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Non-linear Manifold Clustering based on Conformity Index 基于一致性指标的非线性流形聚类
2020 54th Asilomar Conference on Signals, Systems, and Computers Pub Date : 2020-11-01 DOI: 10.1109/IEEECONF51394.2020.9443279
M. Sedghi, George K. Atia, M. Georgiopoulos
{"title":"Non-linear Manifold Clustering based on Conformity Index","authors":"M. Sedghi, George K. Atia, M. Georgiopoulos","doi":"10.1109/IEEECONF51394.2020.9443279","DOIUrl":"https://doi.org/10.1109/IEEECONF51394.2020.9443279","url":null,"abstract":"This paper presents Manifold Clustering based on Conformity Index (MCC), a remarkably fast and powerful manifold clustering approach. The proposed method identifies points belonging to a cluster by examining a novel quantity which measures the level of conformity of the points to a manifold structure. Despite the usual convention of constructing neighborhood structures for handling the non-linearity, we employ the Reproducing Kernel Hilbert spaces to effectively define and calculate our measure such that it can capture the manifold structure effectively. The global view of the underlying manifold geometry coupled with its extremely simple algorithm makes MCC superior to the other state-of-the-art methods. Gained advantages are confirmed by experimental results on both synthetic and real data.","PeriodicalId":248190,"journal":{"name":"2020 54th Asilomar Conference on Signals, Systems, and Computers","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134374453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Energy-Efficient Analog Beamforming with Short Packets in Millimeter-Wave MIMO Systems 毫米波MIMO系统中具有短数据包的高能效模拟波束形成
2020 54th Asilomar Conference on Signals, Systems, and Computers Pub Date : 2020-11-01 DOI: 10.1109/IEEECONF51394.2020.9443474
Jordi Borras, Francesc Molina, Roberto López-Valcarce, J. Sala-Álvarez
{"title":"Energy-Efficient Analog Beamforming with Short Packets in Millimeter-Wave MIMO Systems","authors":"Jordi Borras, Francesc Molina, Roberto López-Valcarce, J. Sala-Álvarez","doi":"10.1109/IEEECONF51394.2020.9443474","DOIUrl":"https://doi.org/10.1109/IEEECONF51394.2020.9443474","url":null,"abstract":"The energy-aware design of fully analog precoders and combiners is investigated in this paper. To that aim, we consider a millimeter-wave short-packet communication scenario where power consumption and hardware complexity constitute relevant factors. User terminals employ a single channel encoder and, at hardware level, they implement analog architectures that combine phase shifters and switches. Additionally, transmitting terminals also leverage a power control system. An energy efficiency figure of merit is considered, and its optimization subject to finite packet-length constraints is tackled cyclically over disconnected feasible sets. Numerical results are reported firstly, to illustrate the advantages of the proposed short-packet fully analog design, secondly, to compare its performance to that of on-off beamforming, and finally, to discuss the optimality of proposed optimization algorithm.","PeriodicalId":248190,"journal":{"name":"2020 54th Asilomar Conference on Signals, Systems, and Computers","volume":"235 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131643802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Finite-Time In-Network Computation of Linear Transforms 线性变换的有限时间网络内计算
2020 54th Asilomar Conference on Signals, Systems, and Computers Pub Date : 2020-11-01 DOI: 10.1109/IEEECONF51394.2020.9443482
S. Kar, Markus Püschel, José M. F. Moura
{"title":"Finite-Time In-Network Computation of Linear Transforms","authors":"S. Kar, Markus Püschel, José M. F. Moura","doi":"10.1109/IEEECONF51394.2020.9443482","DOIUrl":"https://doi.org/10.1109/IEEECONF51394.2020.9443482","url":null,"abstract":"This paper focuses on finite-time in-network computation of linear transforms of distributed graph data. Finite-time transform computation problems are of interest in graph-based computing and signal processing applications in which the objective is to compute, by means of distributed iterative methods, various (linear) transforms of the data distributed at the agents or nodes of the graph. While finite-time computation of consensus-type or more generally rank-one transforms have been studied, systematic approaches toward scalable computing of