In this paper, we propose a rate-distributed linearly constrained minimum variance (LCMV) beamformer for joint noise reduction and spatial cue preservation for assistive hearing in wireless acoustic sensor networks (W...
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ISBN:
(纸本)9781538647523
In this paper, we propose a rate-distributed linearly constrained minimum variance (LCMV) beamformer for joint noise reduction and spatial cue preservation for assistive hearing in wireless acoustic sensor networks (WASNs). The WASN can consist of wireless communicating hearing aids, extended with additional wireless microphones. Due to the fact that each sensor node has a limited power budget, it is essential to consider the energy usage when designing algorithms for such WASNs. As the energy usage in terms of data transmission is directly affected by the communication rate, the proposed method optimally distributes the bit rate for each microphone node. The rate distribution is obtained by minimizing the total transmission costs under constraints on the noise reduction performance and spatial cue preservation of interfering sources. In contrast to sensor selection, i.e., binary decisions on the usefulness of a node, rate distribution allows for soft decisions, and, will lead to more degrees of freedom for joint noise reduction and spatial cue preservation than sensor selection. Numerical results show that given a certain noise reduction requirement, the proposed method displays improved energy efficiency and can preserve the spatial cues of more interferers compared to sensor selection approaches.
Singular value decomposition (SVD) is analytically inherent in various reduced rank filters and/or estimators. But the computation of SVD is generally not an efficient way for rank reduction. This paper introduces an ...
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ISBN:
(纸本)0780363396
Singular value decomposition (SVD) is analytically inherent in various reduced rank filters and/or estimators. But the computation of SVD is generally not an efficient way for rank reduction. This paper introduces an efficient approach to computing for rank reduction. This approach, referred to as alternate power (AP) method, is globally and exponentially convergent under a weak condition, and is a generalization of the conventional power method for subspace computation. The AP method is especially useful for computing the reduced rank filter (RRF) by Brillinger, the reduced rank Wiener filter (RRWF) by Sckarf, and the reduced rank maximum likelihood estimate (RRMLE) by Stoica and Viberg.
The wide waveform bandwidths desired for fine range resolution in current and future phased array radars have an impact on the performance of adaptive digital beamforming (ADBF) dale to the inevitable frequency respon...
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ISBN:
(纸本)0780363396
The wide waveform bandwidths desired for fine range resolution in current and future phased array radars have an impact on the performance of adaptive digital beamforming (ADBF) dale to the inevitable frequency response mismatches that occur from channel to channel across the band. In previous work, analytical expressions for the correlation between channels have been developed for a simple two element array with a sinusoidal ripple in either the amplitude or phase response in one of the channels. This paper extends those results to a more general model that allows larger arrays utilizing time delay steering to be modeled. Expressions are developed for the correlation between channels as a function of the parameters of the channel frequency responses. The performance of the adaptive beamformer is characterized with respect to SINE for waveforms that are flat over the bandwidth and for LFM waveforms processed using stretch processing.
Previous work on ordered transmission approaches showed significant transmission savings but focused entirely on cases with statistically independent observations at a set of sensor nodes. Here we take the first steps...
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ISBN:
(纸本)9781467310710
Previous work on ordered transmission approaches showed significant transmission savings but focused entirely on cases with statistically independent observations at a set of sensor nodes. Here we take the first steps toward applying ordering to cases with statistically dependent observations. While we focus on a particular signal detection problem, we choose one of the most well studied problems, detection of a shift-in-mean for a multivariate Gaussian distribution. We employ the well developed theory of decomposable graphical models, and focus on cases where the observations are taken at a set of sensor nodes which can be grouped into a set of cliques. We assume the nodes within a clique are physically close, so that inner-clique communications can be considered extremely inexpensive. We present the computation of the overall likelihood ratio as a new sum, distinctly different from the sum over a set of independent variables, which implies it is possible to employ ordering over the cliques in an attempt to limit the number of communications from each clique to the place where the clique data will be combined. We present results that imply we can often save a significant portion of these transmission, which is lower bounded by half of the number of cliques. We describe necessary conditions for the result to hold and provide numerical results indicating these conditions are satisfied in many cases of practical interest.
As the modern electro-magnetic environment in urban and battlefield scenarios becomes increasingly denser, system designers tend to gravitate toward wide bandwidth solutions. Not only do spread spectrum designs permit...
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ISBN:
(纸本)1424403081
As the modern electro-magnetic environment in urban and battlefield scenarios becomes increasingly denser, system designers tend to gravitate toward wide bandwidth solutions. Not only do spread spectrum designs permit increased co-channel utilization, they also tend to be inherently more secure, decreasing the probability of intercept by non-cooperative receivers. This is in part due to the code that must be applied in order to modulate the information bandwidth into a much wider transmitted bandwidth. In addition the non-cooperative receiver must contend with issues of increased noise, decreased sensitivity, and increased signalprocessing resource requirements among others. The problem is further exacerbated for receivers that must perform emitter geo-location or other forms of spatial processing, since the conventional high-resolution techniques rely on phase measurements based on the monochromatic assumption. This paper will discuss some of the existing methods suggested to contend with wide bandwidth spatial processing for noncooperative receivers and their limitations. It will introduce a new method based on the bilinear transformation that overcomes some of these limitations. It will present simulation results that demonstrate the advantage of this technique.
