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Robust Super-resolution Frequency Division Duplex (FDD) Channel Estimation

Robust Super-resolution Frequency Division Duplex (FDD) Chan...

引用

sensor array and multichannel signal processing workshop

作者： Yan Liu Xue Jiang School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

Channel estimation is the process of estimating channel parameters from the received samples, which are corrupted by noise. Most of the conventional methods are designed for noise-free or Gaussian noise environment. However, impulsive noise, which is also referred to as outliers, is common in practice and performance of the conventional algorithms degrades in the presence of outliers. In this paper, we propose a robust super-resolution channel estimation algorithm to deal with outliers by replacing ℓ 2 -norm constraints with ℓ 1 -norm constraints to enhance robustness to outliers and solving an improved convex program to obtain the channel parameters, the angles and time delays then are estimated jointly. Simulation results show that the proposed robust super-resolution channel estimation algorithm outperforms the traditional methods and show great robustness to the outliers.

关键词： Parameter estimation Simulation Superresolution Channel estimation signal processing algorithms Frequency conversion Robustness

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DOA estimation using sparse Bayesian learning for colocated MIMO radar with dynamic waveforms

DOA estimation using sparse Bayesian learning for colocated ...

引用

sensor array and multichannel signal processing workshop

作者： Bingfan Liu Baixiao Chen Minglei Yang Hui Xu National Laboratory of Radar Signal Processing Xidian University Xi’an China School of Electronic Engineering Xidian University Xi’an China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

In this paper, we proposed a direction of arrival (DOA) estimation method based on sparse Bayesian learning (SBL) and a dynamic transmitted waveform design method for colocated multiple-input multiple-output (MIMO) radar. First, the SBL DOA estimation method is introduced into the MIMO radar with arbitrary transmitted waveforms. Our theoretical derivation shows that the estimation error of the SBL method is related to the transmitted waveforms. Then, we minimize the estimation error to obtain an updated transmitted waveforms, which will be transmitted in the next pulse repetition period. Numerical simulations show that compared with traditional orthogonal waveforms, the optimized waveforms could achieve a lower Cramér-Rao bound (CRB) and smaller DOA estimation error using the SBL method.

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Aircraft Target Classification Based on CNN

Aircraft Target Classification Based on CNN

引用

sensor array and multichannel signal processing workshop

作者： Qingyuan Zhao Xin Du Yaobing Lu Beijing Insititute of Radio Measurement Beijing China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

In this paper, we applied the idea of deep learning to aircraft targets recognition based on time-frequency diagram. Firstly we introduced application of Convolutional Neural Network (CNN), and the methods of radar target recognition. Secondly, Short Time Fourier Transformation (STFT) was introduced. Thirdly, the structure of improved LeNet CNN was described, considering the character of radar echo wave. Fourthly, 4 kinds of aircraft targets were introduced. Then, the algorithm based on CNN and STFT was validated based on measured data, and was compared with Support Vector Machine (SVM). The accuracy rate could reaches up to 99.98%, 25% higher than SVM. Finally, we summarized advantages of the method proposed in this paper and give the suggestion in engineering application.

关键词： Support vector machines Deep learning Time-frequency analysis Target recognition Weapons Feature extraction Radar signal processing

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Improved sparse error recovery approach for detecting QAM signals in overloaded massive MIMO systems

Improved sparse error recovery approach for detecting QAM si...

引用

sensor array and multichannel signal processing workshop

作者： Yacine Meslem Abeldjalil Aïssa-El-Bey Mustapha Djeddou Laboratoire Télécommunications École Militaire Polytechnique Bordj el Bahri Algeria IMT Atlantique UMR CNRS 6285 Lab-STICC Brest France

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

With a convenient concatenation of a convex relaxation-based detector and a simple greedy algorithm, we propose an improved Post Detection Sparse error Recovery (PDSR) approach for massive Multiple Input Multiple Output (m-MIMO) systems that, in particular, transmit QAM signals. The proposed PDSR approach can perform well in situations, where the classical one, either acts poorly or completely fails. We further propose an Alternating Direction Method of Multipliers (ADMM)-based solver for the convex detector, which is advan¬tageous in maintaining an affordable complexity to the overall proposed detection scheme. Numerical experiments show the efficiency of our approach, especially when applied to overloaded m-MIMO systems.