general linear transforms, specifically in the case of heterogeneous agent objectives in which each agent is interested in obtaining a different linear combination of the network data, are relatively less explored. In this paper, by employing ideas from algebraic geometry, we develop a systematic characterization of linear transforms that are amenable to distributed in-network computation in finite-time using linear iterations. Further, we consider the general case of directed inter-agent communication graphs. Specifically, it is shown that almost all linear transformations of data distributed on the nodes of a digraph containing a Hamiltonian cycle may be computed using at most N linear distributed iterations. Finally, by studying an associated matrix factorization based reformulation of the transform computation problem, we obtain, as a by-product, certain results and characterizations on sparsity-constrained matrix factorization that are of independent interest.","PeriodicalId":248190,"journal":{"name":"2020 54th Asilomar Conference on Signals, Systems, and Computers","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132971031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Waveform Optimization for Near-Field Wireless Powered Communication Using a Coil Array 基于线圈阵列的近场无线供电通信波形优化
2020 54th Asilomar Conference on Signals, Systems, and Computers Pub Date : 2020-11-01 DOI: 10.1109/IEEECONF51394.2020.9443363
Tomohiro Arakawa, J. Krogmeier, D. Love
{"title":"Waveform Optimization for Near-Field Wireless Powered Communication Using a Coil Array","authors":"Tomohiro Arakawa, J. Krogmeier, D. Love","doi":"10.1109/IEEECONF51394.2020.9443363","DOIUrl":"https://doi.org/10.1109/IEEECONF51394.2020.9443363","url":null,"abstract":"Driven by the growing number of Internet of Things (IoT) devices, there is a pressing need for powering devices wirelessly while communicating with them. This paper considers wireless powered communication (WPC) using near-field inductive coupling, a technique to communicate with remote devices that do not have batteries or a power supply. While near-field WPC has long been used for passive radio-frequency identification (RFID) systems, the performances of communication and power transfer have not been fully analyzed. This paper models near-field WPC using a coil array based on an abstract circuit model in which the characteristics of mutual coupling and other linear effects are captured by a small number of parameters. We investigate how the choices of load impedances and source voltages affect the performance of power transfer and communication. The improvement in power and information transfer are verified by simulation.","PeriodicalId":248190,"journal":{"name":"2020 54th Asilomar Conference on Signals, Systems, and Computers","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130760874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Co-array Music under Angle-Independent Nonidealities 角无关非理想性下的共阵音乐
2020 54th Asilomar Conference on Signals, Systems, and Computers Pub Date : 2020-11-01 DOI: 10.1109/IEEECONF51394.2020.9443519
Robin Rajamäki, V. Koivunen
{"title":"Co-array Music under Angle-Independent Nonidealities","authors":"Robin Rajamäki, V. Koivunen","doi":"10.1109/IEEECONF51394.2020.9443519","DOIUrl":"https://doi.org/10.1109/IEEECONF51394.2020.9443519","url":null,"abstract":"The difference co-array is crucial in determining the number of resolvable sources in direction-of-arrival (DoA) estimation. This virtual array of pairwise sensor position differences enables sparse arrays to identify vastly more sources than sensors. However, the idealized assumptions giving rise to the co-array, such as isolated omnidirectional gain patterns, may not hold in practice. Consequently, the applicability of the co-array model to real-world arrays needs to be investigated thoroughly. In this work, we consider a general class of angle-independent departures from the ideal model caused by nonideal sensors or compression of the array measurements. We study the impact of these nonidealities on DoA estimation using co-array MUSIC, assuming that the array is calibrated and that an infinite number of snapshots is available. We establish that proper use of the calibration data enables unbiased DoA estimation of more sources than sensors. Nonidealities may nevertheless cause subspace swap at low SNR.","PeriodicalId":248190,"journal":{"name":"2020 54th Asilomar Conference on Signals, Systems, and Computers","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130867952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Respiration and Cardiac Activity Sensing Using 3-D Cameras 呼吸和心脏活动传感使用3d相机
