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Presents information on a study which described a multiuser interference (MUI)-free receiver for a synchronous direct-sequence code-division multiple access system based on block spreading in the presence of frequency-selective fading. Complexity of the MUI-free receiver; Comparison of the performance of the MUI-free receiver with the performance of the linear multiuser equalizer; Conclusions.

Presents a study which discussed the minimum variance distortionless response beamforming algorithm. Application of the algorithm to least-square problems; Conclusion.

Presents information on a study that analyzed a class of continuous-time subspace tracking algorithms related to a number of discrete-time algorithms such as stochastic gradient algorithm, spherical subspace trackers and discrete-time algorithm. Information on principal component analysis and subspace tracking; Class of subspace tracking algorithms considered in the study; Overview of a formula for tracking the singular value decomposition.

Proposes a stochastic gradient algorithm for principal component analysis and subspace tracking. Achievement of a low computational cost by recasting the orthogonalization step of the algorithm; Derivation of parallel implementation and problem-size independent throughput; Need for improvement on the algorithm.

Describes a systolic algorithm and array for recursive least squares (RLS) estimation. Generic Jacobi-type array for SVD updating and other algorithms; RLS revisited; Directionally weighted RLS; Conclusion.

Explains how the factorization of orthogonal matrices will play an important role in modern digital signal processing. The orthogonality of the estimated eigenvector matrix is known to be crucial for the numerical stability of the recursive algorithms; Factorization of an orthogonal matrix; Updating the parameterization; Conclusion.

• 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]

Background: Although for most cochlear implant (CI) users good speech understanding is reached (at least in quiet environments), the perception and the appraisal of music are generally unsatisfactory. Purpose: The improvement in music appraisal was evaluated in CI participants by using a stereo music preprocessing scheme implemented on a take-home device, in a comfortable listening environment. The preprocessing allowed adjusting the balance among vocals/bass/drums and other instruments, and was evaluated for different genres of music. The correlation between the preferred settings and the participants' speech and pitch detection performance was investigated. Research Design: During the initial visit preceding the take-home test, the participants' speech-in-noise perception and pitch detection performance were measured, and a questionnaire about their music involvement was completed. The take-home device was provided, including the stereo music preprocessing scheme and seven playlists with six songs each. The participants were asked to adjust the balance by means of a turning wheel to make the music sound most enjoyable, and to repeat this three times for all songs. Study Sample: Twelve postlingually deafened CI users participated in the study. Data Collection and Analysis: The data were collected by means of a take-home device, which preserved all the preferred settings for the different songs. Statistical analysis was done with a Friedman test (with post hoc Wilcoxon signed-rank test) to check the effect of "Genre." The correlations were investigated with Pearson's and Spearman's correlation coefficients. Results: All participants preferred a balance significantly different from the original balance. Differences across participants were observed which could not be explained by perceptual abilities. An effect of "Genre" was found, showing significantly smaller preferred deviation from the original balance for Golden Oldies compared to the other genres. Conclusions: The stereo music preprocessing scheme showed an improvement in music appraisal with complex music and hence might be a good tool for music listening, training, or rehabilitation for CI users. [ABSTRACT FROM AUTHOR]

