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On the number of samples needed to identify a mixture of finite alphabet constant modulus sources

On the number of samples needed to identify a mixture of fin...

引用

International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： A. Leshem A.J. van der Veen Department ITS/Electrical Engineering Delft University of Technnology Delft Netherlands School of Engineering Bar-llan University Ramat-Gan Israel

Constant modulus algorithms try to separate linear mixtures of sources with modulus 1. We study the identifiability of this problem: the number of samples needed to ensure that in the noiseless case we have a unique solution. For finite alphabet (L-PSK) sources, finite sample identifiability can hold only with a probability close to but not equal to 1. In a previous paper (Leshem, A. et al., Proc. ieee workshop on sensor array and multichannel signal processing, 2002), we provided a subexponentially decaying upper bound on the probability of non-identifiability. Here, we provide an improved exponentially decaying upper bound, based on Chernoff bounds. We show that, under practical assumptions, this upper bound is much tighter than previously known bounds.

关键词： Upper bound sensor arrays Binary phase shift keying Blind equalizers Source separation Cost function Performance analysis Algorithm design and analysis Phase noise signal processing

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A bootstrap model selection criterion based on Kullback's symmetric divergence

A bootstrap model selection criterion based on Kullback's sy...

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ieee/SP workshop on Statistical signal processing (SSP)

作者： A.-K. Seghouane L. De Lathauwer ETIS UMR 8051 (ENSEA UCP CNRS) Equipes Traitement des Images et du Signal Cergy-Pontoise France

Following in the recent work of J. Cavanaugh (1999) and A.K. Seghouane (2002), a new corrected variant of KIC develop for the purpose of sources separation is proposed in this paper. The variant utilizes bootstrapping to provide an estimate of the expected Kullback-Leibler symmetric divergence between the model generating the data and a fitted approximating model. Simulation results that illustrate the performance of the new proposed criterion for the detection of the number of signals received by a sensor array are presented. As a result, the KIC variant serves as an effective tool for estimating the number of sources compared to other well known criteria.

关键词： sensor arrays Linear regression array signal processing Electronic mail Radar signal processing signal processing Additive noise Backscatter Radar detection Computational efficiency

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Differential Error Feedback for Communication-Efficient Decentralized Optimization

Differential Error Feedback for Communication-Efficient Dece...

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sensor array and multichannel signal processing workshop

作者： Roula Nassif Stefan Vlaski Marco Carpentiero Vincenzo Matta Ali H. Sayed Université Cote d'Azur France Imperial College London UK University of Salerno Italy Ecole Poly technique Fédérale de Lausanne Switzerland

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

Communication-constrained algorithms for decentralized learning and optimization rely on the exchange of quantized signals coupled with local updates. In this context, differential quantization is an effective technique to mitigate the negative impact of quantization by leveraging correlations between subsequent iterates. In addition, the use of error feedback, which consists of incorporating the quantization error into subsequent steps, is a powerful mechanism to compensate for the bias caused by the quantization. Under error feedback, performance guarantees in the literature have so far focused on algorithms employing a fusion center or a special class of contractive quantizers that cannot be implemented with a finite number of bits. In this work, we propose and study a new decentralized communication-efficient learning approach that blends differential quantization with error feedback. The results show that, under some general conditions on the quantization noise, and for sufficiently small step-sizes $\mu$ it is possible to keep the estimation errors small (on the order of μ) in steady state. The results also suggest that, in the small step-size regime, it is possible to attain the performance achievable in the absence of compression.

关键词： Estimation error Quantization (signal) Correlation array signal processing Conferences Noise signal processing algorithms

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Robust DOA Estimation for Sources with Known Waveforms in Impulsive Noise Environments

Robust DOA Estimation for Sources with Known Waveforms in Im...

