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In cell-free massive multiple-input multiple-output systems, a large number of distributed wireless access points (AP) simultaneously serve a number of user equipments (UEs). This setup has recently been introduced as a promising alternative for the current 5G cellular networks. The setup has the ability to offer a good quality of service, especially for the UEs on the cell edges, be it that there is still a need for low-complexity signal processing algorithms. In this paper, the problem of optimal power allocation combined with uplink receive combining and downlink transmit precoding is tackled by providing efficient distributed MMSE-based algorithms. The necessary fronthaul communications to estimate the combining/precoding vectors and the necessary large-scale channel statistics are reduced to a minimum and rely on in-network summation that can be accomplished whenever the APs can be arranged into a tree-topology. Non-weighted max-sum and max–min are used as utilities for the power allocation, but the algorithms are not limited to these cases. Simulations show that the proposed algorithms outperform heuristic power allocation methods, both in uplink and downlink. [ABSTRACT FROM AUTHOR]

We consider nonlinear zero-forcing (ZF) precoding design to improve the downstream G.fast peak-rates when only a few users in the cable binder are active. In order to compute the optimal nonlinear ZF precoder under per-line power constraints (PLPCs), we present a novel low-complexity dual decomposition algorithm, in which the key is the use of Lagrange multiplier based virtual precoders to transform the PLPCs into an easier virtual sum-power constraint (SPC), such that the SPC-optimality of the QR decomposition-based precoder may be exploited. We show a reduced computational complexity of this algorithm over the state-of-the-art SVD-block-diagonalization-based dual decomposition algorithm. We present simulations of a 10-line cable binder that demonstrate substantial peak-rate gains over standard QR decomposition-based ZF precoding in DSL, due to the increasingly stronger crosstalk channels in the G.fast frequency range (up to 212 MHz). Furthermore, we show that the proposed algorithm naturally extends to the scenario with multiple lines terminating at the customer premise equipments. [ABSTRACT FROM AUTHOR]

This paper focuses on the equalization of block transmissions with zero pad (ZP). If the channel impulse response length does not exceed the ZP length, it is possible to construct zero-forcing equalizers (ZFEs). Improved performance may be achieved using a minimum mean squared error (MMSE) equalizer. However, these equalizers are computationally intensive when a time-domain implementation is used. While the frequency-domain implementation of a ZFE has a lower complexity, it is prone to-potentially infinite-noise enhancement in the presence of spectral zeros. The MMSE equalizer in the frequency domain performs better by limiting the noise enhancement but still loses all information stored at the spectral zeros. This paper presents a method to exploit the redundancy of the padding to recover this lost information, leading to two new frequency-domain equalizers, a ZFE and an MMSE-like equalizer. These two equalizers are evaluated through simulations. They have a performance close to the time-domain equalizers, while maintaining the low complexity of the original frequency-domain equalizers. The equalizers are especially useful for scenarios with a high signal-to-noise ratio (SNR), where the performance is not limited by the presence of noise, but by the absence of the information stored in the spectral zeros. In practice, this means an SNR >30 dB. With minor modifications, the equalizers can also be applied if the ZP is replaced by a unique word (UW). [ABSTRACT FROM AUTHOR]

Canonical correlation analysis (CCA) is a widely used data analysis tool that allows to assess the correlation between two distinct sets of signals. It computes optimal linear combinations of the signals in both sets such that the resulting signals are maximally correlated. The weight vectors defining these optimal linear combinations are referred to as “principal CCA directions”. In addition to this particular type of data analysis, CCA is also often used as a blind source separation (BSS) technique, i.e., under certain assumptions, the principal CCA directions have certain demixing properties. In this paper, we propose a distributed CCA (DCCA) algorithm that can operate in wireless sensor networks (WSNs) with a fully connected or a tree topology. The algorithm estimates the Q principal CCA directions from the sensor signal observations collected by the different nodes in the WSN and extracts the corresponding sources. These network-wide principal CCA directions are estimated in a time-recursive fashion without explicitly constructing the corresponding network-wide correlation matrices, i.e., without the need for data centralization. Instead, each node locally computes smaller CCA problems and only transmits compressed sensor signal observations (of dimension Q), which significantly reduces the bit rate over the wireless links of the WSN. We prove convergence and optimality of the DCCA algorithm, and we demonstrate its performance by means of numerical simulations in a blind source separation scenario. [ABSTRACT FROM AUTHOR]

