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Ronald Y. Chang
Center for Information Technology
Mathematical optimizationMIMOComputer networkComputer scienceReal-time computing
94Publications
12H-index
860Citations
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Publications 92
Newest
Dec 1, 2019 in GLOBECOM (Global Communications Conference)
#1Shing-Jiuan Liu (AS: Academia Sinica)
#1Shing-Jiuan Liu (UC Davis: University of California, Davis)H-Index: 1
Last. Feng-Tsun Chien (NCTU: National Chiao Tung University)H-Index: 7
view all 3 authors...
Device-free indoor localization is a key enabling technology for many Internet of Things (IoT) applications. Deep neural network (DNN)-based location estimators achieve high-precision localization performance by automatically learning discriminative features from noisy wireless signals without much human intervention. However, the inner workings of DNN are not transparent and not adequately understood especially in wireless localization applications. In this paper, we conduct visual analyses of ...
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#1Kevin M. Chen (CIT: Center for Information Technology)H-Index: 1
#2Ronald Y. Chang (CIT: Center for Information Technology)H-Index: 12
Last. Shing-Jiuan Liu (UC Davis: University of California, Davis)H-Index: 1
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In this paper, we propose a convolutional neural network (CNN) model for device-free fingerprinting indoor localization based on Wi-Fi channel state information (CSI). Besides, we develop an interpretation framework to understand the representations learned by the model. By quantifying and visualizing CNN in comparison with the fully-connected feedforward deep neural network (DNN) (or multilayer perceptron), we observe that each model can automatically identify location-specific patterns, which ...
1 CitationsSource
#1Shing-Jiuan Liu (CIT: Center for Information Technology)H-Index: 1
#2Ronald Y. Chang (CIT: Center for Information Technology)H-Index: 12
Last. Feng-Tsun Chien (NCTU: National Chiao Tung University)H-Index: 7
view all 3 authors...
Device-free Wi-Fi indoor localization has received significant attention as a key enabling technology for many Internet of Things (IoT) applications. Machine learning-based location estimators, such as the deep neural network (DNN), carry proven potential in achieving high-precision localization performance by automatically learning discriminative features from the noisy wireless signal measurements. However, the inner workings of the DNNs are not transparent and not adequately understood, espec...
Source
#1Cenk M. Yetis (CIT: Center for Information Technology)H-Index: 6
#2Ronald Y. Chang (CIT: Center for Information Technology)H-Index: 12
In this paper, multi-stream transmission in interference networks aided by multiple amplify-and-forward (AF) relays in the presence of direct links is studied. The objective is to minimize the sum power of transmitters and relays by distributed transmit beamforming optimization under the stream signal-to-interference-plus-noise-ratio (SINR) target constraints. We utilize alternating direction method of multipliers (ADMM) algorithm for distributed implementation. The optimization problem is a wel...
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#1Imad Ali (AS: Academia Sinica)H-Index: 2
#2Ronald Y. Chang (CIT: Center for Information Technology)H-Index: 12
Last. Cheng-Hsin Hsu (NTHU: National Tsing Hua University)H-Index: 23
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Recent research has suggested that answers to the particular questions may be found when the questions are forwarded via suitable friends (or helpers) in a multi-hop manner. In mobile social network-based question answering systems, users are associated with limited resources; therefore, a light-weight scheme is crucial. However, improving the performance of the system with a light-weight scheme is challenging. To this end, we propose a distributed SOcial helpeR selecTion (SORT) scheme where all...
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#1Jhe-Yi Lin (NTU: National Taiwan University)H-Index: 1
#2Ronald Y. Chang (CIT: Center for Information Technology)H-Index: 12
Last. Hsuan-Jung Su (NTU: National Taiwan University)H-Index: 18
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For rate optimization in interference limited networks, improper Gaussian signaling has shown its ability to outperform conventional proper Gaussian signaling. In this paper, we study a weighted sum-rate maximization problem with improper Gaussian signaling for the multiple-input multiple-output interference broadcast channel. To solve this nonconvex and NP-hard problem, we propose an effective separate covariance and pseudo-covariance matrices optimization algorithm. In the covariance optimizat...
1 CitationsSource
In this paper, multi-stream transmission in interference networks aided by multiple amplify-and-forward (AF) relays in the presence of direct links is considered. The objective is to minimize the sum power of transmitters and relays by beamforming optimization under the stream signal-to-interference-plus-noise-ratio (SINR) constraints. For transmit beamforming optimization, the problem is a well-known non-convex quadratically constrained quadratic program (QCQP) that is NP-hard to solve. After s...
#1Hung-Wei Hsu (NTU: National Taiwan University)H-Index: 1
#2Yih-Cherng Lee (NTU: National Taiwan University)H-Index: 1
Last. Ronald Y. Chang (CIT: Center for Information Technology)H-Index: 12
view all 4 authors...
Marine mammal detection is helpful for ecological conservation. In this paper, we proposed a novel automatic method in real-time to detect and recognize the dolphin that is underwater and just reveals some characteristics of the body. The proposed method is based on the convolutional neural network with an extra masking layer to approximate various filter without knowing the normal neural network, which explore a discriminative criterion to enhance the image segmentation performance. We evaluate...
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Dec 1, 2018 in GLOBECOM (Global Communications Conference)
#1Chi-Han Lee (NTUST: National Taiwan University of Science and Technology)H-Index: 1
#2Ronald Y. Chang (CIT: Center for Information Technology)H-Index: 12
Last. Shin-Ming Cheng (NTUST: National Taiwan University of Science and Technology)H-Index: 16
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This paper considers the precoder design for energy- efficient data transmissions in energy harvesting (EH)-aided device-to-device (D2D) communications underlaid multiple-input multiple-output (MIMO) cellular networks. We aim to maximize the energy efficiency (EE) of the network, defined as the ratio of the system sum rate to the system power consumption, under EH and transmit power constraints for both cellular and D2D users. The considered problem is nonconvex due to the concave-convex and fra...
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Dec 1, 2018 in GLOBECOM (Global Communications Conference)
#1Ronald Y. Chang (CIT: Center for Information Technology)H-Index: 12
#2Shing-Jiuan Liu (CIT: Center for Information Technology)H-Index: 1
Last. Yen-Kai Cheng (CIT: Center for Information Technology)H-Index: 2
view all 3 authors...
This paper proposes an economical, nonintrusive, and high-precision indoor localization scheme based on Wi-Fi fingerprinting that requires only a single Wi- Fi access point and a single fixed-location receiver. A deep neural network (DNN) based classification model is trained with Wi-Fi channel state information (CSI) fingerprints for localizing the target without any device attached (i.e., device-free). CSI provides finer-grained information than received signal strength (RSS). CSI pre- process...
1 CitationsSource
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