subscriber line (VDSL) is the latest generation in the ongoing evolution of DSL standards. VDSL aims at bringing truly broadband access, greater than 52Mbps in the downstream, to the mass consumer market. This is achieved by transmitting in frequencies up to 12MHz. Operating at such high frequencies gives rise to crosstalk between the DSL systems in a binder, limiting achievable data-rates. Crosstalk is typically 10–15dB larger than other noise sources and is the primary limitation on performance in VDSL. In downstream transmission several crosstalk precompensation schemes have been proposed to address this issue. Whilst these schemes lead to large performance gains, they also have extremely high complexities, beyond the scope of current implementation.In this paper we develop the concept of partial crosstalk precompensation. The majority of the crosstalk experienced in a DSL system comes from only a few other lines within the binder. Furthermore its effects are limited to a small subset of tones. Partial precompensation exploits this by limiting precompensation to the tones and lines where it gives maximum benefit. As a result, these schemes achieve the majority of the gains of full crosstalk precompensation at a fraction of the run-time complexity. In this paper we develop several partial precompensation schemes. We show that with only 20% of the run-time complexity of full precompensation it is possible to achieve 80% of the performance gains. [Copyright &y& Elsevier]

An improved optimization algorithm for the time domain equalizer (TEQ) is developed for discrete multitone (DMT) based asymmetric digital subscriber line (ADSL). In contrast with existing algorithms, our algorithm explicitly disregards the unused tones in the cost function as well as in the non-triviality constraint. Simulation results are presented for the upstream channel. It is shown that the achievable bitrate is higher than for a popular existing algorithm. [Copyright &y& Elsevier]

In discrete multitone receivers, a time domain equalizer (TEQ) is used to shorten the channel impulse response, so that the equalized channel impulse response is shorter than the inserted prefix. The aim of this paper is to show that the minimum mean square error (MMSE) channel shortening problem with two different energy constraints, remarkably, lead to the same TEQ coefficients, up to a scaling factor. Moreover, implying the two energy constraints together in the MMSE optimization again yields the same result and comes down to a canonical correlation analysis between the subspace spanned by the transmitted samples and the received samples, respectively. Hence, the TEQ obtained by these three distinct MMSE cases yields the same performance in terms of bit rate. Since the resulting problem can easily be reformulated as a maximization problem, an iterative procedure based on power iterations can be devised to reduce the computational complexity. [Copyright &y& Elsevier]

We present a novel channel estimation technique based on discrete cosine transforms (DCT) for multicarrier and single carrier communications. Channel estimation is essential in communication systems, but especially in DCT-based transceivers for designing a front-end prefilter that must be included at the receiver to force the channel impulse response to be symmetric. The new technique is derived from the symmetric convolution-multiplication properties of discrete trigonometric transforms, and it is thus particularly suitable for DCT-based transceivers. The proposed channel estimation method is based on the use of training symbols, symmetric in time-domain, known by both transmitter and receiver. We demonstrate that by imposing a whole-sample symmetry condition in the training symbol, the channel impulse response can be estimated in a straightforward way. The analytical expressions to obtain the channel impulse response from the training symbol are also derived. Finally, this study is completed with several computer simulations to demonstrate the validity of the estimation technique. [ABSTRACT FROM AUTHOR]

Previous studies have shown that objective measures based on stimulation with low-rate pulse trains fail to predict the threshold levels of cochlear implant (CI) users for high-rate pulse trains, as used in clinical devices. Electrically evoked auditory steady-state responses (EASSRs) can be elicited by modulated high-rate pulse trains, and can potentially be used to objectively determine threshold levels of CI users. The responsiveness of the auditory pathway of profoundly hearing-impaired CI users to modulation frequencies is, however, not known. In the present study we investigated the responsiveness of the auditory pathway of CI users to a monopolar 500 pulses per second (pps) pulse train modulated between 1 and 100 Hz. EASSRs to forty-three modulation frequencies, elicited at the subject's maximum comfort level, were recorded by means of electroencephalography. Stimulation artifacts were removed by a linear interpolation between a pre- and post-stimulus sample (i.e., blanking). The phase delay across modulation frequencies was used to differentiate between the neural response and a possible residual stimulation artifact after blanking. Stimulation artifacts were longer than the inter-pulse interval of the 500 pps pulse train for recording electrodes ipsilateral to the CI. As a result the stimulation artifacts could not be removed by artifact removal on the bases of linear interpolation for recording electrodes ipsilateral to the CI. However, artifact-free responses could be obtained in all subjects from recording electrodes contralateral to the CI, when subject specific reference electrodes (Cz or Fpz) were used. EASSRs to modulation frequencies within the 30–50 Hz range resulted in significant responses in all subjects. Only a small number of significant responses could be obtained, during a measurement period of 5 min, that originate from the brain stem (i.e., modulation frequencies in the 80–100 Hz range). This reduced synchronized activity of brain stem responses in long-term severely-hearing impaired CI users could be an attribute of processes associated with long-term hearing impairment and/or electrical stimulation. [ABSTRACT FROM AUTHOR]