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sensor array and multichannel signal processing workshop

作者： Yang-Yang Dong Chun-Xi Dong Zhong-Guo Wu Jingjing Cai Hua Chen School of Electronic Engineering Xidian University Xi’an China Luoyang Electronic Equipment Test Center of China Luoyang China Faculty of Information Science and Engineering Ningbo University Ningbo China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

Conventional direction of arrival (DOA) estimation methods for known waveform sources have often assumed the noise being Gaussian distribution. However, the impulsive noise are frequently encountered in practice, which may severely degrade their estimation performance. To deal with this problem, we firstly construct a hybrid cost function to obtain the matrix related to unknown DOAs and complex amplitudes in the presence of impulsive noise. Then, by incorporating the majorization-minimization (MM) framework, the cost function is optimized iteratively. Finally, the DOAs and complex amplitudes are estimated via using the inherent relationship of the matrix calculated from the MM step. As demonstrated by simulation results, for strongly impulsive noise, the proposed method has a better estimation performance than many existing methods. Moreover, it can handle both weakly and strongly impulsive cases effectively.

关键词： Direction-of-arrival estimation array signal processing Simulation Conferences Estimation Gaussian distribution Cost function

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Performance Evaluation of Bluetooth in a Wireless Body Area Network for Practical Applications

Performance Evaluation of Bluetooth in a Wireless Body Area ...

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sensor array and multichannel signal processing workshop

作者： Olaf Reich Erik Hübner Bogdan Ghita Matthias Wagner Jörg Schäfer Department Computer and Engineering Sciences Frankfurt University of Applied Sciences Frankfurt am Main Germany University of Plymouth Plymouth United Kingdom

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

This work focuses on practical research in the field of Bluetooth 5.0 and the maximum number of Bluetooth sensors nodes in a wireless body area network (WBAN) for human activity recognition (HAR). As network topology M:1 multi-pairing is used. For the best of our knowledge no direct related work in this field can be found. We investigated how many Bluetooth connections can be simultaneously connected with different smartphones (iOS) with real sensor data and in which time intervals the data can still be processed and stored. Our results show that a maximum of 14 Bluetooth devices can be connected under practical conditions. A stable transmission with 48 bytes per package are found with most reliability in an minimal interval of 40 ms per node.

关键词： Wireless communication Performance evaluation Wireless sensor networks Bluetooth Network topology Body area networks sensors

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Flying Radar: Altitude Optimization, Clutter Mitigation and Spectrum Sharing With MIMO Communication System

Flying Radar: Altitude Optimization, Clutter Mitigation and ...

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sensor array and multichannel signal processing workshop

作者： Mohamed Rihan Mahmoud M. Selim Chen Xu Lei Huang The Institute of Intelligent Computing Science Shenzhen University College of Information Engineering Shenzhen University Shenzhen China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

According to recent reports, a flying radar (FR) onboard of UAV will provide high fidelity radar information on forward observation missions. However, such desired performance may be degraded when the FR shares the spectrum band with communication systems. In this paper, we study for the first time the coexistence between a FR and MIMO communication system. Specifically, we present an efficient framework to jointly deal with UAV’s altitude optimization, clutter mitigation, and spectrum sharing with MIMO communication system. The proposed framework is based on using transmit precoding at both systems to maximize the SINR of the FR under rate constraints for the communication system, and power budget constraints for both systems. Meanwhile, it optimizes the FR altitude to provide an optimum trade-off between the excreted interference from the communication system encountered at low altitude and high detection probability of the target amongst clutters encountered at high altitude due to line-of-sight. Simulation results show the effectiveness of the proposed framework for scenarios where both clutter and interference exist.

关键词： array signal processing Radar clutter Simulation Switches Receivers Clutter MIMO communication

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Two-timescale Beamforming Optimization for Intelligent Reflecting Surface Enhanced Wireless Network

Two-timescale Beamforming Optimization for Intelligent Refle...

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sensor array and multichannel signal processing workshop

作者： Ming-Min Zhao Qingqing Wu Min-Jian Zhao Rui Zhang College of ISEE Zhejiang University Hangzhou China Department of ECE National University of Singapore Singapore

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

Intelligent reflecting surface (IRS) has drawn a lot of attention recently as a promising new solution to achieve high spectral and energy efficiency for future wireless networks. Prior works on IRS mainly rely on the instantaneous channel state information (I-CSI), which, however, is practically difficult to obtain for IRS-associated links due to its passive operation and large number of elements. To overcome this difficulty, we propose in this paper a new two-timescale (TTS) transmission protocol to maximize the achievable average sum-rate for an IRS-aided multiuser system. Specifically, the passive IRS phase-shifts are first optimized based on the statistical CSI (S-CSI) of all links, which varies much slowly as compared to their I-CSI, while the transmit beamforming/precoding vectors at the access point (AP) are then designed to cater to the I-CSI of the users' effective channels with the optimized IRS phase-shifts, thus significantly reducing the channel training overhead and passive beamforming complexity over the existing schemes based on the I-CSI of all channels. Simulation results are presented to validate the effectiveness of our proposed algorithm.

