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An overview of ultra-wideband microwave imaging via space-time beamforming for early-stage breast-cancer detection

IEEE ANTENNAS AND PROPAGATION MAGAZINE 2005年第1期47卷 19-34页

作者： Li, X Bond, EJ Van Veen, BD Hagness, SC Northwestern Univ Dept Biomed Engn Evanston IL 60208 USA

Ultra-wideband (UWB) microwave imaging has recently been proposed for detecting small malignant breast tumors. In this article, we review the current research status of this approach. First, we introduce the concept of microwave imaging via space-time (MIST) beamforming and related signal-processing algorithms. The objective of these signal-processing techniques is to form a spatial image of scattered microwave energy, and to identify the presence and location of malignant lesions from their scattering signatures. Next, we present numerical studies based on Finite-Difference Time-Domain simulations to demonstrate the efficacy of MIST beamforming for detecting small malignant breast lesions in both prone and supine configurations. Finally, the experimental feasibility of UWB microwave imaging is demonstrated using an initial imaging prototype and multilayered breast phantoms.

关键词： biomedical electromagnetic imaging breast cancer microwave imaging ultra-wideband radar array signal processing FDTD methods microwave measurements

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Reinforcement Learning for Motion Policies in Mobile Relaying Networks

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IEEE TRANSACTIONS ON signal processing 2022年 70卷 850-861页

作者： Evmorfos, Spilios Diamantaras, Konstantinos, I Petropulu, Athina P. Rutgers State Univ Dept Elect & Comp Engn New Brunswick NJ 08854 USA Int Hellen Univ Cent Macedonia Thessaloniki 57001 Greece Rutgers State Univ New Brunswick NJ 08854 USA

We consider joint beamforming and relay motion control in mobile relay beamforming networks, operating in a spatio-temporally varying channel environment. A time slotted approach is adopted, where in each slot, the relays implement optimal beamforming and estimate their optimal positions for the next slot. We place the problem of relay motion control in a sequential decision-making framework. We employ Reinforcement Learning (RL) to guide the relay motion, with the goal of maximizing the cumulative signal-to-Interference+Noise Ratio (SINR) at the destination. First, we present a model based RL approach, which predictively estimates the SINR and accordingly determines the relay motion, based on partial knowledge of the channel model along with channel measurements at the current relay positions. Second, we propose a model-free deep Q-learning approach, which does not rely on channel models. For the deep Q-learning approach, we propose two modified Multilayer Perceptron Neural Networks (MLPs) for approximating the value function Q. The first modification applies a Fourier feature mapping of the state before passing it through the MLP. The second modification constitutes a different neural network architecture that uses sinusoids as activations between layers. Both modifications enable the MLP to better learn the high frequency value function and have a profound effect on convergence speed and SINR performance. Finally, we conduct a comparative analysis of all the presented approaches and provide insights on advantages and drawbacks.

关键词： Relays array signal processing Q-learning signal to noise ratio Motion control Interference Neural networks Reinforcement learning deep Q-learning mobile relay beamforming cooperative relay beamforming 2-hop relaying fourier feature mapping

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Low-Noise Low-Power Ultrasound AFE With Continuous TGC Built in Both TIA and Beamformer

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IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2023年第5期17卷 1062-1073页

作者： Yu, Xinwei Wang, Yan Ye, Fan Ren, Junyan Fudan Univ State Key Lab ASIC & Syst Shanghai 200433 Peoples R China

