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arXiv 2020年

作者： Huang, Jie Wang, Cheng-Xiang Bai, Lu Sun, Jian Yang, Yang Li, Jie Tirkkonen, Olav Zhou, Ming-Tuo National Mobile Communications Research Laboratory School of Information Science and Engineering Southeast University Nanjing210096 China Purple Mountain Laboratories Nanjing211111 China School of Cyber Science and Technology Beihang University Beijing100191 China Shandong Provincial Key Lab of Wireless Communication Technologies School of Information Science and Engineering Shandong University Qingdao266237 China ShanghaiTech University Shanghai201210 China Department of Computer Science and Engineering Shanghai Jiaotong University Shanghai200240 China Aalto University Espoo02150 Finland Shanghai200050 China

The standardization process of the fifth generation (5G) wireless communications has recently been accelerated and the first commercial 5G services would be provided as early as in 2018. The increasing of enormous smartphones, new complex scenarios, large frequency bands, massive antenna elements, and dense small cells will generate big datasets and bring 5G communications to the era of big data. This paper investigates various applications of big data analytics, especially machine learning algorithms in wireless communications and channel modeling. We propose a big data and machine learning enabled wireless channel model framework. The proposed channel model is based on artificial neural networks (ANNs), including feed-forward neural network (FNN) and radial basis function neural network (RBF-NN). The input parameters are transmitter (Tx) and receiver (Rx) coordinates, Tx-Rx distance, and carrier frequency, while the output parameters are channel statistical properties, including the received power, root mean square (RMS) delay spread (DS), and RMS angle spreads (ASs). Datasets used to train and test the ANNs are collected from both real channel measurements and a geometry based stochastic model (GBSM). Simulation results show good performance and indicate that machine learning algorithms can be powerful analytical tools for future measurement-based wireless channel modeling. Copyright © 2020, The Authors. All rights reserved.

关键词： 5G mobile communication systems

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A Monte Carlo based computation offloading algorithm for feeding robot IoT system 1

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3rd International Conference on Smart Computing and communications, SmartCom 2018

作者： Zhang, Cheng Ohashi, Takumi Saijo, Miki Solis, Jorge Takeda, Yukio Lindborg, Ann-Louise Takeda, Ryuta Tanaka, Yoshiaki Department of Computer Science and Communications Engineering Waseda University Tokyo169-0072 Japan Tokyo Institute of Technology Tokyo152-8550 Japan Department of Engineering and Physics Karlstad University Karlstad Sweden Camanio Care AB Norgegatan 2 4tr Nacka164 32 Sweden Leave a Nest Co. Ltd. Tokyo162-0822 Japan Global Information and Telecommunication Institute Waseda University Tokyo169-8555 Japan Department of Communications and Computer Engineering Waseda University Tokyo169-8555 Japan

ISBN: (数字)9783030057558

ISBN: (纸本)9783030057541

Ageing is becoming an increasingly major problem in European and Japanese societies. We have so far mainly focused on how to improve the eating experience for both frail elderly and caregivers by introducing and developing the eating aid robot, Bestic, made to get the food from plate to the mouth for frail elderly or person with disabilities. We expand the functionalities of Bestic to create food intake reports automatically so as to decrease the undernutrition among frail elderly and workload of caregivers through collecting data via a vision system connected to the Internet of Things (IoT) system. Since the computation capability of Bestic is very limited, computation offloading, in which resource intensive computational tasks are transferred from Bestic to an external cloud server, is proposed to solve Bestic’s resource limitation. In this paper, we proposed a Monte Carlo algorithm based heuristic computation offloading algorithm, to minimize the total overhead of all the Bestic users after we show that the target optimization problem is NP-hard in a theorem. Numeric results showed that the proposed algorithm is effective in terms of system-wide overhead. © 2018, Springer Nature Switzerland AG.

关键词： Internet of things

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Channel Aware Sparse Signaling for Ultra Low-latency Communication in TDD systems

Channel Aware Sparse Signaling for Ultra Low-latency Communi...