关键词： Greedy algorithms Quadrature amplitude modulation Conferences signal processing algorithms Detectors Massive MIMO Transforms

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Channel Estimation for Hybrid MIMO Communication with (Non-) Uniform Linear arrays via Tensor Decomposition

Channel Estimation for Hybrid MIMO Communication with (Non-)...

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sensor array and multichannel signal processing workshop

作者： Ali Koochakzadeh Piya Pal Electrical and Computer Engineering Department University of California San Diego

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

This paper considers the problem of channel estimation for millimeter wave wireless communication channels. Many existing channel estimation approaches utilize the spatial sparsity of mmWave channels and employ compressive sensing based techniques to estimate the parameters of the channel, such as the Angles of Arrival (AoA) and Angles of Departure (AoD) of the channel paths. In this paper, we show how the problem of channel estimation can be converted into a fourth order tensor decomposition problem, which offers several benefits. Firstly, we do not need a grid-based search for the angles. More importantly, our algorithm is applicable for both uniform and non-uniform arrays at the transmitter and receiver. In particular, our method can exploit well-known benefits offered by the difference co-array of suitably designed sparse arrays and provably identify a larger number of channel paths compared to existing approaches 1 .

关键词： Wireless communication Radio frequency Sufficient conditions Tensors Transmitters Channel estimation signal processing algorithms

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Rank regularized beamforming in single group multicasting networks

Rank regularized beamforming in single group multicasting ne...

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sensor array and multichannel signal processing workshop

作者： Dima Taleb Marius Pesavento Communication Systems Group Technische Universität Darmstadt Darmstadt Germany

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

In multicasting networks, a multi-antenna base station transmits the same information to a single group of users. In this work we consider general rank beamforming using orthogonal space-time block codes (OSTBC)s. The beamforming problem is non-convex and generally NP hard. The semidefinite relaxation technique is employed to solve the problem. In order to control the rank of the beamforming solution we propose to replace the power minimization by a regularized volume minimization which is known as a surrogate for the rank minimization. We propose an iterative two scale algorithm to find the appropriate value for the regularization parameter that yields the desired rank and to compute stationary points of the corresponding optimization problem. The high computational complexity of the proposed algorithm is improved significantly using a one scale algorithm, where the value of the regularization variable is reduced along with the decreasing rank. Simulation results demonstrate that our algorithms outperform the stateof-the-arts procedures in terms of the transmitted power and symbol error rate (SER). For a proper setting of the regularization variable, one scale algorithm outperforms the best compared methods in terms of computational complexity.

关键词： Multicast algorithms array signal processing Simulation signal processing algorithms Multicast communication Minimization Approximation algorithms

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Power Allocation Strategy for OFDM Waveform in RadCom Systems

Power Allocation Strategy for OFDM Waveform in RadCom System...

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sensor array and multichannel signal processing workshop

作者： Mohammad A.B. Mohammad Guolong Cui Xianxiang Yu Mohammad Ahmed Ashenafi Yadessa Gemechu School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

At present, the integrated radar and communication (RadCom) system has attracted much attention. It has several advantages such as power consumption, reducing system size, weight,...etc. This paper proposes a power allocation strategy for the RadCom system in signal-dependent clutter, where both systems use the Orthogonal Frequency Division Multiplexing (OFDM) waveform. The convex optimization problem is formulated and solved analytically by using the Karush-Kuhn-Tuckers (KKT) optimality conditions. The proposed strategy minimizes the total transmitted power while fulfilling the two systems requirements i.e., signal-to-Clutter-plus-Noise Ratio (SCNR) for the target detection performance and Data Information Rate (DIR) for the communication system performance. Finally, the simulation results are presented to verify the effectiveness of the proposed power allocation strategy.

