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检索条件"任意字段=2008 IEEE Sensor Array and Multichannel Signal Processing Workshop"

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A Monte Carlo scheme for node-specific inference over wireless sensor networks

A Monte Carlo scheme for node-specific inference over wirele...

引用

sensor array and multichannel signal processing workshop

作者： Luca Martino Jorge Plata-Chaves Francisco Louzada Institute of Mathematical Sciences and Computing Universidade de São Paulo (ICMC-USP) Brazil Department of Electrical Engineering-ESAT STADIUS Leuven Belgium

ISBN: (纸本)9781509021048

In this work, we design an efficient Monte Carlo scheme for a node-specific inference problem where a vector of global parameters and multiple vectors of local parameters are involved. This scenario often appears in inference problems over heterogeneous wireless sensor networks where each node performs observations dependent on a vector of global parameters as well as a vector of local parameters. The proposed scheme uses parallel local MCMC chains and then an importance sampling (IS) fusion step that leverages all the observations of all the nodes when estimating the global parameters. The resulting algorithm is simple and flexible. It can be easily applied iteratively, or extended in a sequential framework.

关键词： Monte Carlo methods Wireless sensor networks Probability density function signal processing algorithms Bandwidth Inference algorithms Estimation

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Beamforming designs for multiuser transmissions in FDD massive MIMO systems using partial CSIT

Beamforming designs for multiuser transmissions in FDD massi...

引用

sensor array and multichannel signal processing workshop

作者： Ming-Fu Tang Szu-Yu Wang Borching Su National Taiwan University Taipei TW

ISBN: (纸本)9781509021048

In this paper, we consider an effective acquisition mechanism of partial channel state information at the transmitter (CSIT) for frequency-division duplex (FDD) massive MIMO systems, based on which two downlink beamforming methods are proposed. The partial CSIT is in the form of downlink angles of departure (AoDs) and the amplitudes of the strongest paths of each UE. By exploiting the reciprocity between downlink AoDs and uplink angles of arrival (AoAs), the partial CSIT can be acquired through downlink training and uplink feedback effectively. Therefore, the feasibility of FDD massive MIMO systems is greatly enhanced. Simulation results demonstrate the superiority of the proposed methods compared to other methods in the sense of fairness and achievable sum rate.

关键词： Downlink Uplink array signal processing Training MIMO Design methodology Time-frequency analysis

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A subspace method for array covariance matrix estimation

A subspace method for array covariance matrix estimation

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sensor array and multichannel signal processing workshop

作者： Mostafa Rahmani George K. Atia Department of Electrical and Computer Engineering University of Central Florida Orlando FL USA

ISBN: (纸本)9781509021048

This paper introduces a subspace method for the estimation of an array covariance matrix. When the received signals are uncorrelated, it is shown that the array covariance matrices lie in a special subspace defined through all possible correlation vectors of the received signals and whose dimension is typically much smaller than the ambient dimension. Based on this observation, a subspace-based covariance matrix estimator is proposed as a solution to a semi-definite convex optimization problem. While the optimization problem has no closed-form solution, a nearly optimal closed-form solution that is easily implementable is proposed. The proposed approach is shown to yield higher estimation accuracy than conventional approaches since it eliminates the estimation error that does not lie in the subspace of the true covariance matrices. The numerical examples demonstrate that the proposed estimator can significantly improve the estimation quality of the covariance matrix.

关键词： Covariance matrices Correlation Eigenvalues and eigenfunctions Direction-of-arrival estimation Estimation error signal processing algorithms

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Joint MSINR and relay selection algorithms for distributed beamforming

Joint MSINR and relay selection algorithms for distributed b...

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sensor array and multichannel signal processing workshop

作者： Hang Ruan Rodrigo C. de Lamare Department of Electronics University of York UK CETUC PUC-Rio Brazil

ISBN: (纸本)9781509021048

This paper presents joint maximum signal-to-interference-plus-noise ratio (MSINR) and relay selection algorithms for distributed beam-forming. We propose a joint MSINR and restricted greedy search relay selection (RGSRS) algorithm with a total relay transmit power constraint that iteratively optimizes both the beamforming weights at the relays nodes, maximizing the SINR at the destination. Specifically, we devise a relay selection scheme that is based on greedy search and compare it to other schemes like restricted random relay selection (RRRS) and restricted exhaustive search relay selection (RESRS). A complexity analysis is provided and simulation results show that the proposed joint MSINR and RGSRS algorithm achieves excellent bit error rate (BER) and SINR performances.

关键词： Relays signal to noise ratio Interference array signal processing Shadow mapping Covariance matrices Optimization

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Radar system design for dual-functionality platforms

Radar system design for dual-functionality platforms

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sensor array and multichannel signal processing workshop

作者： Aboulnasr Hassanien Moeness G. Amin Center for Advanced Communications Villanova University Villanova PA USA

ISBN: (纸本)9781509021048

Dual-functionality platforms have recently been proposed to jointly and simultaneously enable radar target illumination and establish wireless communication links. This duality serves as means to alleviate the spectrum congestion crisis. In this paper, we consider the problem of radar system design for dual-function radar-communications (DFRC). We develop a new transmit signaling scheme which permits the embedding of communication symbols in the radar signal emissions. The proposed scheme recognizes the radar and communication signal deliveries as the primary and secondary functions, respectively, and strives to have a minimum impact of the DFRC system on radar operation integrity. In particular, we investigate how the embedding of communication symbols into the radar emission affects the transmit power efficiency. The performance of the proposed technique is validated using simulation examples.

