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Coordinated waveform design and receiver filter optimization for cognitive radar networks

Coordinated waveform design and receiver filter optimization...

引用

2016 ieee sensor array and multichannel signal processing workshop, SAM 2016

作者： Rossetti, Gaia Lambotharan, Sangarapillai Signal Processing and Networks Research Group Wolfson School. Loughborough University LoughboroughLE11 3TU United Kingdom

ISBN: (纸本)9781509021031

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. © 2016 ieee.

关键词： Convex optimization

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Antenna selection in massive MIMO systems: Full-array selection or subarray selection?

Antenna selection in massive MIMO systems: Full-array select...

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2016 ieee sensor array and multichannel signal processing workshop, SAM 2016

作者： Gao, Yuan Kaiser, Thomas Institute of Digital Signal Processing University of Duisburg-Essen Duisburg Germany

ISBN: (纸本)9781509021031

This paper presents a concept of subarray antenna selection in massive MIMO systems, i.e., the whole antenna array is segmented into subarrays and only one antenna is selected in each subarray. The subarray antenna selection can reduce the hardware complexity of the RF switching network, but at the cost of performance degradation due to the introduced selection constraint. We evaluate such performance degradation not only with the ideal independent and identically distributed (i.i.d.) but also with the realistic measured channels. To serve our evaluation, an antenna selection algorithm based on branch and bound method is presented, which aims to select an optimal channel submatrix with the largest minimum singular value. A qualitative analysis is also given to compare the performance between the full-array and subarray selection. Simulation results show that the massive MIMO subarray antenna selection has close performance to the full-array antenna selection, no matter with the i.i.d. channels or the realistic channels. The results in this paper imply that the with the concept of subarray antenna selection, antenna selection is still a practical and promising technology in the realistic massive MIMO systems. © 2016 ieee.

关键词： MIMO systems

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Low-complexity correlated time-averaged variable forgetting factor mechanism for diffusion RLS algorithm in sensor networks

Low-complexity correlated time-averaged variable forgetting ...

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2016 ieee sensor array and multichannel signal processing workshop, SAM 2016

作者： Zhang, Ling Cai, Yunlong Li, Chunguang De Lamare, Rodrigo C. Zhao, Minjian Department Ofinformation Science and Electronic Engineering Zhejiang University Hangzhou310027 China CETUC-PUC-Rio Rio de Janeiro22453-900 Brazil

ISBN: (纸本)9781509021031

In this work, we present the low-complexity variable forgetting factor (VFF) technique for the diffusion recursive least squares (RLS) algorithm. In particular, we adopt the VFF mechanism that rely on time-averages of the posteriori error signal and incorporate it into the diffusion RLS (DRLS) algorithm to yield the low-complexity correlated time-averaged VFF diffusion RLS (LCTVFF-DRLS) algorithm. We develop detailed analyses in terms of mean and mean square performance for the proposed algorithm, and derive mathematical expressions to compute the mean square deviation (MSD) and the excess mean square error (EMSE). The simulation results show that the proposed LCTVFF-DRLS algorithm outperforms the existing DRLS algorithm with the fixed forgetting factor, and demonstrate a good match between our proposed analytical expressions and simulated results. © 2016 ieee.

关键词： Diffusion

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Frequency-domain analysis of linear periodically time-varying FBMC systems

Frequency-domain analysis of linear periodically time-varyin...