Dynamic spectrum management (DSM) refers to a wide range of techniques for counteracting crosstalk in digital subscriber line (DSL) networks. DSM is categorized into three levels based on the degree of coordination among users. In this article, we investigate optimal joint level 2 and 3 DSM for upstream DSL. We will discuss the difficulties of finding the universally optimal solution and we propose an optimal algorithm, referred to as IF/MAC-OSB, under some practical and implementation assumptions for this problem. Using computer simulations, we show that IF/MAC-OSB is capable of increasing the user bit rates considerably compared to several other DSM techniques. The proposed algorithm involves using the minimum mean squared error (MMSE)-generalized decision feedback equalizer (GDFE) together with Lagrange dual optimization. We address several aspects of the problem including the optimal decoding order in the GDFE receiver, GDFE error propagation, and the computational complexity of the algorithm. We also study effects of channel model randomness and upstream power back-off utilization on the performance of the algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we address the problem of distributed adaptive estimation of node-specific signals for signal enhancement or noise reduction in wireless sensor networks with multi-sensor nodes. The estimation is performed by a multi-channel Wiener filter (MWF) in which a low-rank approximation based on a generalized eigenvalue decomposition (GEVD) is incorporated. In non-stationary or low-SNR conditions, this GEVD-based MWF has been demonstrated to be more robust than the original MWF. In a centralized realization where a fusion center has access to all the nodes’ sensor signal observations, the network-wide sensor signal correlation matrices and the low-rank approximation can be directly estimated and used to compute the network-wide GEVD-based MWF. However, in this paper, we aim to avoid centralizing the sensor signal observations, in which case the network-wide sensor signal correlation matrices cannot be estimated. To this end, we start from the so-called distributed adaptive node-specific signal estimation (DANSE) algorithm, and include GEVD-based low-rank approximations in the per-node local computations. Remarkably, the new algorithm is able to significantly compress the signal observations transmitted between the nodes, while still converging to the network-wide GEVD-based MWF as if each node would have access to all sensor signal observations, even though the low-rank approximations are applied locally at each node. We provide a theoretical convergence analysis, which shows that the algorithm converges to the network-wide GEVD-based MWF under conditions that are less strict than in the original DANSE algorithm. The convergence and performance of the algorithm are further investigated via numerical simulations. [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]

Objective: Music perception and appraisal are generally poor in cochlear implant recipients. Simple musical structures, lyrics that are easy to follow, and clear rhythm/beat have been reported among the top factors to enhance music enjoyment. The present study investigated the preference for modified relative instrument levels in music with normal-hearing and cochlear implant subjects. Design: In experiment 1, test subjects were given a mixing console and multi-track recordings to determine their most enjoyable audio mix. In experiment 2, a preference rating experiment based on the preferred relative level settings in experiment 1 was performed. Study sample: Experiment 1 was performed with four postlingually deafened cochlear implant subjects, experiment 2 with ten normal-hearing and ten cochlear implant subjects. Results: A significant difference in preference rating was found between normal-hearing and cochlear implant subjects. The latter preferred an audio mix with larger vocals-to-instruments ratio. In addition, given an audio mix with clear vocals and attenuated instruments, cochlear implant subjects preferred the bass/drum track to be louder than the other instrument tracks. Conclusions: The original audio mix in real-world music might not be suitable for cochlear implant recipients. Modifying the relative instrument level settings potentially improves music enjoyment. [ABSTRACT FROM AUTHOR]

Dynamic spectrum management is recognized as a key technique to tackle interference in multi-user multi-carrier communication systems and networks. However existing dynamic spectrum management algorithms may not be suitable when the available computation time and compute power are limited, i.e., when a very fast responsiveness is required. In this paper, we present a new paradigm, theory and algorithm for real-time dynamic spectrum management (RT-DSM). Specifically, a RT-DSM algorithm is real-time in the sense that it can be stopped at any point in time while guaranteeing a feasible and improved solution. This is enabled by the introduction of a novel difference-of-variables (DoV) transformation and problem reformulation, for which a primal coordinate ascent approach is proposed with exact line search via a logarithmically-scaled grid search. The proposed algorithm is referred to as iterative power difference balancing (IPDB). Simulations for different realistic wireline and wireless interference-limited systems demonstrate its good performance, low complexity and wide applicability under different configurations. [ABSTRACT FROM PUBLISHER]

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]