This article presents a low-noise high-power-efficiency analog front-end (AFE) for capacitive-micromachined-ultrasonic transducers (CMUT). Implemented in 28-nm CMOS technology, the proposed AFE features three-stage continuous time-gain compensation (TGC) embedded in both trans-impedance amplifiers (TIAs) and an analog beamformer to provide a large compensation range with no extra power-consumption cost. The use of noise cancellation and capacitive feedback optimizes the noise performance of TIAs. The first stage of the TGC is built in the TIA by adjusting the positive and negative resistance loads, which are composed of voltage-controlled transistor arrays. An all-pass passive network is used as the delay unit of the analog beamformer, meanwhile achieving the second TGC stage. Phase shift for all frequency components in the ultrasound pass-band is manifested as a delay to the echoes. The third stage of the TGC is merged with a summing unit, which is a closed-loop amplifier with variable resistance feedback. The design takes into account the ability to handle large signals and power consumption, with TIA and beamforming operating at voltages of 2.5 V and 0.9 V, respectively. Experimental results show that the proposed AFE achieves a 2.11 pA/root Hz input-referred noise (IRN) at the 5 MHz center frequency of the echoes while consuming only 1.02 mW/channel. A total exponential TGC range of 60 dB with continuous ranges of 12 dB, 24 dB, and 24 dB assigned to three stages has been verified for this work.

关键词： Delays Gain array signal processing Acoustics Ultrasonic imaging Receivers Impedance Ultrasound AFE time-gain compensation trans-impedance amplifier low-noise amplifier variable gain ultrasound signal

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Federated-Learning-Driven Radio Access Networks

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IEEE WIRELESS COMMUNICATIONS 2022年第4期29卷 48-54页

作者： Foukalas, Fotis Univ Thessaly Volos Greece

In this work, we present federated learning (FL) driven radio access mechanisms, which can be employed at the future radio access networks (RANs) to achieve high accuracy rather than data rate that was the objective in RANs without FL application so far. We first present low feedback FL techniques based on local aggregation updates such as sparsification and quantization, which enable a communication efficient FL application in RANs. Next, the concept of FL-driven radio access mechanisms is presented, which is considered the joint design/optimization of FL with beamforming, retransmission, resource allocation and scheduling respectively. The aim of each joint optimization is to achieve the highest accuracy of the considered training model on data originated from the connected devices. Finally, a simulation setup is developed to obtain simulation results, which show the advantage of using the proposed radio access mechanisms comparing with FL without joint design with RAN in terms of accuracy, feedback overhead and communication rounds.

关键词： Quantization (signal) Training data Optimization signal to noise ratio Mathematical models array signal processing Collaborative work Federated learning Radio access networks

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An ultrasonic obstacle detector based on phase beamforming principles

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IEEE SENSORS JOURNAL 2006年第1期6卷 179-186页

作者： Strakowski, MR Kosmowski, BB Kowalik, R Wierzba, P Gdansk Univ Technol Dept Optoelect PL-80952 Gdansk Poland

A prototype of an ultrasonic obstacle detector developed as a part of a navigation system for blind and visually impaired people is presented. The detector, which employs a single ultrasound source and an array of microphones, determines the distance to the obstacle by measuring time between sending the pulse and receiving the reflected signal. Using the phase beamforming technique, borrowed from hydroacoustics, to process the output signals of microphones, it determines also the direction from Which the reflected signal is received, thereby locating the obstacle. The obstacle detector was subjected to a series of tests in order to verify its design and to assess its ability to detect a broad range of obstacles. Presented test results show that most obstacles can be detected and recognized, and that the tested obstacle detector provides complete coverage of the safety zone in front of the user.

关键词： array signal processing beamforming navigation aid ultrasonic obstacle detector

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Electronic noses: a review of signal processing techniques

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IEE PROCEEDINGS-CIRCUITS DEVICES AND SYSTEMS 1999年第6期146卷 297-310页

作者： Hines, EL Llobet, E Gardner, JW Univ Warwick Elect & Elect Engn Div Sch Engn Coventry CV4 7AL W Midlands England Univ Rovira & Virgili Dept Elect Engn Tarragona 43006 Spain

