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arXiv: Signal Processing
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1441
Papers 2440
1 page of 244 pages (2,440 results)
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Published on Nov 15, 2018in arXiv: Signal Processing
Multiple-input-multiple-output (MIMO) antennas performance can be degraded due to the poor isolation between the MIMO antenna elements. In this paper a review of the different isolation enhancement schemes available in the literature is presented. Empirically the isolation between the antennas can be improved by placing the antenna as far as possible and it can be enhanced further by introducing different isolation enhancement schemes. Theory of characteristic modes (TCM) was recently proposed t...
Published on Sep 4, 2019
Dominique Fourer4
Estimated H-index: 4
,
François Auger16
Estimated H-index: 16
This paper addresses the problem of efficiently jointly representing a non-stationary multicomponent signal in time and frequency. We introduce a novel enhancement of the time-reassigned synchrosqueezing method designed to compute sharpened and reversible representations of impulsive or strongly modulated signals. After establishing theoretical relations of the new proposed method with our previous results, we illustrate in numerical experiments the improvement brought by our proposal when appli...
Sangwoo Park1
Estimated H-index: 1
,
Hyeryung Jang3
Estimated H-index: 3
+ -3 AuthorsJoonhyuk Kang13
Estimated H-index: 13
This paper considers an Internet-of-Things (IoT) scenario in which devices transmit sporadically using short packets with few pilot symbols over a fading channel. Devices are characterized by unique transmission non-idealities, such as amplifiers' non-linear transfer functions. The number of pilots is generally insufficient to obtain an accurate estimate of the end-to-end channel, which includes the effects of fading and of the transmission-side distortion. This paper proposes to tackle this pro...
Nasir Saeed4
Estimated H-index: 4
,
Ahmed Elzanaty + -3 AuthorsMohamed-Slim Alouini68
Estimated H-index: 68
The research in the emerging space industry is becoming more and more attractive, given the increasing number of space-related applications. One primary entity of current space research is the design of miniaturized satellites, known as CubeSats, due to their numerous applications and low design and deployment cost. The new paradigm of connected space through CubeSats enables a wide range of applications such as Earth remote sensing, space exploration, and rural connectivity. CubeSats further pr...
Chengxi Li , You He (THU: Tsinghua University)+ -3 AuthorsPramod K. Varshney61
Estimated H-index: 61
In this letter, we consider the detection of sparse stochastic signals with sensor networks (SNs), where the fusion center (FC) collects 1-bit data from the local sensors and then performs global detection. For this problem, a newly developed 1-bit locally most powerful test (LMPT) detector requires 3.3Q sensors to asymptotically achieve the same detection performance as the centralized LMPT (cLMPT) detector with Q sensors. This 1-bit LMPT detector is based on 1-bit quantized observations withou...
Felix G. Hamza-Lup1
Estimated H-index: 1
(GS: Georgia Southern University),
Ionut Emil Iacob1
Estimated H-index: 1
(GS: Georgia Southern University),
Sushmita Khan (GS: Georgia Southern University)
A large number of sensors deployed in recent years in various setups and their data is readily available in dedicated databases or in the cloud. Of particular interest is real-time data processing and 3D visualization in web-based user interfaces that facilitate spatial information understanding and sharing, hence helping the decision making process for all the parties involved. In this research, we provide a prototype system for near real-time, continuous X3D-based visualization of processed se...
Weite Zhang1
Estimated H-index: 1
,
Hipolito Gomez-Sousa4
Estimated H-index: 4
+ -3 AuthorsJose A. Martinez-Lorenzo15
Estimated H-index: 15
(NU: Northeastern University)
In this work, a physical and geometrical optics based single-frequency imaging scheme is proposed for personal screening systems using multiple reconfigurable reflectarrays. This scheme is able to not only reconstruct profiles of potential threat objects on human body, but also identify their materials in terms of their complex relative permittivities. Both simulation and experiment are carried out to detect dielectric objects at a microwave frequency of 24.16 GHz. The object profiles and comple...
Jinhui Lu3
Estimated H-index: 3
,
Yuntian Wang (Nanjing University of Science and Technology)+ -3 AuthorsZhu Han69
Estimated H-index: 69
(UH: University of Houston)
In order to overcome the inherent latency in multi-user unmanned aerial vehicle (UAV) networks with orthogonal multiple access (OMA). In this paper, we investigate the UAV enabled uplink non-orthogonal multiple access (NOMA) network, where a UAV is deployed to collect the messages transmitted by ground users. In order to maximize the sum rate of all users and to meet the quality of service (QoS) requirement, we formulate an optimization problem, in which the UAV deployment position and the power...
In the traditional load flow analysis, a key assumption is that the input variables, i.e., generator output and customer demand, are fixed in time and the associated response has no variability. This assumption, however, is no longer valid as the adoption of renewable energy resources add more variability and uncertainty to the modern electrical system. Addressing these concerns is the definition of the Probabilistic Load Flow (PLF) problem. The challenge of the PLF problem lies in handling high...
Udit Gupta3
Estimated H-index: 3
(Harvard University),
Brandon Reagen7
Estimated H-index: 7
+ -3 AuthorsDavid M. Brooks41
Estimated H-index: 41
Recurrent neural networks (RNNs) are becoming the de facto solution for speech recognition. RNNs exploit long-term temporal relationships in data by applying repeated, learned transformations. Unlike fully-connected (FC) layers with single vector matrix operations, RNN layers consist of hundreds of such operations chained over time. This poses challenges unique to RNNs that are not found in convolutional neural networks (CNNs) or FC models, namely large dynamic activation. In this paper we prese...
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