Cochlear implant (CI) recipients report severe degradation of speech understanding under noisy conditions. Most CI recipients typically can require about 10–25 dB higher signal-to-noise ratio than normal hearing (NH) listeners in order to achieve similar speech understanding performance. In recent years, significant emphasis has been put on binaural algorithms, which not only make use of the head shadow effect, but also have two or more microphone signals at their disposal to generate binaural inputs. Most of the CI recipients today are unilaterally implanted but they can still benefit from the binaural processing utilizing a contralateral microphone. The phase error filtering (PEF) algorithm tries to minimize the phase error variance utilizing a time–frequency mask for noise reduction. Potential improvement in speech intelligibility offered by the algorithm is evaluated with four different kinds of mask functions. The study reveals that the PEF algorithm which uses a contralateral microphone but unilateral presentation provides considerable improvement in intelligibility for both NH and CI subjects. Further, preference rating test suggests that CI subjects can tolerate higher levels of distortions than NH subjects, and therefore, more aggressive noise reduction for CI recipients is possible. [ABSTRACT FROM PUBLISHER]

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]

Users of a cochlear implant and contralateral hearing aid are sensitive to interaural level differences (ILDs). However, when using their clinical devices, most of these subjects cannot use ILD cues for localization in the horizontal plane. This is partly due to a lack of high-frequency residual hearing in the acoustically stimulated ear. Using acoustic simulations of a cochlear implant and hearing loss, it is shown that localization performance can be improved by up to 14° rms error relative to 48° rms error for broadband noise by artificially introducing ILD cues in the low frequencies. The algorithm that was used for ILD introduction is described. [ABSTRACT FROM AUTHOR]

Auditory steady-state responses (ASSRs) are used for hearing threshold estimation at audiometric frequencies. Hearing impaired newborns, in particular, benefit from this technique as it allows for a more precise diagnosis than traditional techniques, and a hearing aid can be better fitted at an early age. However, measurement duration of current single-channel techniques is still too long for clinical widespread use. This paper evaluates the practical performance of a multi-channel electroencephalogram (EEG) processing strategy based on a detection theory approach. A minimum electrode set is determined for ASSRs with frequencies between 80 and 110 Hz using eight-channel EEG measurements of ten normal-hearing adults. This set provides a near-optimal hearing threshold estimate for all subjects and improves response detection significantly for EEG data with numerous artifacts. Multi-channel processing does not significantly improve response detection for EEG data with few artifacts. In this case, best response detection is obtained when noise-weighted averaging is applied on single-channel data. The same test setup (eight channels, ten normal-hearing subjects) is also used to determine a minimum electrode setup for 10-Hz ASSRs. This configuration allows to record near-optimal signal-to-noise ratios for 80% of subjects. [ABSTRACT FROM AUTHOR]

Modern digital subscriber line (DSL) networks suffer from crosstalk among different lines in the same cable bundle. This crosstalk can lead to a major performance degradation. By balancing the transmit power spectra, the impact of crosstalk can be minimized leading to spectacular performance gains. This is referred to as spectrum management. In this paper, a unifying perspective is presented on distributed spectrum management algorithms based on the Karush-Kuhn-Tucker (KKT) conditions. Furthermore, novel distributed algorithms are presented within the same KKT framework. The proposed distributed algorithms consist of local water-filling-like algorithms running in the individual modems, controlled by the spectrum management center. Extensive simulation results show that the proposed algorithms perform very well for several multi-user ADSL and VDSL scenarios. [ABSTRACT FROM AUTHOR]

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]

Over the last decade, the detection of auditory steady-state responses (ASSR) has been developed for reliable hearing threshold estimation at audiometric frequencies. Unfortunately, the duration of ASSR measurement can be long, which is unpractical for wide scale clinical application. In this paper, we propose independent component analysis (ICA) as a tool to improve the ASSR detection in recorded single-channel as well as multichannel electroencephalogram (EEG) data. We conclude that ICA is able to reduce measurement duration significantly. For a multichannel implementation, near-optimal performance is obtained with five-channel recordings. [ABSTRACT FROM AUTHOR]