Abstract: This paper deals with the discrete multitone multiple input, multiple output interference channel (DMT MIMO IC) in DSL networks. The scenario consists of a number of users, each with a given number of transceivers, that share the same channel in multiple tones. Our goal is to maximize the weighted rate sum of the users subject to power constraints. A recent paper has treated this problem with per-user power constraints. In this paper we focus on per-transceiver power constraints. We propose two different algorithms. First, we straightforwardly adapt the previously proposed DMT-WMMSE algorithm. Second, we adapt the WMMSE-GDSB, in which we separate the problem in signal and spectrum coordination parts. For the spectrum coordination part, we show that the problem can be solved more efficiently with a change of variables: we use a coordinate system consisting of a radius and a direction vector with ℓ1 norm equal to 1. This can be interpreted as spherical coordinates in taxicab geometry. It is observed that for the radial dimension the problem can be made concave after approximations and it is thus easy to solve. The remaining dimensions are solved with a sequence of line searches. Simulation results show that the WMMSE-GDSB converges faster. [Copyright &y& Elsevier]

Abstract: A wireless sensor network is envisaged that performs signal estimation by means of the distributed adaptive node-specific signal estimation (DANSE) algorithm. This wireless sensor network has constraints such that only a subset of the nodes are used for the estimation of a signal. While an optimal node selection strategy is NP-hard due to its combinatorial nature, we propose a greedy procedure that can add or remove nodes in an iterative fashion until the constraints are satisfied based on their utility. With the proposed definition of utility, a centralized algorithm can efficiently compute each nodes's utility at hardly any additional computational cost. Unfortunately, in a distributed scenario this approach becomes intractable. However, by using the convergence and optimality properties of the DANSE algorithm, it is shown that for node removal, each node can efficiently compute a utility upper bound such that the MMSE increase after removal will never exceed this value. In the case of node addition, each node can determine a utility lower bound such that the MMSE decrease will always exceed this value once added. The greedy node selection procedure can then use these upper and lower bounds to facilitate distributed node selection. [Copyright &y& Elsevier]

Abstract: Acoustic feedback is a well-known problem in hearing aids, caused by the undesired acoustic coupling between the hearing aid loudspeaker and microphone. Acoustic feedback produces annoying howling sounds and limits the maximum achievable hearing aid amplification. This paper is focused on adaptive feedback cancellation (AFC) where the goal is to adaptively model the acoustic feedback path and estimate the feedback signal, which is then subtracted from the microphone signal. The main problem in identifying the acoustic feedback path model is the correlation between the near-end signal and the loudspeaker signal caused by the closed signal loop, in particular when the near-end signal is spectrally colored as is the case for a speech signal. This paper adopts a prediction-error method (PEM)-based approach to AFC, which is based on the use of decorrelating prediction error filters (PEFs). We propose a number of improved PEF designs that are inspired by harmonic sinusoidal modeling and pitch prediction of speech signals. The resulting PEM-based AFC algorithms are evaluated in terms of the maximum stable gain (MSG), filter misadjustment, and computational complexity. Simulation results for a hearing aid scenario indicate an improvement up to 5–7dB in MSG and up to 6–8dB in terms of filter misadjustment. [Copyright &y& Elsevier]

Abstract: In this paper, we present an iterative method for estimation of pitches from signals containing multiple sources using subspace techniques. The resulting estimator is termed Iterative Harmonic MUltiple SIgnal Classification (I-HMUSIC). Different modifications of I-HMUSIC are proposed that improve upon the classical MUSIC algorithm, including a computationally efficient method for noise subspace updating I-HMUSIC and its modifications are evaluated and compared with both the Cramér–Rao lower bound (CRLB) and non-iterative HMUSIC; good statistical performances have been obtained. [Copyright &y& Elsevier]

Abstract: The possibilities of currently commercially available auditory steady-state response (ASSR) devices are mostly limited to avoid unintentional misuse and to guarantuee patient safety as such. Some setups, e.g. do not allow the application of high intensities or the use of own stimuli. Moreover, most devices generally only allow data collection using maximal two EEG channels. The freedom to modify and extend the accompagnying software and hardware is very restricted or inexistent. As a result, these devices are not suited for research and several clinically diagnostic purposes. In this paper, a research platform for multi-channel ASSR measurements is presented, referred to as SOMA (setup ORL for multi-channel ASSR). The setup allows multi-channel measurements and the use of own stimuli. It can be easily extended to facilitate new measurement protocols and real-time signal processing. The mobile setup is based on an inexpensive multi-channel RME soundcard and software is written in C++. Both hardware and software of the setup are described. An evaluation study with nine normal-hearing subjects shows no significant performance differences between a reference and the proposed platform. SOMA presents a flexible and modularly extensible mobile high-end multi-channel ASSR test platform. [Copyright &y& Elsevier]

