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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]

This paper aims at studying the achievable data rate of discrete cosine transform (DCT)-based multicarrier modulation (MCM) systems. To this end, a general formulation is presented for the full transmission/reception process of data in Type-II even DCT and Type-IV even DCT-based systems. This paper focuses on the use of symmetric extension and zero padding as redundancy methods. Furthermore, three cases related to the channel order and the length of the redundancy are studied. In the first case, the channel order is less than or equal to the length of the redundancy. In the second and third cases, the channel order is greater than the length of the redundancy; the interference caused by the channel impulse response is calculated, and theoretical expressions for their powers are derived. These expressions allow studying the achievable data rate of the DCT-based MCM systems, besides enabling the comparison with the conventional MCM based on the discrete Fourier transform. [ABSTRACT FROM AUTHOR]

Parametric equalization of an acoustic system aims to compensate for the deviations of its response from a desired target response using parametric digital filters. An optimization procedure is presented for the automatic design of a low-order equalizer using parametric infinite impulse response (IIR) filters, specifically second-order peaking filters and first-order shelving filters. The proposed procedure minimizes the sum of square errors (SSE) between the system and the target complex frequency responses, instead of the commonly used difference in magnitudes, and exploits a previously unexplored orthogonality property of one particular type of parametric filter. This brings a series of advantages over the state-of-the-art procedures, such as an improved mathematical tractability of the equalization problem, with the possibility of computing analytical expressions for the gradients, an improved initialization of the parameters, including the global gain of the equalizer, the incorporation of shelving filters in the optimization procedure, and a more accentuated focus on the equalization of the more perceptually relevant frequency peaks. Examples of loudspeaker and room equalization are provided, as well as a note about extending the procedure to multi-point equalization and transfer function modeling. [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]

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]

Cochlear implant (CI) stimulation artifacts are currently removed from electrically evoked steady-state response (EASSR) measurements based on a linear interpolation (LI) over the artifact-contaminated signal parts. LI is only successful if CI stimulation artifacts are shorter than the interpulse interval, i.e., for contralateral channels and stimulation pulse rates up to 500 pulses per second (pps). The objective of this paper is to develop and evaluate a template subtraction (TS) method to remove continuous CI stimulation artifacts in order to accurately measure EASSRs. The template construction (TC) is based on an EEG recording containing CI stimulation artifacts but no synchronous neural response. The constructed templates are subtracted from the recording of interest. Response amplitudes and latencies are compared for the TS and LI method, and for different TC durations. The response amplitudes and latencies in contralateral channels are the same after TS and LI, as expected. In ipsilateral channels, response amplitudes and latencies are within the expected range only after TS. The TC duration can be reduced from 5 min to 1 min without a significant effect on response latency. TS with a TC duration of only 1 min allows to remove all CI stimulation artifacts in individual contra- and ipsilateral EEG recording channels. [ABSTRACT FROM AUTHOR]

This report introduces a new database of room impulse responses (RIRs) measured in an empty rectangular room using subwoofers as sound sources. The purpose of this database, publicly available for download, is to provide acoustic measurements within the frequency region of modal resonances. Performing acoustic measurements at low frequencies presents many difficulties, mainly related to ambient noise and to unavoidable nonlinearities of the subwoofer. In this report it is shown that these issues can be addressed and partially solved by means of the exponential sine-sweep technique and a careful calibration of the measurement equipment. A procedure for estimating the reverberation time at very low frequencies is proposed, which uses a cosine-modulated filterbank and an approximation of the RIRs using parametric models in order to reduce problems related to low signal-to-noise ratio and to the length of typical band-pass filter responses. [ABSTRACT FROM AUTHOR]

Unlike traditional homogeneous single-task wireless sensor networks (WSNs), heterogeneous and multitask WSNs allow the cooperation among multiple heterogeneous devices dedicated to solving different signal processing tasks. Despite their heterogenous nature and the fact that each device may solve a different task, the devices could still benefit from a collaboration between them to achieve a superior performance. However, the design of such heterogeneous WSNs is very challenging and requires the design of scalable algorithms that maximize the performance of the devices without transmitting their raw sensor signals in an uncontrolled fashion. Towards this goal, novel techniques are needed both on the signal processing level and on the network-communication level. In this paper, we give an overview of applications in the field of heterogeneous and multitask WSNs with special focus on the signal processing aspects. Moreover, we provide a general overview of the existing algorithms for distributed node-specific estimation. Finally, we discuss the main challenges that have to be tackled for the design of heterogeneous multitask WSNs. [ABSTRACT FROM PUBLISHER]

We consider a multi-task wireless sensor network (WSN) where some of the nodes aim at applying a multi-channel Wiener filter to denoise their local sensor signals, whereas others aim at implementing a linearly constrained minimum variance beamformer to extract node-specific desired signals and cancel interfering signals, and again others aim at estimating the node-specific direction-of-arrival of a set of desired sources. For this multi-task WSN, by relying on distributed signal estimation techniques that incorporate a low-rank approximation of the desired signals correlation matrix, we design a distributed algorithm under which the nodes cooperate with reduced communication resources even though they are solving different signal processing tasks and do not know the tasks of the other nodes. Convergence and optimality results show that the proposed algorithm lets all the nodes achieve the network-wide centralized solution of their node-specific estimation problem. Finally, the algorithm is applied in a wireless acoustic sensor network scenario with multiple speech sources to show the effectiveness of the algorithm and support the theoretical results. [ABSTRACT FROM PUBLISHER]

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]

The ability to efficiently assess and track the utility of each sensor signal is crucial to reduce the energy consumption in a wireless sensor network (WSN), e.g., by putting the sensors with low utility to sleep. Methods to track the sensor signal utility have been described for several multichannel signal estimation methods. For linear minimum mean squared error (LMMSE) estimation, the utility of a sensor signal is defined as the predicted increase in the minimum mean squared error when the sensor would be shut down. However, rather than making such a binary decision, more flexible energy-saving methods could be considered where a sensor changes internal parameters such as, e.g., the number of bits per sample, which results in noise injection in the transmitted sensor signal. We propose a generalization of the original definition of sensor signal utility to include this effect, and we show that it can be efficiently computed and tracked at hardly any computational cost compared to the already available LMMSE estimator. In addition, we illustrate how it can be used to assign a number of bits to each sensor with a greedy approach. Simulation results show that a greedy assignment based on the proposed generalized utility leads to improved results compared to the original utility measure. [ABSTRACT FROM PUBLISHER]