Binaural hearing aids use microphone inputs from both the left and right hearing aid to generate an output for each ear. On the other hand, a monaural hearing aid generates an output by processing only its own microphone inputs. This correspondence presents a binstural extension of a monaural multichannel noise reduction algorithm for hearing aids based on Wiener filtering. In addition to significantly suppressing the noise interference, the algorithm preserves the interaural time delay (ITD) cues of the speech component, thus allowing the user to correctly localize the speech source. Unfortunately, binaural multichannel Wiener filtering distorts the ITD cues of the noise source. By adding a parameter :o the cost function the amount of noise reduction performed by the algorithm can be controlled, and traded off for the preservation of the noise ITO cues. [ABSTRACT FROM AUTHOR]

Crosstalk is a major issue in modern digital subscriber line (DSL) systems such as ADSL and VDSL. Static spectrum management, which is the traditional way of ensuring spectral compatibility, employs spectral masks that can be overly conservative and lead to poor performance. This paper presents a centralized algorithm for optimal spectrum balancing in DSL. The algorithm uses the dual decomposition method to optimize spectra in an efficient and computationally tractable way. The algorithm shows significant performance gains over existing dynamis spectrum management (DSM) techniques, e.g., in one of the cases studied, the proposed centralized algorithm leads to a factor-of-four increase in data rate over the distributed DSM algorithm iterative waterfilling. [ABSTRACT FROM AUTHOR]

In this paper, we propose a time-domain as well as a frequency-domain per-tone equalization for orthogonal frequency-division multiplexing (OFDM) over doubly selective channels. We consider the most general case, where the channel delay spread is larger than the cyclic prefix (CP), which results in interblock interference (IBI). IBI in conjunction with the Doppler effect destroys the orthogonality between subcarriers and, hence, results in severe intercarrier interference (Id). In this paper, we propose a time-varying finite-impulse-response (TV-FIR) time-do-main equalizer (TEQ) to restore the orthogonality between subcarriers, and hence to eliminate ICIIIBI. Due to the fact that the TEQ optimizes the performance over all subcarriers in a joint fashion, it has a poor performance. An optimal frequency-domain per-tone equalizer (PTEQ) is then obtained by transferring the TEQ operation to the frequency domain. Through computer simulations, we demonstrate the performance of the proposed equalization techniques. [ABSTRACT FROM AUTHOR]

This paper considers the situation where users that experience high-mobility transmit data over frequency-selective channels, resulting in a doubly selective channel model (i.e., time- and frequency-selective channels) and this within the framework of Known Symbol Padding (KSP) transmission. KSP is a recently proposed block transmission technique where short sequences of known symbols acting as, guard bands are inserted between successive blocks of data symbols. This paper proposes three novel channel estimation methods that allow for an accurate estimation of the time-varying transmission channel solely relying on the knowledge of the redundant symbols introduced by the KSP transmission scheme. The first method is a direct adaptive one while the others rely on a recently proposed model, the Basis Expansion Model (BEM), where the doubly selective channel is approximated with high accuracy using a limited number of complex exponentials. An important characteristic of the proposed methods is that they exploit all the received symbols that contain contributions from the training sequences and blindly filter out the contribution of the unknown surrounding data symbols. Besides these channel identification methods, the classical KSP equalizers are adapted to the context of doubly selective channels, which allows evaluation of the bit-error-rate (BER) performance of a KSP transmission system relying on the proposed channel estimation methods in the context of doubly selective channels. Simulation results show that KSP transmission is indeed a suitable transmission technique toward the delivery of high data rates to users experiencing a high mobility, when adapted KSP equalizers are used in combination with the proposed channel estimation methods. [ABSTRACT FROM AUTHOR]

This paper studies the effect of bilateral hearing aids on directional hearing in the frontal horizontal plane. Localization tests evaluated bilateral hearing aid users using different stimuli and different noise scenarios. Normal hearing subjects were used as a reference. The main research questions raised in this paper are: (i) How do bilateral hearing aid users perform on a localization task, relative to normal hearing subjects? (ii) Do bilateral hearing aids preserve localization cues, and (iii) Is there an influence of state of the art noise reduction algorithms, more in particular an adaptive directional microphone configuration, on localization performance? The hearing aid users were tested without and with their hearing aids, using both a standard omnidirectional microphone configuration and an adaptive directional microphone configuration. The following main conclusions are drawn. (i) Bilateral hearing aid users perform worse than normal hearing subjects in a localization task, although more than one-half of the subjects reach normal hearing performance when tested unaided. For both groups, localization performance drops significantly when acoustical scenarios become more complex. (ii) Bilateral, i.e., independently operating hearing aids do not preserve localization cues. (iii) Overall, adaptive directional noise reduction can have an additional and significant negative impact on localization performance. [ABSTRACT FROM AUTHOR]