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]

There are two types of crosstalk in digital subscriber line (DSL) systems, namely near-end crosstalk (NEXT) and far-end crosstalk (FEXT). NEXT is usually much stronger than FEXT. Therefore, high-speed DSL systems transmit in preplanned disjoint downstream (DS) and upstream (US) frequency bands to avoid NEXT. Although easy for implementation, such a fixed bandplan can lead to inefficient bandwidth usage, depending on the DS and US bit rate requirements and the loop topology, particularly in so-called vectored DSL systems, which include signal coordination for FEXT cancellation. In dynamic bandplanning (DBP), each frequency band is allocated to either DS, US, or to both directions depending on the aforementioned parameters. In this paper, we consider optimal DBP for vectored DSL with linear as well as with nonlinear transmitter/receiver structures. We propose an optimal DBP algorithm for systems with disjoint DS and US bands. For systems with overlapping bands, the problem of finding the optimal transmitter/receiver filters is nonconvex and we propose two iterative algorithms based on recent optimum spectrum balancing schemes from the literature. We also study the effect of echo and US NEXT cancellation on the system performance. Finally, simulation results are provided to demonstrate that our algorithms can indeed significantly increase the achievable bit rates. [ABSTRACT FROM PUBLISHER]

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]

In this paper, we investigate joint level 2 and 3 dynamic spectrum management (joint DSM 2/3) for downstream (DS) DSL. We consider a DS scenario in which users are divided into a few separate groups, where vector encoding based signal coordination can be applied in each group and spectrum coordination is possible for all users. This can be seen as a mixed interference/broadcast channel (IF/BC) scenario. In order to obtain the optimal transmitter structure, we develop a generalized duality between the vector broadcast and multiple-access channel (MAC) for scenarios in which partial signal coordination is available among users. This theory together with optimal spectrum balancing (OSB) is exploited to calculate the jointly optimal filters and transmit powers for non-linear vector dirty paper coding structures (in the form of Tomlinson-Harashima precoder (THP)) in the groups. The proposed scheme is compared to several other joint DSM 2/3 algorithms for DS DSL. Simulation results show that the proposed scheme (referred to as the IF/BC-OSB algorithm) achieves considerably higher bit rates than the other schemes. IF/BC-OSB encompasses the earlier developed BC-OSB algorithm as a special case. A simplified version of IF/BC-OSB avoiding exhaustive search with near-optimal performance is also proposed. [ABSTRACT FROM PUBLISHER]

Total least squares (TLS) estimation is a popular solution technique for overdetermined systems of linear equations with a noisy data matrix. In this paper, we revisit the distributed total least squares (D-TLS) algorithm, which operates in an ad hoc network, where each node has access to a subset of the linear equations. The D-TLS algorithm computes the TLS solution of the full system of equations in a fully distributed fashion (without fusion center). To reduce the large computational complexity due to an eigenvalue decomposition (EVD) at every node and in each iteration, we modify the D-TLS algorithm based on inverse power iterations (IPIs). In each step of the modified algorithm, a single IPI is performed, which significantly reduces the computational complexity. We show that this IPI-based D-TLS algorithm still converges to the network-wide TLS solution under certain assumptions, which are often satisfied in practice. We provide simulation results to demonstrate the convergence of the algorithm, even when some of these assumptions are not satisfied. [ABSTRACT FROM PUBLISHER]

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]

This paper evaluates noise reduction techniques in bilateral and binaural hearing aids. Adaptive implementations (on a real-time test platform) of the bilateral and binaural speech distortion weighted multichannel Wiener filter (SDW-MWF) and a competing bilateral fixed beamformer are evaluated. As the SDW-MWF relies on a voice activity detector (VAD), a realistic binaural VAD is also included. The test subjects (both normal hearing subjects and hearing aid users) are tested by an adaptive speech reception threshold (SRT) test in different spatial scenarios, including a realistic cafeteria scenario with nonstationary noise. The main conclusions are: (a) The binaural SDW-MWF can further improve the SRT (up to 2 dB) over the improvements achieved by bilateral algorithms, although a significant difference is only achievable if the binaural SDW-MWF uses a perfect VAD. However, in the cafeteria scenario only the binaural SDW-MWF achieves a significant SRT improvement (2.6 dB with perfect VAD, 2.2 dB with real VAD), for the group of hearing aid users. (b) There is no significant degradation when using a real VAD at the input signal-to-noise ratio (SNR) levels where the hearing aid users reach their SRT. (c) The bilateral SDW-MWF achieves no SRT improvements compared to the bilateral fixed beamformer. [ABSTRACT FROM AUTHOR]