In this work we investigate an alternative model for signals encountered in acoustic environments to the traditional Gaussian process. The sound signals in this case are assumed to be sub-Gaussian of impulsive nature....
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ISBN:
(纸本)0780375513
In this work we investigate an alternative model for signals encountered in acoustic environments to the traditional Gaussian process. The sound signals in this case are assumed to be sub-Gaussian of impulsive nature. The noise encountered in these environments predominantly stems from reverberation or multipath effects, which makes it significantly dependent on the source. Hence, the noise is also modeled as jointly sub-Gaussian. The Levy alpha-stable distribution, of characteristic exponent 0.5 and index of symmetry 1, is used together with a multivariate Gaussian density to derive the sub-Gaussian process. Based on this density, the stochastic Maximum Likelihood (ML) estimator is formulated. A separable solution of the estimator is given. Subsequently, simulations demonstrating the performance gains relative to the Gaussian-based ML estimator are provided, as well as a comparison of the two methods on localization of real sounds gathered with a 20- and 41-microphone arrays.
sensor networks offer an opportunity for improving submarine detection. Let each sensor firstly make a binary local decision-'0' or '1', and then a fusion center collects them to make a system-level in...
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ISBN:
(纸本)9781467310710
sensor networks offer an opportunity for improving submarine detection. Let each sensor firstly make a binary local decision-'0' or '1', and then a fusion center collects them to make a system-level inference without knowledge of probabilities of local detection. An obvious strategy is a counting rule test, which simply counts the total number of 1's and compares it to a threshold. This approach equally considers all network subareas. However, reflected signals from a submarine are highly aspect dependent, and in many instances only sensors in a particular zone could receive the echoes. This paper focuses on the scan statistic, which slides a window across the sensor field, and selects the subarea with the largest number of 1's to make a decision. The scan statistic integrates the spatial distinction of local decisions into detection fusion. With a proper window size, it may suppress subarea interference, and improve system-level performance.
In recent years, the author has been involved in starting up a high-tech company and bringing to a successful fruition of both the product and the company itself In this paper, we will share our experiences from this ...
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ISBN:
(纸本)0780375513
In recent years, the author has been involved in starting up a high-tech company and bringing to a successful fruition of both the product and the company itself In this paper, we will share our experiences from this venture with the audience. The product in question was a VDSL modem, delivering about 15 megabits-per-second over unshielded telephone wires in full duplex. We review VDSL technology, its capabilities and limitations, and put it in the context of the "broadband to the home" trend. We describe the steps involved in turning a paper-concept into a real working product, as well as the main challenges and obstacles. We discuss what may be the future of copper-based broadband technology and what may come after it. Finally, we reflect on possible implications of our industry experience on teaching digital signalprocessing in the future.
The problem of detecting the number of narrowband sources of energy and the direction of arrival (DOA) of each detected source using data received by an array of sensors is investigated. The well known difficulty of a...
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ISBN:
(纸本)0780375513
The problem of detecting the number of narrowband sources of energy and the direction of arrival (DOA) of each detected source using data received by an array of sensors is investigated. The well known difficulty of an unconstrained maximum likelihood (ML) approach for estimation of dimensionality parameters (e.g., model order) is addressed by using ML signal-to-noise ratio estimates of hypothesized sources as detection statistics rather than using the likelihood function (LF) with a penalty function. Performance comparisons are made to unstructured and structured techniques based on Akaike Information Theoretic Criteria (AIC), Minimum Description Length (MDL), and Bayesian Predictive Density (BPD) methods as well as Minimum Variance Distortionless Response (MVDR). The technique presented here offers better detection performance for multiple closely spaced uncorrelated signals, with the ability to trade off detection and false alarm performance.
In this paper, we analyze the performance of dynamic time division duplexing (DTDD) in a distributed antenna array massive multiple-input multiple-output (DAA-mMIMO) system in the presence of simultaneous uplink (UL) ...
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ISBN:
(纸本)9781665406338
In this paper, we analyze the performance of dynamic time division duplexing (DTDD) in a distributed antenna array massive multiple-input multiple-output (DAA-mMIMO) system in the presence of simultaneous uplink (UL) and downlink (DL) data requirements. DTDD has been shown to substantially improve system performance in terms of spectral efficiency (SE) for cellular mMIMO systems. In the DAAenabled system, we show that the performance of DTDD depends critically on appropriately scheduling the UL/DL modes at the access points (APs) based on the localized UL/DL traffic demand. Since an exhaustive search over all possible UL/DL modes is combinatorially complex, we present a greedy algorithm to solve the AP-scheduling problem in polynomial time. Via extensive numerical experiments, we illustrate the 95%-likely sum UL-DL SE achieved by our solution, and show that DAA-mMIMO with dynamic AP-scheduling can substantially outperform TDD-based cellular as well as DAA mMIMO systems.
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