Music perception and appraisal is very poor in cochlear implant (CI) subjects partly because (musical) pitch is inadequately transmitted by the current clinically used sound processors. A new sound processing scheme (F0mod) was designed to optimize pitch perception, and its performance for music and pitch perception was compared in four different experiments to that of the current clinically used sound processing scheme (ACE) in six Nucleus CI24 subjects. In the F0mod scheme, slowly varying channel envelopes are explicitly modulated sinusoidally at the fundamental frequency (F0) of the input signal, with 100% modulation depth and in phase across channels to maximize temporal envelope pitch cues. The results of the four experiments show that: (1) F0 discrimination of single-formant stimuli was not significantly different for the two schemes, (2) F0 discrimination of musical notes of five instruments was three times better with the F0mod scheme for F0 up to 250 Hz, (3) melody recognition of familiar Flemish songs (with all rhythm cues removed) was improved with the F0mod scheme, and (4) estimates of musical pitch intervals, obtained in a musically trained CI subject, matched more closely the presented intervals with the F0mod scheme. These results indicate that explicit F0 modulation of the channel envelopes improves music perception in CI subjects. Copyright © 2006 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

The standard continuous adaptation feedback cancellation algorithm for feedback suppression in hearing aids suffers from a large model error or bias if the received sound signal is spectrally colored. To reduce the bias in the feedback path estimate, we propose adaptive feedback cancellation techniques that are based on a closed-loop identification of the feedback path as well as the (auto-regressive) modeling of the desired signal. In general, both models are not simultaneously identifiable in the closed-loop system at hand. We show that—under certain conditions, e.g., if a delay is inserted in the forward path—identification of both models is indeed possible. Two classes of adaptive procedures for identifying the desired signal model and the feedback path are derived: a two-channel identification method as well as a prediction error method. In contrast to the two-channel identification method, the prediction error method allows use of different adaptation schemes for the feedback path and for the desired signal model and, hence, is found to be preferable for highly non-stationary sound signals. Simulation results demonstrate that the proposed techniques outperform the standard continuous adaptation algorithm if the conditions for identifiability are satisfied. [ABSTRACT FROM AUTHOR]

In this paper, the first real-time implementation and perceptual evaluation of a singular value decomposition (SVD)-based optimal filtering technique for noise reduction in a dual microphone behind-the-ear (BTE) hearing aid is presented. This evaluation was carried out for a speech weighted noise and multitalker babble, for single and multiple jammer sound source scenarios. Two basic microphone configurations in the hearing aid were used. The SVD-based optimal filtering technique was compared against an adaptive beamformer, which is known to give significant improvements in speech intelligibility in noisy environment. The optimal filtering technique works without assumptions about a speaker position, unlike the two-stage adaptive beamformer. However this strategy needs a robust voice activity detector (VAD). A method to improve the performance of the VAD was presented and evaluated physically. By connecting the VAD to the output of the noise reduction algorithms, a good discrimination between the speech-and-noise periods and the noise-only periods of the signals was obtained. The perceptual experiments demonstrated that the SVD-based optimal filtering technique could perform as well as the adaptive beamformer in a single noise source scenario, i.e., the ideal scenario for the latter technique, and could outperform the adaptive beamfonner in multiple noise source scenarios. [ABSTRACT FROM AUTHOR]

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]