2020 54th Asilomar Conference on Signals, Systems, and Computers Pub Date : 2020-11-01 DOI: 10.1109/IEEECONF51394.2020.9443331
Yu Rong, S. Srinivas, Huiwen Chu, Hanguang Yu, Kailing Liu, D. Bliss
{"title":"Respiration and Cardiac Activity Sensing Using 3-D Cameras","authors":"Yu Rong, S. Srinivas, Huiwen Chu, Hanguang Yu, Kailing Liu, D. Bliss","doi":"10.1109/IEEECONF51394.2020.9443331","DOIUrl":"https://doi.org/10.1109/IEEECONF51394.2020.9443331","url":null,"abstract":"Remote vital sign monitoring at home with commercially viable hardware extends care from hospital wards to personal settings without overwhelming health care providers and resources. In this paper, we explore usage of Azure Kinect (Microsoft) to monitor respiration and cardiac activity of a subject. We propose a fusion sensing technique that ensures immunity to ambient lighting conditions and movements of the subject, two key limitations while employing cameras or radars respectively. The functionality of this process is enabled by the phenomenon of Photoplethysmography (PPG) and availability of commercial sensors that can leverage it. We investigate robustness of the proposed technique by conducting experiments in variable lighting conditions while the subject is in motion. A comparison is drawn to an RGB camera and the results are validated using a pulse oximeter, a contact PPG sensor.","PeriodicalId":248190,"journal":{"name":"2020 54th Asilomar Conference on Signals, Systems, and Computers","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130837730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
Learning a Low-Complexity Channel Estimator for One-Bit Quantization 学习一种低复杂度的一比特量化信道估计器
2020 54th Asilomar Conference on Signals, Systems, and Computers Pub Date : 2020-11-01 DOI: 10.1109/IEEECONF51394.2020.9443563
B. Fesl, M. Koller, N. Turan, W. Utschick
{"title":"Learning a Low-Complexity Channel Estimator for One-Bit Quantization","authors":"B. Fesl, M. Koller, N. Turan, W. Utschick","doi":"10.1109/IEEECONF51394.2020.9443563","DOIUrl":"https://doi.org/10.1109/IEEECONF51394.2020.9443563","url":null,"abstract":"A low-complexity convolutional neural network (CNN) channel estimator has been proposed recently, which was designed based on assumptions on the underlying channel model. In this work, we investigate how one-bit quantized observations affect this CNN estimator. In contrast to many other approaches, we propose a technique to obtain only one CNN estimator for a whole range of signal-to-noise ratio (SNR) values. We compare the performance of this estimator with a linear minimum mean square error (LMMSE) estimator based on the Bussgang decomposition and also with a state-of-the-art maximum a posteriori (MAP) approach, which exploits an approximate sparsity of the channels.","PeriodicalId":248190,"journal":{"name":"2020 54th Asilomar Conference on Signals, Systems, and Computers","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130996619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Asynchronous Successive Interference Cancellation for 5G Receiver Operating in Shared Spectrum with Different Radio System 不同无线电系统共享频谱下5G接收机的异步连续干扰消除
2020 54th Asilomar Conference on Signals, Systems, and Computers Pub Date : 2020-11-01 DOI: 10.1109/IEEECONF51394.2020.9443560
I. Kanno, R. Kataoka, Toshinori Suzuki, H. Ishikawa, K. Yamazaki, Y. Kishi
{"title":"Asynchronous Successive Interference Cancellation for 5G Receiver Operating in Shared Spectrum with Different Radio System","authors":"I. Kanno, R. Kataoka, Toshinori Suzuki, H. Ishikawa, K. Yamazaki, Y. Kishi","doi":"10.1109/IEEECONF51394.2020.9443560","DOIUrl":"https://doi.org/10.1109/IEEECONF51394.2020.9443560","url":null,"abstract":"This paper deals with a receiver design for 5G operated as secondary radio in spectrum sharing with different radio system. In the scenario, the receiver suffers from asynchronous interference from the primary system which utilize different transmission waveform parameters from 5G, such as sampling rate and symbol duration. The proposed receiver employs successive interference cancellation of the primary system to decode 5G. For realizing asynchronous cancellation with single front end and ADC, the architecture includes sampling rate conversions of the received and replica signal. Computer simulation shows the proposed receiver can improve performance significantly.","PeriodicalId":248190,"journal":{"name":"2020 54th Asilomar Conference on Signals, Systems, and Computers","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132919534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Privacy-Preserving Distributed Learning with Nonsmooth Objective Functions 非光滑目标函数下的隐私保护分布式学习