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IEEE Vehicular Technology Conference

作者： Wonjun Kim Hyoungju Ji Byonghyo Shim Institute of New Media and Communications and Department of Electrical and Computer Engineering Seoul National University

ISBN: (纸本)9781538663592;9781538663585

Fifth generation (5G) wireless networks are currently being developed to handle wide variety of use cases. In order to support these cases, new types of requirements other than throughput enhancement have been introduced. One such requirement is to reduce the latency down to a millisecond (ms) level in ultra reliable and low latency communications (URLL-C). In case of uplink transmission, supporting this stringent latency requirement is quite challenging and problematic since the scheduling procedure is a time-consuming and complicated handshaking process. In time division duplexing (TDD) systems, satisfying the latency requirement is far more difficult since the mobile device cannot transmit the data when the subframe is assigned for the downlink. In this paper, we propose a new type of uplink transmission scheme for TDD-based URLLC. Key idea of the proposed scheme is to transmit the latency sensitive data immediately after performing the ultra-short one-way signaling from the basestation to the mobile device. To reduce the processing time of grant signal, we present a fast signaling mechanism, referred to as channel-aware sparse signaling (CASS). Numerical results confirm that the proposed uplink transmission scheme is very effective in TDD-based URLLC systems.

关键词： Latency tal demand distortion up link door bucks Signal Transduction Signaling Communication Research processing time

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Receiver Parameters Effect on Underwater Optical Wireless Communication Performance in the Presence of Transmitted Gaussian Beam 11

Receiver Parameters Effect on Underwater Optical Wireless Co...

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11th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2018

作者： Vali, Zahra Gholami, Asghar Ghassemlooy, Zabih Omoomi, Masood Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan*** Iran Optical Communications Research Group Northumbria University Newcastle-Upon-TyneNE1 8ST United Kingdom

ISBN: (纸本)9781538613351

Using divergent Gaussian beams mitigates the transmitter (Tx) and the receiver (Rx) misalignment in underwater optical wireless communications (UOWC) point-to-point links and increases the maximum acceptable lateral offset (MALO) at the Rx. However, extra spatial dispersion, temporal dispersion and angular spreading do occur compared to multiple scattering. Therefore, it is important to optimize the Rx for power loss, channel bandwidth and angle of arrival (AOA) distribution. Here both the field of view (FOV) and the aperture size of the Rx are investigated. We show how the required FOV of the Rx can be obtained from the AOA distribution, and also investigate how FOV and the aperture size of the Rx can be selected to minimize the power loss and the channel bandwidth degradation. To illustrate the effect of multiple scattering, results are presented for both clear and harbor waters. © 2018 IEEE.

关键词： Underwater optical wireless communication

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Sum-Rate Maximization of Uplink Rate Splitting Multiple Access (RSMA) Communication

Sum-Rate Maximization of Uplink Rate Splitting Multiple Acce...

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2019 IEEE Global communications Conference (GLOBECOM)

作者： Zhaohui Yang Mingzhe Chen Walid Saad Wei Xu Mohammad Shikh-Bahaei Department of Engineering Centre for Telecommunications Research King's College London London UK Electrical Engineering Department Princeton University USA Chinese University of Hong Kong Shenzhen China Bradley Department of Electrical and Computer Engineering Wireless@VT Virginia Tech Blacksburg VA USA National Mobile Communications Research Laboratory Southeast University Nanjing China

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

In this paper, the problem of maximizing sum-rate for uplink rate splitting multiple access (RSMA) communications is studied. In the considered model, each user transmits two messages to the base station (BS) with separate transmit power and the BS will use a successive decoding technique to decode the received messages. To maximize each user's transmission rate, the users must adjust their transmit power and the BS must determine the decoding order of the messages transmitted from the users to the BS. This problem is formulated as a sum-rate maximization problem with proportional rate constraints by adjusting the users' transmit power and the BS's decoding order. However, since the decoding order variable in the optimization problem is discrete, the original minimization problem with transmit power and decoding order variables can be transformed into a problem with only the rate splitting variable. Then, the optimal rate splitting of each user is determined. Given the optimal rate splitting of each user and a decoding order, the optimal transmit power of each user is determined. Next, the optimal decoding order is determined by an exhaustive search method. To further reduce the complexity of the optimization algorithm used for sum-rate maximization in RSMA, a user pairing based algorithm is introduced, which enables two users to use RSMA in each pair and also enables the users in different pairs to be allocated with orthogonal frequency. Simulation results show that RSMA can achieve up to 10.0%, 22.2%, and 83.7% gains in terms of rate compared to non-orthogonal multiple access (NOMA), frequency division multiple access (FDMA), and time division multiple access (TDMA).