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2016 ieee sensor array and multichannel signal processing workshop, SAM 2016

作者： Laas, Tobias Baltar, Leonardo G. Nossek, Josef A. Institute for Circuit Theory and Signal Processing Technische Universität München München80290 Germany Next Generation and Standards Intel Deutschland GmbH Am Campeon 10-12 Neubiberg85579 Germany

ISBN: (纸本)9781509021031

We study how to analyze Linear Periodically Time-Varying (LPTV) Filter Bank Based Multi-Carrier (FBMC) transmitters with Offset QAM (OQAM) modulation. Using an approach based on the Bifrequency Map and the Power Spectral Density (PSD), we can derive a Pseudo-Transfer Function for each subcarrier in the steady-state, taking the upsampling into account. Furthermore, we show that the magnitude of the PseudoTransfer Function can be expressed as the average magnitude of Linear Time Invariant (LTI) transfer functions and that an FIR LTI filter with the same magnitude as the Pseudo-Transfer Function and with the same degree as the LPTV filter exists. We also present an LPTV filter fulfilling the Perfect Reconstruction (PR) conditions and apply our previous results. © 2016 ieee.

关键词： Transfer functions

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Improving spectral efficiency in large-array FDD systems with hybrid beamforming

Improving spectral efficiency in large-array FDD systems wit...

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2016 ieee sensor array and multichannel signal processing workshop, SAM 2016

作者： Araujo, Daniel C. Karipidis, Eleftherios De Almeida, Andre L. F. Mota, Joao C. M. Ceará Brazil Ericsson Research Stockholm Sweden

ISBN: (纸本)9781509021031

We investigate the spectral efficiency of large-array systems serving a single-antenna user in cellular frequencies, using full digital or hybrid analog-digital beamforming in frequency division duplexing (FDD) or time division duplexing (TDD) mode. We consider downlink transmission in time-frequency coherent channel blocks, containing both the pilots and data. Considering FDD and taking the pilot overhead into account, we show that hybrid beamforming provides better spectral efficiency performance than full digital beamforming, mainly in cases with high mobility and many antenna elements. We also optimize the number of used radio chains for hybrid beamforming in FDD and show it is possible to achieve comparable spectral efficiency as with full digital beamforming in TDD. © 2016 ieee.

关键词： Spectrum efficiency

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Interpolation-and-decimation-based dimensionality reduction applied to space-time processing

Interpolation-and-decimation-based dimensionality reduction ...

引用

2016 ieee sensor array and multichannel signal processing workshop, SAM 2016

作者： De Oliveira, Aline Sampaio-Neto, Raimundo Fortes, Jose Mauro Backx, Fabian Rio de Janeiro Brazil PUC-Rio Rio de Janeiro Brazil Rio de Janeiro Brazil

ISBN: (纸本)9781509021031

In this paper, we specialize a novel stage of dimensionality reduction, based on a joint interpolation and decimation scheme (JIDS), proposed in [1] and [2], for airborne phased-array radars. The JIDS design approach consists of a very elegant and effective way to obtain the joint interpolation filter and decimation pattern, taking advantage of the correlation generated by the interpolation filter in order to eliminate samples and still achieve low signal to interference and noise ratio (SINR) loss. We compare its results in terms of probability of detection and Doppler performance with the full rank Minimum Variance Distortionless Response sample matrix inversion (MVDR-SMI) space-time filter and other rank reduction techniques such as Principal Components (PC), Cross-Spectral Metric (CSM) and Multistage Wiener Filter (MWF). Simulation results show that the proposed approach has an impressive ability to significantly reduce the length of the space-time snapshots and achieves very good performance in Doppler SINR loss and probability of detection, especially in sample starving scenarios. © 2016 ieee.

关键词： Interpolation

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Joint frequency and direction of arrival estimation with space-time array

Joint frequency and direction of arrival estimation with spa...