关键词： Power demand OFDM Simulation Radar Radar signal processing Resource management Clutter

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Direct Adaptive Equalization with CFO Pre-compensation for Single-Carrier Underwater Acoustic Communications

Direct Adaptive Equalization with CFO Pre-compensation for S...

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sensor array and multichannel signal processing workshop

作者： Jun Tao Fengzhong Qu Hongtao Zhang Key Laboratory of Underwater Acoustic Signal Processing of the Ministry of Education School of Information Science and Engineering Southeast University Nanjing China Key Laboratory of Ocean Observation-Imaging Testbed of Zhejiang Province Zhejiang University Zhoushan China Hangzhou Applied Acoustics Research Institute Hangzhou China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

For single-carrier underwater acoustic (UWA) communications, phase correction is critical to the symbol detection on the receiver side. Existing receiver schemes either run a phase- locked loop (PLL) in parallel with an equalizer or perform the phase correction at the output of an equalizer. Both parallel and serial phase correction methods suffer limitations in practical use though. In this work, we propose to introduce a carrier frequency offset (CFO) pre-compensation module for existing receivers, with the CFO estimated with an m-sequence. The so-obtained receiver scheme was tested by real data collected in an at-sea UWA communication trial. Experimental results verified the extra performance gain brought by the CFO precompensation. In particular, when the CFO is the main source of phase rotation, conventional CFO correction modules like the PLL can be dropped without performance degradation.

关键词： Degradation array signal processing Conferences Receivers Performance gain Adaptive equalizers Frequency estimation

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Automotive Dual-Function Radar Communications Systems: An Overview

Automotive Dual-Function Radar Communications Systems: An Ov...

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sensor array and multichannel signal processing workshop

作者： Dingyou Ma Nir Shlezinger Tianyao Huang Yimin Liu Yonina C. Eldar Department of Electronic Engineering Tsinghua University Beijing China Faculty of Mathematics and Computer Science Weizmann Institute of Science Rehovot Israel

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

Future cars will constantly sense the environment and interchange information with their surrounding in order to successfully choose routes, avoid hazards, and comply with traffic regulations. These vehicles will be equipped with multiple sensors, including automotive radar, as well as wireless communications capabilities. The similarity in hardware and signal processing of automotive radar and wireless communications motivates designing these functionalities in a joint manner. Such dual function radar-communications (DFRC) designs are the focus of a large body of recent works. These joint designs lead to substantial gains in size, cost, power consumption, and performance, making them especially important for vehicular applications, where both the radar and communications operate in similar ranges. This paper reviews a wide variety of existing DFRC strategies and their relevance to automotive systems. We discuss the pros and cons of current methods, mapping them in the context of vehicular application, and present the main challenges and possible research directions.

关键词： Wireless communication Power demand Radar signal processing sensor systems Regulation Hazards sensors

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Gridless Sparsity-Based Localization for Near-Field Sources with Symmetric Linear array

Gridless Sparsity-Based Localization for Near-Field Sources ...

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sensor array and multichannel signal processing workshop

作者： Weiliang Zuo Jingmin Xin Tong Xiao Nanning Zheng Akira Sano Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an China Department of System Design Engineering Keio University Yokohama Japan

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

In this paper, we investigate the problem of estimating the directions-of-arrival (DOAs) and ranges of multiple nearfield narrowband sources impinging on a symmetric uniform linear array (ULA). By forming a Toeplitz-like correlation matrix from the anti-diagonal elements of the array covariance matrix, a convex optimization problem for the resultant Toeplitz-like matrix reconstruction is established and further a gridless sparsity-based localization for near-field sources is proposed. The DOAs can then be retrieved by using the recovered correlation matrix according to root-MUSIC or Vandermonde decomposition theorem. Additionally, the ranges are obtained through a subspace-based estimator with the corresponding estimated DOAs, while the association of the estimated DOAs and ranges are completed at the same time. Finally, the numerical examples are provided to substantiate the performance of our proposed method, and the simulation results demonstrate that the proposed method provides remarkable and satisfactory estimation performance.

关键词： Location awareness Direction-of-arrival estimation Symmetric matrices Correlation Simulation Estimation Convex functions

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