In this paper, we consider the linearly constrained distributed adaptive node-specific signal estimation (LC-DANSE) algorithm, which generates a node-specific linearly constrained minimum variance (LCMV) beamformer, i.e., with node-specific linear constraints, at each node of a wireless sensor network. The algorithm significantly reduces the number of signals that are exchanged between nodes, and yet obtains the optimal LCMV beamformers as if each node has access to all the signals in the network. We consider the case where all the steering vectors are known, as well as the blind beamforming case where the steering vectors are not known. We formally prove convergence and optimality for both versions of the LC-DANSE algorithm. We also consider the case where nodes update their local beamformers simultaneously instead of sequentially, and we demonstrate by means of simulations that applying a relaxation is often required to obtain a converging algorithm in this case. We also provide simulation results that demonstrate the effectiveness of the algorithm in a realistic speech enhancement scenario. [ABSTRACT FROM PUBLISHER]

We study the problem of distributed least-squares estimation over ad hoc adaptive networks, where the nodes have a common objective to estimate and track a parameter vector. We consider the case where there is stationary additive colored noise on both the regressors and the output response, which results in biased local least-squares estimators. Assuming that the noise covariance can be estimated (or is known a priori), we first propose a bias-compensated recursive least-squares algorithm (BC-RLS). However, this bias compensation increases the variance or the mean-square deviation (MSD) of the local estimators, and errors in the noise covariance estimates may still result in residual bias. We demonstrate that the MSD and residual bias can then be significantly reduced by applying diffusion adaptation, i.e., by letting nodes combine their local estimates with those of their neighbors. We derive a necessary and sufficient condition for mean-square stability of the algorithm, under some mild assumptions. Furthermore, we derive closed-form expressions for its steady-state mean and mean-square performance. Simulation results are provided, which agree well with the theoretical results. We also consider some special cases where the mean-square stability improvement of diffusion BC-RLS over BC-RLS can be mathematically verified. [ABSTRACT FROM AUTHOR]

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]

Total least squares (TLS) is a popular solution technique for overdetermined systems of linear equations, where both the right-hand side and the input data matrix are assumed to be noisy. We consider a TLS problem in an ad hoc wireless sensor network, where each node collects observations that yield a node-specific subset of linear equations. The goal is to compute the TLS solution of the full set of equations in a distributed fashion, without gathering all these equations in a fusion center. To facilitate the use of the dual-based subgradient algorithm (DBSA), we transform the TLS problem to an equivalent convex semidefinite program (SDP), based on semidefinite relaxation (SDR). This allows us to derive a distributed TLS (D-TLS) algorithm, that satisfies the conditions for convergence of the DBSA, and obtains the same solution as the original (unrelaxed) TLS problem. Even though we make a detour through SDR and SDP theory, the resulting D-TLS algorithm relies on solving local TLS-like problems at each node, rather than computationally expensive SDP optimization techniques. The algorithm is flexible and fully distributed, i.e., it does not make any assumptions on the network topology and nodes only share data with their neighbors through local broadcasts. Due to the flexibility and the uniformity of the network, there is no single point of failure, which makes the algorithm robust to sensor failures. Monte Carlo simulation results are provided to demonstrate the effectiveness of the method. [ABSTRACT FROM AUTHOR]