This paper describes a least squares (LS) channel estimation scheme for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems based on pilot tones. We first compute the mean square error (MSE) of the LS channel estimate. We then derive optimal pilot sequences and optimal placement of the pilot tones with respect to this MSE. It is shown that the optimal pilot sequences are equipowered, equispaced, and phase shift orthogonal. To reduce the training overhead, an LS channel estimation scheme over multiple OFDM symbols is also discussed. Moreover, to enhance channel estimation, a recursive LS (RLS) algorithm is proposed, for which we derive the optimal forgetting or tracking factor. This factor is found to be a function of both the noise variance and the channel Doppler spread. Through simulations, it is shown that the optimal pilot sequences derived in this paper outperform both the orthogonal and random pilot sequences. It is also shown that a considerable gain in signal-to-noise ratio (SNR) can be obtained by using the RLS algorithm, especially in slowly time-varying channels. [ABSTRACT FROM AUTHOR]

Per-tone equalization has recently been proposed as an alternative receiver structure for discrete multitone-based systems improving upon the well-known structure based on time-domain equalization. Fast initialization of all the equalizer coefficients has been identified as an open problem. In this letter, a recursive initialization scheme based on recursive least squares with inverse updating is presented for the per-tone equalizers. Simulation results show convergence with an acceptably small number of training symbols. Complexity calculations are made for per-tone equalization and for the case where tones are grouped. It is demonstrated with an example that in the latter case, initialization complexity becomes sufficiently low and comparable to complexity during data transmission. [ABSTRACT FROM AUTHOR]

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]

In this paper, an efficient computational scheme is proposed to calculate the symbol mean and variance from bit a priori information, when a so-called multilinear mapping is employed. The multilinear mapping is exploited to reduce the number of the terms needed for the calculation of the symbol mean and variance. [ABSTRACT FROM AUTHOR]

In next-generation digital subscriber line networks such as G.fast, employing discrete multi-tone transmission in high frequencies up to 212 MHz, the crosstalk among lines reaches very high levels. To precompensate the crosstalk in downstream transmission, QRD-based precoding has been proposed as a near-optimal dynamic spectrum management (DSM) technique. However, the performance of QRD-based precoding is greatly affected by the user encoding ordering (UEO). Since current multi-tone UEO methods are rather heuristic in the way they approach fairness, we develop, in this paper, a set of novel DSM algorithms for joint power allocation and UEO that enforce a generalized $ \alpha $ -fairness policy. Since finding the globally optimal UEO entails a combinatorial optimization problem with excessive computational complexity, an iterative algorithm is proposed which uses per-tone exhaustive searches (PTESs) and provides near-optimal approximate solutions. To further reduce the computational complexity, two suboptimal methods are suggested to replace the expensive PTESs, leading to two additional $ \alpha $ -fair DSM algorithms that are tractable for large scenarios against little performance loss. Simulations of a G.fast cable binder show that the $ \alpha $ -fair DSM algorithms achieve an efficient trade-off between fairness and performance in contrast to current UEO methods. [ABSTRACT FROM AUTHOR]

Diffusion adaptation techniques have shown great promise in addressing the problem of node-specific distributed estimation where the nodes in the network are interested in different, possibly overlapping, sets of parameters. In this work, node-specific distributed detection, which has remained largely unexamined, is considered. In particular, the problem is formulated as one of binary hypothesis testing at each node for each of its parameters of interest. A distributed, online solution for this problem is sought based on diffusion adaptation techniques. In this setting, a signal to be detected by one node constitutes interference that may compromise the ability of the other nodes to detect their signals of interest reliably. Under mild assumptions on the data and network, it is shown that, for sufficiently small adaptation step-sizes, interference can be kept in check. Local detectors are developed where the test-statistics and thresholds adapt to changing conditions in real time. The distributed algorithm is analyzed; and its detection performance characterized and illustrated through numerical simulations. [ABSTRACT FROM AUTHOR]