Abstract: Recently, a generalized multi-microphone noise reduction scheme, referred to as the spatially pre-processed speech distortion weighted multichannel Wiener filter (SP-SDW-MWF), has been presented. This scheme consists of a fixed spatial pre-processor and a multichannel adaptive noise canceler (ANC) optimizing the SDW-MWF cost function. By taking speech distortion explicitly into account in the design criterion of the multichannel ANC, the SP-SDW-MWF adds robustness to the standard generalized sidelobe canceler (GSC). In this paper, we present a multichannel frequency-domain criterion for the SDW-MWF, from which several – existing and novel – adaptive frequency-domain algorithms can be derived. The main difference between these adaptive algorithms consists in the calculation of the step size matrix (constrained vs. unconstrained, block-structured vs. diagonal) used in the update formula for the multichannel adaptive filter. We investigate the noise reduction performance, the robustness and the tracking performance of these adaptive algorithms, using a perfect voice activity detection (VAD) mechanism and using an energy-based VAD. Using experimental results with a small-sized microphone array in a hearing aid, it is shown that the SP-SDW-MWF is more robust against signal model errors than the GSC, and that the block-structured step size matrix gives rise to a faster convergence and a better tracking performance than the diagonal step size matrix, only at a slightly higher computational cost. [Copyright &y& Elsevier]

Abstract: In a previous paper, we proposed a bitrate maximizing design criterion for time-domain equalizers (TEQ) in DMT transceivers to shorten the channel impulse response, as needed in, e.g., ADSL receivers. The proposed criterion truly maximizes the bitrate, as it is based on an exact formulation of the subchannel SNR as a function of the TEQ taps. In this paper, we show how the BM-TEQ design can be used in a bitrate maximizing per group equalizer (BM-PGEQ): the active tones are divided into groups and each group is provided with a bitrate maximizing equalizer. This BM-PGEQ design allows for a trade-off between memory requirement and performance, keeping computational complexity during data transmission roughly at the same level. It encompasses the BM-TEQ design and the so-called per tone equalization scheme (PTEQ) as extreme cases. We also present an adaptation algorithm to design the BM-TEQ and BM-PGEQ. Through simulation, we show that the BM-PGEQ scheme outperforms an earlier presented tone grouping scheme where the whole tone group was assigned the PTEQ of the group center tone. The BM-PGEQ scheme appears as a useful intermediate between BM-TEQ and PTEQ and closely approaches the PTEQ performance for as few as four tone groups in an ADSL scenario, even in harsh environments with narrowband interference and crosstalk. [Copyright &y& Elsevier]

Abstract: In this paper, a physical and perceptual evaluation of two adaptive noise reduction algorithms for dual-microphone hearing aids are described. This is the first comparison between a fixed directional microphone on the one hand, and an adaptive directional microphone and an adaptive beamformer on the other hand, all implemented in the same digital hearing aid. The adaptive directional microphone is state-of-the-art in most modern commercial hearing aids. The physical evaluation shows the importance of an individual calibration procedure for the performance of the noise reduction algorithms with two microphone hearing aids. The directivity index calculated in anechoic conditions and intelligibility-weighted polar diagrams measured in reverberant conditions show that all the noise reduction strategies yield an improved signal-to-noise ratio (SNR), but that the adaptive beamformer generally performs best. From the perceptual evaluation, it is demonstrated that the adaptive beamformer always performs best in single noise source scenarios. In a more complex noise scenario, there is still a SNR improvement with all the techniques, however the effect is the same for all the strategies. [Copyright &y& Elsevier]

Abstract: In this report, a novel technique is described for the combination of per-tone equalization (PTEQ) with receiver windowing. The PTEQ is an equalization technique for discrete multitone modulation (DMT) based modems, such as asymmetric digital subscriber line (ADSL) modems and very high bitrate digital subscriber line (VDSL) modems, optimizing the SNR (and thus capacity) of each carrier separately. Windowing functions are very useful in multitone communications systems, to prevent a narrow band noise source from causing wide band interference. Combining both techniques in a windowed PTEQ (referred to as WiPTEQ) leads to a robust communication system. The described technique is especially useful in case of a trapezoidal or raised cosine window, and when the window taper length is large compared to the number of equalizer filter taps. [Copyright &y& Elsevier]