We present a distributed adaptive node-specific signal estimation (DANSE) algorithm that operates in a wireless sensor network with a tree topology. The algorithm extends the DANSE algorithm for fully connected sensor networks, as described in previous work. It is argued why a tree topology is the natural choice if the network is not fully connected. If the node-specific desired signals share a common latent signal subspace, it is shown that the distributed algorithm converges to the same linear MMSE solutions as obtained with the centralized version of the algorithm. The computational load is then shared between the different nodes in the network, and nodes exchange only linear combinations of their sensor signal observations and data received from their neighbors. Despite the low connectivity of the network and the multi-hop signal paths, the algorithm is fully scalable in terms of communication bandwidth and computational power. Two different cases are considered concerning the communication protocol between the nodes: point-to-point transmission and local broadcasting. The former assumes that there is a reserved communication link between node-pairs, whereas with the latter, nodes communicate the same data to all of their neighbors simultaneously. The convergence properties of the algorithm are demonstrated by means of numerical examples. [ABSTRACT FROM AUTHOR]

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]

This paper presents a physical evaluation of four feedback cancellation techniques in commercial hearing aids and two implementations of a recently developed feedback cancellation algorithm. Based on physical measures for detecting instability, oscillations and distortion, three performance aspects were measured: 1) the added stable gain compared to the hearing aid operating without feedback reduction for white noise as well as for spectrally colored input signals in two static acoustic conditions, 2) the amount of feedback, oscillations and distortion at gain values below the maximum stable gain, 3) the ability to track feedback path changes. Added stable gains between 3 dB and 26 dB were identified. Five of the six techniques achieve worse feedback reduction for a tonal opera input signal than for a speech input signal. Preventing the feedback canceller to drift away from an initial feedback path measurement results in improved performance for tonal signals at the expense of a worse feedback reduction in the acoustic conditions that differ from the condition for which the initialization was performed, as well as a worse tracking of feedback path changes. Repeated measures indicated that the reproducibility of the test set-up is crucial, in particular when the hearing aid operates close to instability. [ABSTRACT FROM AUTHOR]

To gradually expand their networks, operators deploy new xDSL technologies from remote terminals (RT's) closer to the customer. However, since xDSL lines deployed from an RT can share a binder with lines deployed from the central office (CO), a near-far problem is introduced and crosstalk may cause a severe performance degradation for the CO-deployed lines. RT lines have to be careful about how to allocate transmit power to the transmission frequencies, such that the impact on the CO lines is acceptable. Noise Impact (NI) methods have been proposed based on a target noise shape generated by the disturbers (RT lines). In this paper new methods based on the actual impact on the bit rate of the victims (CO lines) are proposed. These Bit Impact (BI) methods closely approximate the optimal power allocation. [ABSTRACT FROM AUTHOR]

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]

In this paper, equalization for transmission over doubly selective channels is discussed. The symbol-by-symbol maximum a posteriori probability (MAP) equalizer and the maximum-likelihood sequence estimation (MLSE) are discussed. The doubly selective channel is modeled using the basis expansion model (BEM). Using the BEM allows for an easy and low-complexity mechanism for constructing the channel trellis to implement the MLSE and the MAP equalizer. The MLSE and the MAP equalizer are implemented for single-carrier transmission and for multicarrier transmission implemented using orthogonal frequency-division multiplexing (OFDM). In this scenario, a complexity-diversity tradeoff can be observed. In addition, we propose a joint estimation and equalization technique for doubly selective channels. In this joint estimation and equalization technique, the channel state information (CSI) is obtained in an iterative manner. Simulation results show that the performance of the joint channel estimation and equalization approaches the performance when perfect CSI is available at the receiver. [ABSTRACT FROM AUTHOR]

This paper presents a novel Reed-Solomon codes based transmission scheme called RS-SC-CP. While RS-SC-CP is essentially a Reed-Solomon (RS) coded single carrier with cyclic prefix (SC-CP) system, a filter bank representation of the RS code is used. This filter bank representation unveils a DFT synthesis bank, just as in a traditional Orthogonal Frequency Division Multiplexing (OFDM) system (allbeit in a finite field). Therefore, RS-SC-CP is topologically equivalent with OFDM. As such, the RS-SC-CP system inherits the advantages of an SC-CP system over a traditional OFDM system like a low Peak to Average Power Ratio (PAPR). But, more importantly, it allows us to use a novel equalization technique that resembles a traditional OFDM equalizer. The equalizer of an RS-SC-CP receiver is split into two stages: the first stage encompasses a partial equalization in the complex field, which ensures that the residual channel response has integer coefficients. It is calculated using a Minimum Mean Square Error (MMSE) criterion. The residual ISI is removed by a Galois field equalizer in the second stage, posterior to the RS decoding removing the noise. Finally, the performance of the RS-SC-CP system is further evaluated by simulations showing the performance gain of the RS-SC-CP system compared to a traditional coded OFDM or Single Carrier with Cyclic Prefix (SC-CP) scheme. [ABSTRACT FROM AUTHOR]