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2016 ieee sensor array and multichannel signal processing workshop, SAM 2016

作者： Anil Kumar, A. Razul, Sirajudeen Gulam Girish Chandra, M. See, Chong Meng Balamuralidhar, P. TCS Innovation Labs Bangalore560066 India Temasek Laboratories at NTU Nanyang Technological University Singapore637553 Singapore

ISBN: (纸本)9781509021031

Joint frequency and DOA estimation of more sources than the number of sensors is considered in this paper. We assume a simple uniform linear array (ULA) and propose to employ a multiple delay channel network at every sensor, which can easily be realized by sampling at a slightly higher rate. By combining the outputs of the ULA and the delay network, we show that the manifold matrix is analogous to that of a uniform rectangular array, and hence we appropriately refer to this array as the space-time array. Further, estimation of parameters via the rotational invariance technique (ESPRIT) based algorithm referred to as space-time (ST)-Euler-ESPRIT is proposed. ST-Euler-ESPRIT, similar to well known unitary-ESPRIT provides automatically paired frequencies and their DOAs. We further show that with the proposed approach for a M element ULA and with N-1 delay channel, O(MN) frequencies and their DOAs can be estimated. The performance of ST-Euler-ESPRIT is verified by simulations, where it shows consistently better performance than the unitary-ESPRIT algorithm under noisy conditions. © 2016 ieee.

关键词： Direction of arrival

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Shift invariance, incomplete arrays and coupled CPD: A case study

Shift invariance, incomplete arrays and coupled CPD: A case ...

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2016 ieee sensor array and multichannel signal processing workshop, SAM 2016

作者： Sorensen, Mikael De Lathauwer, Lieven STADIUS Center for Dynamical Systems Signal Processing and Data Analytics IMinds Medical IT Department Kasteelpark Arenberg 10 Leuven-HeverleeB-3001 Belgium Group Science Engineering and Technology KU Leuven Kulak E. Sabbelaan 53 Kortrijk8500 Belgium

ISBN: (纸本)9781509021031

Tensors have proven to be useful tools for array processing. Most attention has been paid to separable arrays, which lead to a Canonical Polyadic Decomposition (CPD). For more general geometries, and in particular for sparse arrays and arrays with missing sensors, more general tensor methods are required. The recently proposed coupled CPD framework allows a data fission/fusion approach in which one zooms in on partial structures and combines the partial CPDs through which the latter are imposed. This approach yields explicit algebraic conditions under which the solution is unique. The exact solution can be found with a matrix eigenvalue decomposition in the noiseless case, similar to ESPRIT in the case of uniform linear arrays. We study in detail the case of sparse spatial sampling where sensors are located on points of a two-dimensional grid. Despite the fact that the array is incomplete, coupled CPD allows us to exploit the rectangularity of the grid as well as the uniformity of the spatial sampling in both dimensions. © 2016 ieee.

关键词： array processing

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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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2016 ieee sensor array and multichannel signal processing workshop, SAM 2016

作者： Plata-Chaves, Jorge Bertrand, Alexander Moonen, Marc KU Leuven Electrical Engineering Dept. ESAT-STADIUS Kasteelpark Arenberg 10 Leuven3001 Belgium

ISBN: (纸本)9781509021031

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. © 2016 ieee.

关键词： Active noise control

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Cooperative navigation and coverage identification with random gossip and sensor fusion

Cooperative navigation and coverage identification with rand...

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2016 ieee sensor array and multichannel signal processing workshop, SAM 2016

作者： Braga, Andre R. Bruno, Marcelo G. S. Fritsche, Carsten Gustafsson, Fredrik Division of Electronics Engineering Aeronautics Institute of Technology São José dos Campos SP12228-900 Brazil Department of Electrical Engineering Linköping University LinköpingSE-581 83 Sweden

ISBN: (纸本)9781509021031

This paper is concerned with cooperative Terrain Aided Navigation of a network of aircraft using fusion of Radar Altimeter and inter-node range measurements. State inference is performed using a Rao-Blackwellized Particle Filter with online measurement noise statistics estimation. For terrain coverage measurement noise parameter identification, an online Expectation Maximization algorithm is proposed, where local sufficient statistics at each node are calculated in the E-step, which are then distributed to neighboring nodes using a random gossip algorithm to perform the M-step at each node. Simulation results show that improvement on positioning and calibration performance can be achieved compared to a non-cooperative approach. © 2016 ieee.

关键词： Image segmentation

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