2020 54th Asilomar Conference on Signals, Systems, and Computers Pub Date : 2020-11-01 DOI: 10.1109/IEEECONF51394.2020.9443287
François Gauthier, C. Gratton, Naveen K. D. Venkategowda, Stefan Werner
{"title":"Privacy-Preserving Distributed Learning with Nonsmooth Objective Functions","authors":"François Gauthier, C. Gratton, Naveen K. D. Venkategowda, Stefan Werner","doi":"10.1109/IEEECONF51394.2020.9443287","DOIUrl":"https://doi.org/10.1109/IEEECONF51394.2020.9443287","url":null,"abstract":"This paper develops a fully distributed differentially-private learning algorithm based on the alternating direction method of multipliers (ADMM) to solve nonsmooth optimization problems. We employ an approximation of the augmented Lagrangian to handle nonsmooth objective functions. Furthermore, we perturb the primal update at each agent with a time-varying Gaussian noise with decreasing variance to provide zero-concentrated differential privacy. The developed algorithm has competitive privacy-accuracy trade-off and applies to nonsmooth and non necessarily strongly convex problems. Convergence and privacy-preserving properties are confirmed via both theoretical analysis and simulations.","PeriodicalId":248190,"journal":{"name":"2020 54th Asilomar Conference on Signals, Systems, and Computers","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133067813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Non-invasive Deep Brain Stimulation using Electromagnetic Waves 使用电磁波的非侵入性深部脑刺激
2020 54th Asilomar Conference on Signals, Systems, and Computers Pub Date : 2020-11-01 DOI: 10.1109/IEEECONF51394.2020.9443281
Fatima Ahsan, T. Chi, Raymond Y. Cho, S. Sheth, W. Goodman, B. Aazhang
{"title":"Non-invasive Deep Brain Stimulation using Electromagnetic Waves","authors":"Fatima Ahsan, T. Chi, Raymond Y. Cho, S. Sheth, W. Goodman, B. Aazhang","doi":"10.1109/IEEECONF51394.2020.9443281","DOIUrl":"https://doi.org/10.1109/IEEECONF51394.2020.9443281","url":null,"abstract":"This paper presents the novel study of deep brain stimulation using electromagnetic waves. Using giga-hertz electric fields, we can manipulate both amplitudes and phases to achieve focal stimulation at target regions inside the brain tissue. However, the issue with this approach would be that neurons have priorly been shown to respond to lower frequency electric fields (~1kHz). To overcome this issue, similar to the recently proposed temporal interference stimulation for electric currents, we propose using two giga-hertz electromagnetic waves differing from each other by a small frequency offset to potentially modulate neurons for non-invasive deep brain stimulation purposes. Moreover, leveraging the advances in antenna technology, we can create miniature antenna arrays at giga-hertz that can be endocranially implanted to allow for continuous operation, which can also help mitigate signal attenuation. To achieve high focality, we then propose an optimization framework that optimizes the antenna array phases and amplitudes to achieve focal stimulation at multiple target regions inside the brain tissue without moving the antenna arrays. We test the efficacy of our proposed method via Finite Element Method simulations on four realistic 2D human brain phantoms. Our results show that with endocranially implanted array size of mean 4.6cm consisting of point source antenna array elements, a focality of mean 3cm can be achieved at targets deep inside the brain tissue.","PeriodicalId":248190,"journal":{"name":"2020 54th Asilomar Conference on Signals, Systems, and Computers","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133153086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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