Recently, the duality between multiple-input multiple-output (MIMO) multiple-access channels (MAC) and MIMO broadcast channels (BCs) has been established under a total power constraint. The same set of rates for MAC can be achieved in BC exploiting the MAC-BC duality formulas while preserving the total power constraint. In this paper, we describe the BC optimal power allocation applying this duality in a downstream x-digital subscriber lines (xDSLs) context under a total power constraint for all modems over all tones. Then, a new algorithm called BC-optimal spectrum balancing (BC-OSB) is devised for a more realistic power allocation under per-modem total power constraints. The capacity region of the primal BC problem under per-modem total power constraints is found by the dual optimization problem for the BC under per-modem total power constraints which can be rewritten as a dual optimization problem in the MAC by means of a precoder matrix based on the Lagrange multipliers. We show that the duality gap between the two problems is zero. The multiuser power allocation problem has been solved for interference channels and MAC using the OSB algorithm. In this paper we solve the problem of multiuser power allocation for the BC case using the OSB algorithm as well and we derive a computational efficient algorithm that will be referred to as BC-OSB. Simulation results are provided for two VDSL2 scenarios: the first one with differential-mode (DM) transmission only and the second one with both DM and phantom-mode (PM) transmissions. [ABSTRACT FROM AUTHOR]

Speech reception tests are commonly administered by manually scoring the oral response of the subject. This requires a test supervisor to be continuously present. To avoid this, a subject can type the response, after which it can be scored automatically. However, spelling errors may then be counted as recognition errors, influencing the test results. We demonstrate an autocorrection approach based on two scoring algorithms to cope with spelling errors. The first algorithm deals with sentences and is based on word scores. The second algorithm deals with single words and is based on phoneme scores. Both algorithms were evaluated with a corpus of typed answers based on three different Dutch speech materials. The percentage of differences between automatic and manual scoring was determined, in addition to the mean difference in speech recognition threshold. The sentence correction algorithm performed at a higher accuracy than commonly obtained with these speech materials. The word correction algorithm performed better than the human operator. Both algorithms can be used in practice and allow speech reception tests with open set speech materials over the internet. [ABSTRACT FROM AUTHOR]

In xDSL systems, crosstalk can be separated into two categories, namely in-domain crosstalk and out-of-domain crosstalk. In-domain crosstalk is also refered to as self crosstalk. Out-of-domain crosstalk is crosstalk originating from outside the multi-pair system and is also denoted as external noise (alien crosstalk, radio frequency interference,…). While self crosstalk in itself can easily be canceled by a linear detector like the ZF detector, the presence of external noise requires a more advanced processing. Coordination between transmitters and receivers enables the self crosstalk and the external noise to be mitigated using MIMO signal processing, usually by means of a whitening filter and SVD. In this paper, we investigate the problem of finding the optimal power allocation in MIMO xDSL systems in the presence of self crosstalk and external noise. Optimal Tx/Rx structures and power allocation algorithms will be devised under practical limitations from xDSL systems, namely per-modem total power constraints and/or spectral mask constraints, leading to a generalized SVD-based transmission. Simulation results are given for bonded VDSL2 systems with external noise coming from ADSL2+ or VDSL2 disturbing lines, along with a comparison between algorithms with one-sided signal coordination either only at the transmit side or the receive side. [ABSTRACT FROM AUTHOR]

Blind identification is a crucial subtask in signal processing problems such as blind signal separation (BSS) and direction-of-arrival (DOA) estimation. This paper presents a procedure for multiple-input multiple-output instantaneous blind identification based on second-order temporal properties of the signals, such as coloredness and nonstationarity. The procedure consists of two stages. First, based on assumptions on the second-order temporal structure (SOTS) of the source and noise signals, and using subspace techniques, the problem is reformulated in a particular way such that each column of the unknown mixing matrix satisfies a system of multivariate homogeneous polynomial equations. Then, this nonlinear system of equations is solved by means of a so-called homotopy method, which provides a general tool for solving (possibly nonexact) systems of nonlinear equations by smoothly deforming the known solutions of a simple start system into the desired solutions of the target system. Our blind identification procedure allows to estimate the mixing matrix for scenarios with more sources than sensors without resorting to sparsity assumptions, something that is often believed to be impossible when using only second-order statistics. In addition, since our algorithm does not require any assumption on the mixing matrix, also mixing matrices that are rank-deficient or even have identical columns can be identified. Finally, we give examples and performance results for speech source signals. [ABSTRACT FROM AUTHOR]