The 1000-fold capacity increase envisioned by dense 5G networks results also in a tremendous increase in the energy consumption of the whole network. Utilizing relays in combination with physical-layer network coding (PNC) has been proposed as an energy-efficient solution to this problem by creating several short-distance low-power transmissions and by reducing the transmission time. However, deploying relay nodes can be very costly for dense networks. On the other hand, the proximity of transmitting nodes in dense networks allows the transmitting nodes to serve as relays and retransmit the signals overheard from other transmitting nodes using PNC. This approach has been shown to increase the spectral efficiency, but the impact on energy efficiency has not been studied yet. Therefore, in this paper, we analyze two approaches that exploit the overhearing capabilities of the transmitting nodes in terms of spectral efficiency, energy efficiency, and success rate. We then provide a low-complexity power control strategy that achieves a performance close to the optimal for each approach. We show that when at least one indirect link is stronger than the direct links, exploiting the overhearing capabilities of the transmitting nodes provides the highest performance in both the transmit power-dominated and circuit power-dominated regimes. [ABSTRACT FROM AUTHOR]

In the G.fast digital subscriber line frequency range (up to 106 or 212 MHz), where crosstalk channels may even become larger than direct channels, linear zero-forcing (ZF) precoding is no longer near-optimal for downstream (DS) vectored transmission. To improve performance, we develop a novel low-complexity algorithm for both linear and nonlinear precoding-based dynamic spectrum management that maximizes the weighted sum-rate under realistic per-line total power and per-tone spectral mask constraints. It applies to DS scenarios with a single copper line at each customer site [i.e., broadcast channel (BC) scenarios], as well as to DS scenarios with multiple copper lines at some or all customer sites (i.e., the so-called multiple-input-multiple-output-BC scenarios). The algorithm alternates between precoder and equalizer optimization, where the former relies on a Lagrange multiplier based transformation of the DS dual decomposition approach formulation into its dual upstream (US) formulation, together with a low-complexity iterative fixed-point formula to solve the resulting US problem. Simulations with measured G.fast channel data of a very high crosstalk cable binder are provided revealing a significantly improved performance of this algorithm over ZF techniques for various scenarios, and in addition, a faster convergence rate compared with the state-of-the-art WMMSE algorithm. [ABSTRACT FROM AUTHOR]

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]

Subjective audio quality evaluation experiments have been conducted to assess the performance of embedded-optimization-based precompensation algorithms for mitigating perceptible linear and nonlinear distortion in audio signals. It is concluded with statistical significance that the perceived audio quality is improved by applying an embeddedoptimization- based precompensation algorithm, both in case (i) nonlinear distortion and (ii) a combination of linear and nonlinear distortion is present. Moreover, a significant positive correlation is reported between the collected subjective and objective PEAQ audio quality scores, supporting the validity of using PEAQ to predict the impact of linear and nonlinear distortion on the perceived audio quality. [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]

Objective: Listening to music is still one of the more challenging aspects of using a cochlear implant (CI) for most users. Simple musical structures, a clear rhythm/beat, and lyrics that are easy to follow are among the top factors contributing to music appreciation for CI users. Modifying the audio mix of complex music potentially improves music enjoyment in CI users. Methods: A stereo music preprocessing scheme is described in which vocals, drums, and bass are emphasized based on the representation of the harmonic and the percussive components in the input spectrogram, combined with the spatial allocation of instruments in typical stereo recordings. The scheme is assessed with postlingually deafened CI subjects (N = 7) using pop/rock music excerpts with different complexity levels. Results: The scheme is capable of modifying relative instrument level settings, with the aim of improving music appreciation in CI users, and allows individual preference adjustments. The assessment with CI subjects confirms the preference for more emphasis on vocals, drums, and bass as offered by the preprocessing scheme, especially for songs with higher complexity. Conclusion: The stereo music preprocessing scheme has the potential to improve music enjoyment in CI users by modifying the audio mix in widespread (stereo) music recordings. Significance: Since music enjoyment in CI users is generally poor, this scheme can assist the music listening experience of CI users as a training or rehabilitation tool. [ABSTRACT FROM PUBLISHER]