关键词： Training Protocols array signal processing Wireless networks Simulation Precoding signal processing algorithms

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Direction finding via joint diagonalization

Direction finding via joint diagonalization

引用

ieee workshop on Statistical signal and array processing

作者： A.J. Weiss B. Friedlander Department Electrical Engineering Systems Tel-Aviv University Tel-Aviv Israel Department Electrical& Computer Engineering University of California Davis CA USA

An approach to array processing (i.e., direction finding, signal separation and reconstruction, and calibration) based on the analytical constant modulus algorithm is considered. The main advantage of this approach is that the multidimensional search associated with maximum likelihood based estimators or the single dimensional search associated with MUSIC type methods are eliminated. The sensor array elements are assumed to have the same, up to a multiplicative constant, angle dependent, unknown gain pattern. We show that under this assumption it is possible to estimate the array response matrix and then use the result for direction finding, if the nominal array manifold is known, at least approximately. It is also possible to use the estimated array response matrix in order to separate and reconstruct the signals, or calibrate the array shape or response.

关键词： sensor arrays array signal processing Source separation Calibration signal analysis Algorithm design and analysis Multidimensional systems Maximum likelihood estimation Multiple signal classification Shape

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Error analysis of the pruned multi-angle resolution beamformer

Error analysis of the pruned multi-angle resolution beamform...

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ieee Digital signal processing workshop

作者： Yeo-Sun Yoon L.M. Kaplan J.H. McClellan Center for Signal and Image Processing School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA CTSPS Department of Engineering Clark Atlanta University Atlanta GA USA

ISBN: (纸本)0780381165

Recently, we proposed the pruned fast beamformer that is able to detect coherent signals during beamforming. The fast beamformer is a multistage approximation to delay and sum beamforming. Using a coherent signal detector, the pruned fast beamformer is able to reduce the computational load by eliminating processing to resolve steering directions that do not contain a target-like source. This paper analyzes the performance of the detector and discusses how approximation errors in the fast beamformer effects detection performance. The results indicate that the coherence detectors is effective under the approximation errors.

关键词： Error analysis array signal processing sensor arrays signal processing Detectors Approximation error signal resolution signal detection Delay Performance analysis

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A Machine- Learning -based approach to Direction-of-arrival Sectorization using Spherical Microphone array

A Machine- Learning -based approach to Direction-of-arrival ...

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sensor array and multichannel signal processing workshop

作者： Chibuzo Joseph Nnonyelu Meng Jiang Marianthi Adamopoulou Jan Lundgren STC Research Center Mid Sweden University Sundsvall Sweden

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

Direction of arrival estimation using the spherical microphone array usually requires a search in the whole 3-dimensional space, hence computationally demanding. This work presents a machine learning approach to sectorizing the 3-dimensional space, as an intermediate step for direction-of-arrival estimation using spherical microphone array. A new feature based on the outer product of spherical harmonic vectors was proposed for the classification. This spherical harmonic matrix nominally offers lower dimensionality compared to the commonly used covariance matrix of received data. The dimension of the input matrix was further reduced using the neighborhood component analysis. The extracted features were then used to train a support vector machine (SVM), 2-layer multilayer perceptron (MLP) and a convolutional neural network (CNN) for classification purposes. The results show that the models were able to classify the spherical sector with up to 90 % accuracy for all models and number of sectors under consideration. Also, the MLP and CNN trained with simulated samples were able to accurately classify samples from real data that were not included in training samples.

关键词： Support vector machines Training Direction-of-arrival estimation Machine learning Harmonic analysis Microphone arrays Vectors

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