Per-tone equalization (PTEQ) has been proposed as an alternative to time-domain equalization in asymmetric digital subscriber line (ADSL) modems. It optimizes the bit rate performance of the system as each tone can be equalized independently. In a per-tone equalization-based ADSL system a fixed-length frequency-domain equalizer is typically used for every tone. The ADSL channel has, however, a lower channel gain at high frequencies; therefore, using a longer equalizer for these frequencies does not result in a significant performance gain. With a fixed equalizer length, the length of the equalizer is determined by the required length at the lower frequencies; hence, a significant number of equalizer taps are wasted in the high-frequency range without any performance gain. Using a variable-length equalizer designed such that an overall performance criterion is optimized can significantly decrease the total number of equalizer taps without coripromising performance. In this correspondence, a resource allocation technique is presented for a variable-length equalizer design using a dual problem formulation. This optimally solves the problem of equalizer length distribution over tones for given resource constraints, with a relatively low complexity. [ABSTRACT FROM AUTHOR]

This paper focuses on Reed-Solomon (RS) codes, which are the most widespread classical error correcting codes. Recently, we have shown that an finite-impulse response (FIR) critically subsampled filterbank representation can be derived for some RS codes. However, this work only addresses RS codes with a non-coprime codeword and dataword length, seriously limiting its practical usability. In this paper, an alternative purely algebraic method is presented to construct such a filterbank. Apart from providing additional insight into the algebraic structure of (non-systematic) RS codes, this method is suited to eliminate the non-coprimeness constraint mentioned before. Using this filter-bank decomposition, a RS code is broken into smaller subcodes that can subsequently be used to build a soft-in soft-out (SISO) RS decoder. It is shown how any RS code, written as an FIR fil. terbank, can be SISO decoded using the filterbank based decoder. Owing to the importance of systematic RS codes, it is shown that any systematic RS code can be decoded using the FIR filterbank decomposition. This leads to better decoding performance in addition with a slightly lower complexity. A further extension towards systematic RS codes is also presented in this paper resulting in an infinite-impulse response critically subsampled filterbank representation. [ABSTRACT FROM AUTHOR]

Zero-intermediate frequency (IF)-based orthogonal frequency division multiplexing (OFDM) transmitters and receivers are gaining a lot of interest because of their potential to enable low-cost terminals. However, such systems suffer from front-end impairments such as in-phase/quadrature-phase (IQ) imbalance which may have a huge impact on the performance. Moreover, since OFDM is very sensitive to a carrier frequency offset, this distortion needs to be taken into account in the derivation and analysis of any IQ imbalance estimation/compensation scheme. In this paper, the effect of both transmitter and receiver IQ imbalance under carrier frequency offset in an OFDM system is studied and an algorithm is developed to compensate for such distortions in the digital domain. The algorithm involved is a very efficient post-FFT adaptive equalization which is shown to lead to near ideal compensation. [ABSTRACT FROM AUTHOR]

In this paper, we propose a frequency-domain equalization technique for orthogonal frequency division multiplexing (OFDM) transmission over frequency-selective channels. We consider the case where the receiver analog front-end suffers from IQ-imbalance and the local oscillator suffers from carrier-frequency offset (CFO). While the IQ-imbalance results in a mirroring effect, the CFO induces inter-carrier interference (ICI). In addition to ICI, we consider the channel delay spread is larger than the cyclic prefix (CP). This means that inter-block interference (IBI) is present. The frequency-domain equalizer is obtained by transferring a time-domain equalizer (TEQ) to the frequency-domain resulting in a per-tone equalizer (PTEQ). Due to the presence of IQ-imbalance the conventional TEQ (where only one TEQ is applied to the received Sequence) is not sufficient to cope with the mirroring effect. A sufficient TEQ consists of two time-domain filters; one applied to the received sequence and another applied to a conjugated version of the received sequence. For the case of IQ-imbalance and CFO, the TEQs are designed according the basis expansion model (BEM) which showed to be able to cope with the ICI problem. Finally, in addition to the frequency-domain PTEQ design procedure, a training-based RLS type initialization scheme for direct per-tone equalization is also proposed. [ABSTRACT FROM AUTHOR]