The field of electronic noses, electronic instruments capable of mimicking the human olfactory system, has developed rapidly in the past ten years. There are now at least 25 research groups working in this area and more than ten companies have developed commercial instruments, which are mainly employed in the food and cosmetics industries. Most of the work published to date, and commercial applications, relate to the use of well established static pattern analysis techniques, such as principal components analysis, discriminant function analysis, cluster analysis and multilayer perceptron based neural networks. The authors first review static techniques that have been applied to the steady-state response of different odour sensors, e.g. resistive, acoustic and FET-based. Then they review the emerging field of the dynamic analysis of the sensor array response. Dynamic signal processing techniques reported so far include traditional parametric and nonparametric ones borrowed from the traditional field of system identification as well as linear filters, time series neural networks and others. Finally the authors emphasise the need for a systems approach to solve specific electronic nose applications, with associated problems of sensor drift and interference.

关键词： odour sensors dynamic analysis discriminant function analysis linear filters electronic noses cluster analysis sensor array response sensor drift signal processing techniques time series neural networks multilayer perceptron based neural networks array signal processing principal components analysis olfactory system gas sensors static pattern analysis techniques time series principal component analysis multilayer perceptrons

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Structured Covariance Matrix Estimation With Missing-(Complex) Data for Radar Applications via Expectation-Maximization

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IEEE TRANSACTIONS ON signal processing 2021年 69卷 5920-5934页

作者： Aubry, Augusto De Maio, Antonio Marano, Stefano Rosamilia, Massimo Univ Napoli Federico II Dept Elect Engn & Informat Technol DIETI I-80125 Naples Italy Natl Interuniv Consortium Telecommun I-43124 Parma Italy Univ Salerno Dipartimento Ingn Informaz Elettr & Matemat Appli I-84084 Fisciano SA Italy

Structured covariance matrix estimation in the presence of missing-(complex) data is addressed in this paper with emphasis on radar signal processing applications. After a motivation of the study, the array model is specified and the problem of computing the maximum likelihood estimate of a structured covariance matrix is formulated. A general procedure to optimize the observed-data likelihood function is developed resorting to the expectation-maximization algorithm. The corresponding convergence properties are thoroughly established and the rate of convergence is analyzed. The estimation technique is contextualized for two practically relevant radar problems: beamforming and detection of the number of sources. In the former case an adaptive beamformer leveraging the EM-based estimator is presented;in the latter, detection techniques generalizing the classic Akaike information criterion, minimum description length, and Hannan-Quinn information criterion, are introduced. Numerical results are finally presented to corroborate the theoretical study.

关键词： Covariance matrices Estimation Radar array signal processing Convergence Radar antennas Radar signal processing Missing data expectation-maximization algorithm adaptive array signal processing beamforming source number detection

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Frequency Diverse array Antenna: New Opportunities

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IEEE ANTENNAS AND PROPAGATION MAGAZINE 2015年第2期57卷 145-152页

作者： Wang, Wen-Qin Univ Elect Sci & Technol China Sch Commun & Informat Engn Chengdu 610054 Peoples R China

Phased-array antennas are known for their capability to electronically steer a beam with high effectiveness, but beam steering is fixed in an angle for all range cells. This paper reviews frequency diverse array (FDA) antennas. Different from a phased array, an FDA uses a small frequency increment, as compared with the carrier frequency, across array elements. The use of a frequency increment generates an array factor that is a function of the angle, the time, and the range, allowing the FDA antenna to transmit the energy over the desired range and angle. In addition to analyzing FDA factor characteristics, this paper investigates FDA potential applications in range-dependent energy control and technical challenges in system implementation, with an aim to call for further investigations on the FDA.