关键词： Radar Radar antennas Receivers Communication symbols Amplitude shift keying array signal processing System analysis and design

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Incremental multiple error filtered-X LMS for node-specific active noise control over wireless acoustic sensor networks

Incremental multiple error filtered-X LMS for node-specific ...

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sensor array and multichannel signal processing workshop

作者： Jorge Plata-Chaves Alexander Bertrand Marc Moonen KU Leuven ESAT-STADIUS Leuven Belgium

ISBN: (纸本)9781509021048

We propose an adaptive distributed algorithm to solve a node-specific Active Noise Control (ANC) problem. In this novel ANC problem, the nodes estimate different but overlapping ANC filters in order to generate secondary signals that cancel a primary noise source as it impinges on their microphones. Different sets of nodes follow a cyclic mode of cooperation in order to implement several coupled Multiple Error Filtered-X Least Mean Squares algorithms, each responsible for the estimation of part of the different node-specific ANC filters. The proposed algorithm outperforms the non-cooperative strategies and achieves the same steady-state noise reduction as a centralized solution that processes all the signals in the network. Finally, computer simulations are provided to illustrate the effectiveness of the proposed algorithm.

关键词： Distributed algorithms Microphones Wireless sensor networks Estimation signal processing algorithms Loudspeakers Filtering algorithms

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Minimum BER precoding in 1-Bit massive MIMO systems

Minimum BER precoding in 1-Bit massive MIMO systems

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sensor array and multichannel signal processing workshop

作者： Hela Jedda Josef A. Nossek Amine Mezghani Institute of Circuit Theory and Signal Processing Technische Universität München Munich Germany University of California Irvine Irvine CA USA

ISBN: (纸本)9781509021048

1-bit digital-to-analog (DACs) and analog-to-digital converters (ADCs) are gaining more interest in massive MIMO systems for economical and computational efficiency. We present a new precoding technique to mitigate the inter-user-interference (IUI) and the channel distortions in a 1-bit downlink MU-MISO system with QPSK symbols. The transmit signal vector is optimized taking into account the 1-bit quantization. We develop a sort of mapping based on a look-up table (LUT) between the input signal and the transmit signal. The LUT is updated for each channel realization. Simulation results show a significant gain in terms of the uncoded bit-error-ratio (BER) compared to the existing linear precoding techniques.

关键词： Optimization Quantization (signal) MIMO Phase shift keying Table lookup Antennas Distortion

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Low-rank robust adaptive beamforming techniques using joint iterative optimization

Low-rank robust adaptive beamforming techniques using joint ...

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sensor array and multichannel signal processing workshop

作者： Hang Ruan Rodrigo C. de Lamare Department of Electronics University of York UK CETUC PUC-Rio Brazil

ISBN: (纸本)9781509021048

This work presents cost-effective low-rank techniques for designing robust adaptive beamforming (RAB) algorithms. At first, we introduce an orthogonal Krylov subspace projection mismatch estimation (OKSPME) method, in which a general linear equation is considered in large dimensions which aims to solve for the steering vector mismatch with known information, then we employ the idea of the full orthogonalization method (FOM), an orthogonal Krylov subspace based method, to iteratively estimate the steering vector mismatch in a reduced-dimensional subspace. An adaptive algorithm based on stochastic gradient and joint iterative optimization (JIO) dimensionality reduction technique is devised for beamforming large sensor arrays with low complexity. Simulations results show excellent performance in terms of the output signal-to-interference-plus-noise ratio (SINR) among all the compared RAB methods.

关键词： Complexity theory Algorithm design and analysis Robustness array signal processing Optimization Mathematical model signal to noise ratio

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Coordinated waveform design and receiver filter optimization for cognitive radar networks

Coordinated waveform design and receiver filter optimization...

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sensor array and multichannel signal processing workshop

作者： Gaia Rossetti Sangarapillai Lambotharan Signal Processing and Networks Research Group Loughborough University Loughborough UK

ISBN: (纸本)9781509021048

We propose convex optimization based waveform designs for cognitive radar networks. The Multiple Input Multiple Output (MIMO) nature of the considered model as well as the cognitive capabilities provided by the joint adaptation of receiver and transmitter and some initial knowledge on the environment, make these algorithms suitable for cognitive radar networks. In particular, we propose two complementary optimization techniques. The first one aims at optimizing the signal to Interference and Noise Ratio (SINR) of a specific radar while keeping the SINR of the other radars at desired levels. The second approach optimizes the SINR of all radars using a Max-Min optimization criterion. The optimization framework includes many constraints on the waveforms such as mutual orthogonality and transmission power. The simulation results confirm the efficiency of the algorithms.

关键词： Optimization Interference signal to noise ratio Receivers Radar cross-sections

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Adaptation with reduced-size message pass to precoder selection in multi-cell MIMO systems

Adaptation with reduced-size message pass to precoder select...

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sensor array and multichannel signal processing workshop

作者： Igor M. Guerreiro Charles C. Cavalcante Dennis Hui Wireless Telecommunications Research Group Universidade Federal do Ceará Fortaleza Brazil Ericsson Research San José CA USA

ISBN: (纸本)9781509021048

This paper addresses the optimization of a multicell network where each cell needs to select precoding matrices for beamforming in a distributed way. A modified version of the adaptive min-sum algorithm that considers reduced-size messages in the message-passing procedure is proposed. The message-passing technique, where each message is reduced to convey only part of usual information, is applied to maximize the system throughput leading to a faster adaptation procedure. Simulation results show this reduction leads to a small average performance loss in system throughput of approximately 6%, while generally reduces the message size in about 73%. Also, the proposed method still outperforms the baseline greedy technique.

关键词： Throughput Niobium Indexes Measurement MIMO Precoding array signal processing

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