Direct-conversion architectures are recently receiving a lot of interest in OFDM-based wireless transmission systems. However, due to component imperfections in the front-end analog processing, such systems are very sensitive to in-phase/quadrature-phase (IQ) imbalances. The IQ imbalance results in intercarrier interference (ICI) from the mirror carrier of the OFDM symbol. The resulting distortion can limit the achievable data rate and hence the performance of the system. In this paper, the joint effect of frequency-selective IQ imbalance at both the transmitter and receiver ends is studied. We consider OFDM transmission over a time-invariant frequency-selective channel. When the cyclic prefix is long enough to accommodate the channel impulse response combined with the transmitter and receiver filters, we propose a low-complexity two-tap equalizer with LMS-based adaptation to compensate for IQ imbalances along with channel distortions. When the cyclic prefix is not sufficiently long, then in addition to ICI there also exists interblock interference (IBI) between the adjacent OFDM symbols. In this case, we propose a frequency domain per-tone equalizer (PTEQ) obtained by transferring a time-domain equalizer (TEQ) to the frequency domain. The PTEQ is initialized by a training-based RLS scheme. Both algorithms provide a very efficient post-FFT adaptive equalization and their performance is shown to be close to the ideal case. [ABSTRACT FROM AUTHOR]

In the last decade, there has been a growing interest in soft decoding techniques. These techniques are used in the context of concatenated codes, with Turbo codes as the main example, but are almost never applied to existing classical codes. In this paper, the family of Reed-Solomon (RS) codes is considered, and the complexity problem of soft-in soft-out (SISO) RS decoding is tackled by breaking RS codes into several smaller subcodes. Finally, the decoders of these subcodes work together in a Turbo-like fashion (Gallager's algorithm) to find an approximate maximum a posteriori (MAP) solution. The decomposition that is presented here is based on critically subsampled filterbanks, with one sub-code in each subband. A critically subsampled filterbank allows us to define a number of parallel independent subcodes. Furthermore, noncritically subsampled filterbanks have a larger number of subband variables than the codeword length, causing a message passing decoder (Gallager's algorithm) to fail. This paper focuses on the construction of such filterbanks, starting from noncritically subsampled filterbanks, it gradually evolves towards a critically subsampled filterbank. [ABSTRACT FROM AUTHOR]

The per-tone equalizer (PTEQ) has been presented as an attractive alternative for the classical time-domain equalizer (TEQ) in discrete multitone (DMT) based systems, such as ADSL systems. The PTEQ is based on a linear minimum mean- square-error (L-MMSE) equalizer design for each separate tone. In this paper, we reconsider DMT modulation and equalization in the ADSL context under the realistic assumption of an infinite im- pulse response (HR) model for the wireline channel. First, optimum linear zero-forcing (L-ZF) block equalizers for arbitrary IIR model orders and cyclic prefix (CP) lengths are developed. It is shown that these L-ZF block equalizers can be decoupled per tone, hence they lead to an L-ZF PTEQ. Then, based on the L-ZF PTEQ, low- complexity L-MMSE PTEQ extensions are developed: the linear PTEQ extension exploits frequency-domain transmit redundancy from pilot and unused tones; alternatively, a closely related decision-feedback PTEQ extension can be applied. The PTEQ extensions then add flexibility to a DMT-based system design: the CF overhead can be reduced by exploiting frequency-domain transmit redundancy instead, so that a similar bitrate as with the original PTEQ is achieved at a lower memory and computational cost or, alternatively, a higher bitrate is achieved without a considerable cost increase. Both PTEQ extensions are also shown to improve the receiver's robustness to narrow-band interference. [ABSTRACT FROM AUTHOR]