关键词： arrays array signal processing frequency diverse array (FDA) range dependent beamforming phased array

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Max-Min Fairness in IRS-Aided Multi-Cell MISO Systems With Joint Transmit and Reflective Beamforming

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2021年第2期20卷 1379-1393页

作者： Xie, Hailiang Xu, Jie Liu, Ya-Feng Guangdong Univ Technol Sch Informat Engn Guangzhou 510006 Peoples R China Chinese Univ Hong Kong Shenzhen Future Network Intelligence Inst FNii Shenzhen 518172 Peoples R China Chinese Univ Hong Kong Shenzhen Sch Sci & Engn Shenzhen 518172 Peoples R China Chinese Acad Sci Acad Math & Syst Sci Inst Computat Math & Sci Engn Comp State Key Lab Sci & Engn Comp Beijing 100190 Peoples R China

This paper investigates an intelligent reflecting surface (IRS)-aided multi-cell multiple-input single-output (MISO) network with a set of multi-antenna base stations (BSs) each communicating with multiple single-antenna users, in which an IRS is dedicatedly deployed for assisting the wireless transmission and suppressing the inter-cell interference. Under this setup, we jointly optimize the coordinated transmit beamforming vectors at the BSs and the reflective beamforming vector (with both reflecting phases and amplitudes) at the IRS, for the purpose of maximizing the minimum weighted signal-to-interference-plus-noise ratio (SINR) at the users, subject to the individual maximum transmit power constraints at the BSs and the reflection constraints at the IRS. To solve the non-convex min-weighted-SINR maximization problem, we first present an exact-alternating-optimization approach to optimize the transmit and reflective beamforming vectors in an alternating manner, in which the transmit and reflective beamforming optimization subproblems are solved exactly in each iteration by using the techniques of second-order-cone program (SOCP) and semi-definite relaxation (SDR), respectively. However, the exact-alternating-optimization approach has high computational complexity, and may lead to compromised performance due to the uncertainty of randomization in SDR. To avoid these drawbacks, we further propose an inexact-alternating-optimization approach, in which the transmit and reflective beamforming optimization subproblems are solved inexactly in each iteration based on the principle of successive convex approximation (SCA). In addition, to further reduce the computational complexity, we propose a low-complexity inexact-alternating-optimization design, in which the reflective beamforming optimization subproblem is solved more inexactly. Via numerical results, it is shown that the proposed three designs achieve significantly increased min-weighted-SINR values, as compared wi

关键词： array signal processing MISO communication Optimization Wireless communication signal to noise ratio Interference Computational complexity Intelligent reflecting surface (IRS) multi-cell systems multiple-input single-output (MISO) coordinated transmit beamforming reflective beamforming optimization

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THE FORWARD-BACKWARD AVERAGING TECHNIQUE APPLIED TO TLS-ESPRIT processing

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IEEE TRANSACTIONS ON signal processing 1995年第11期43卷 2691-2699页

作者： BACHL, R NATL UNIV SINGAPORE DEPT ELECT ENGNSINGAPORE 0511SINGAPORE

Certain array geometries greatly simplify and enhance high resolution array processing, In this paper, two techniques are used-the ESPRIT algorithm, which employs two shifted but otherwise identical subarrays, and forward-backward averaging, which can be applied to axis-symmetrical arrays, The former has been shown to provide an efficient solution to bearing estimation while the latter incorporates the a priori knowledge about the symmetry, effectively increasing the number of data vectors available and decorrelating coherent or highly correlated signals, A combination of the two techniques implies a special array geometry that includes uniformly spaced linear arrays, The resulting algorithm yields parameter estimates that are constrained on the unit circle, satisfying the postulated data model provided merely that the arguments of these estimates are distinct, However, if the arguments of some parameter estimates coincide in a given scenario, the ESPRIT algorithm does not yield different results for distinct signals and these estimates can be rejected, Perhaps the most significant advantage of combining forward-backward averaging with ESPRIT parameter estimation is the substantial reduction in computational complexity that can be achieved, Based on the centro-Hermitian property of the data and noise covariance matrices, the computational complexity of the ESPRIT solution is reduced almost by a factor of four and the algorithm can be formulated entirely over the field of real numbers.

关键词： Yield estimation Parameter estimation Geometry Computational complexity array signal processing Direction of arrival estimation Vectors Decorrelation Data models Noise reduction

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