Although in a number of experiments noise-band vocoders have been shown to provide acoustic models for speech perception in cochlear implants (CI), the present study assesses in four experiments whether and under what limitations noise-band vocoders can be used as an acoustic model for pitch perception in CI. The first two experiments examine the effect of spectral smearing on simulated electrode discrimination and fundamental frequency (F0) discrimination. The third experiment assesses the effect of spectral mismatch in an F0-discrimination task with two different vocoders. The fourth experiment investigates the effect of amplitude compression on modulation rate discrimination. For each experiment, the results obtained from normal-hearing subjects presented with vocoded stimuli are compared to results obtained directly from CI recipients. The results show that place pitch sensitivity drops with increased spectral smearing and that place pitch cues for multi-channel stimuli can adequately be mimicked when the discriminability of adjacent channels is adjusted by varying the spectral slopes to match that of CI subjects. The results also indicate that temporal pitch sensitivity is limited for noise-band carriers with low center frequencies and that the absence of a compression function in the vocoder might alter the saliency of the temporal pitch cues. [ABSTRACT FROM AUTHOR]

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]

Recently, a generalized noise reduction scheme has been proposed, called the Spatially Preprocessed, Speech Distortion Weighted, Multichannel Wiener Filter (SP-SDW-MWF). It encompasses the Generalized Sidelobe Canceller (GSC) and a multichannel Wiener filtering technique as extreme cases. Compared with the widely studied GSC with Quadratic Inequality Constraint (QICuGSC), the SP-SDW-MWF achieves a better noise reduction performance for a given maximum speech distortion level. In this paper, we develop a low-cost, stochastic gradient implementation of the SP-SDW-MWE To speed up convergence and reduce computational complexity, the algorithm is implemented in the frequency domain. Experimental results with a behind-the-ear hearing aid show that the proposed frequency-domain stochastic gradient algorithm preserves the benefit of the exact SP-SDW-MWF over the QIC-GSC, while its computational cost is comparable to the least mean square-based scaled projection algorithm for QIC-GSC. [ABSTRACT FROM AUTHOR]

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]

This paper focuses on multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems with channel order larger than the cyclic prefix (CP) length. Writing the demodulating fast Fourier transform (FFT) as a sliding FFT followed by a downsampling operation, we show in this paper that by swapping the filtering operations of the MIMO channel and the sliding FFT, the data model for the temporally smoothened received signal of each individual tone of the MIMO OFDM system is very similar to the data model for the temporally smoothened received signal of a MIMO single-carrier (SC) system. As a result, to recover the data symbol vectors, the conventional equalization approach for MIMO SC systems can be applied to each individual tone of the MIMO OFDM system. This so-called per-tone equalization (PTEQ) approach for MIMO OFDM systems is an attractive alternative to the recently developed time-domain equalization (TEQ) approach for MIMO OFDM systems. In the second part of this paper, we focus on direct per-tone equalizer design and adapt an existing semi-blind equalizer design method for space-time block coding (STBC) SC systems to the corresponding semi-blind per-tone equalizer design method for STBC OFDM systems. [ABSTRACT FROM AUTHOR]

Describes two design procedures for designing broadband beamformers with an arbitrary spatial directivity pattern. Sensitivity to errors of fixed broadband beamformers using small-size microphone arrays; Optimization of the mean performance of the broadband beamformer; Phase probability density functions.

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]

A new echo cancellation structure for discrete multitone systems is presented where each used roue has its own per-tone echo canceller in addition to a per-tone equalizer. which provides an alternative to current employed time domain and time/frequency domain approaches. The per-tone approach enables us to optimize the signal-to-noise ratio for each tone separately by solving a minimum mean-square error problem for each tone, with implicit so-called joint shortening. Complexity during data transmission is compared for time domain, time/frequency domain, and per-tone echo cancellation. Structures with reduced complexity are derived for an interpolated and a decimated rate setup. Finally, simulation results for an asymmetric digital subscriber line setting demonstrate improved performance over time domain (or time/frequency domain) echo cancellation. [ABSTRACT FROM AUTHOR]

Proposes a generalized singular value decomposition (GSVD) based algorithm for enhancing multimicrophone speech signals degraded by additive colored noise. Description of the optimal filtering technique for enhancing multimicrophone noisy speech signals; Discussion of the practical computation using a GSVD; Information on symmetry properties and averaging operation.