关键词： Decoding Uplink Wireless networks NOMA Optimization Time division multiple access Resource management

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Primate Markerless Pose Estimation and Movement Analysis Using DeepLabCut

Primate Markerless Pose Estimation and Movement Analysis Usi...

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International Conference on Informatics, Electronics & Vision (ICIEV)

作者： Rollyn Labuguen Dean Karlo Bardeloza Salvador Blanco Negrete Jumpei Matsumoto Kenichi Inoue Tomohiro Shibata Graduate School of Life Science and Systems Engineering Kyushu Institute of Technology Kitakyushu Japan Department of Electronics Computer and Communications Engineering Ateneo de Manila University Quezon Philippines System Emotional Science University of Toyama Toyama Japan Systems Neuroscience Section Kyoto University

The analysis and understanding of primate behavior play a fundamental role in fields such as neuroscience, medicine, psychology, genetics, and more. This paper demonstrates an automatic detection of primate features by using an open-source deep learning toolset, DeepLabCut. We trained the deep neural network to locate 17 features and extract the monkey pose by relating the set of features detected. The model is trained with 5,967 manually annotated monkey images, which achieved train and test set errors of 3.61 and 19.72 unit pixels respectively. We also plotted the feature trajectories across multiple frames to show that the trained model can be used for analyzing behavior.

关键词： Feature extraction Training Predictive models Wrist Task analysis Nose Pose estimation

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ACT: An Autonomous Drone Cinematography System for Action Scenes

ACT: An Autonomous Drone Cinematography System for Action Sc...

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2018 IEEE International Conference on Robotics and Automation, ICRA 2018

作者： Huang, Chong Gao, Fei Pan, Jie Yang, Zhenyu Qiu, Weihao Chen, Peng Yang, Xin Shen, Shaojie Cheng, Kwang-Ting Tim Department of Electrical and Computer Engineering University of California Santa Barbara Santa BarbaraCA93106 United States Department of Electrical and Computer Engineering Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong College of Information and Engineering Zhejiang University of Technology Hangzhou310023 China School of Electronics Information and Communications Huazhong University of Science and Technology Wuhan Hubei430074 China

ISBN: (纸本)9781538630815

Drones are enabling new forms of cinematography. Aerial filming via drones in action scenes is difficult because it requires users to understand the dynamic scenarios and operate the drone and camera simultaneously. Existing systems allow the user to manually specify the shots and guide the drone to capture footage, while none of them employ aesthetic objectives to automate aerial filming in action scenes. Meanwhile, these drone cinematography systems depend on the external motion capture systems to perceive the human action, which is limted to the indoor environment. In this paper, we propose an Autonomous CinemaTography system 'ACT' on the drone platform to address the above the challenges. To our knowledge, this is the first drone camera system which can autonomously capture cinematic shots of action scenes based on limb movements in both indoor and outdoor environments. Our system includes the following novelties. First, we propose an efficient method to extract 3D skeleton points via a stereo camera. Second, we design a real-time dynamical camera planning strategy that fulfills the aesthetic objectives for filming and respects the physical limits of a drone. At the system level, we integrate cameras and GPUs into the limited space of a drone and demonstrate the feasibility of running the entire cinematography system onboard in real-time. Experimental results in both simulation and real-world scenarios demonstrate that our cinematography system 'ACT' can capture more expressive video footage of human action than that of a state-of-the-art drone camera system. © 2018 IEEE.

关键词： Drones

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Multiscale fluctuation-based dispersion entropy and its applications to neurological diseases

arXiv

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arXiv 2019年

作者： Azami, Hamed Arnold, Steven E. Sanei, Saeid Chang, Zhuoqing Sapiro, Guillermo Escudero, Javier Gupta, Anoopum S. Department of Neurology Massachusetts General Hospital Harvard University CharlestownMA02129 United States Department of Neurology Massachusetts General Hospital Harvard Medical School CharlestownMA02129 United States School of Science and Technology Nottingham Trent University Nottingham United Kingdom Department of Electrical and Computer Engineering Duke University DurhamNC27707 United States Department of Electrical and Computer Engineering Computer Sciences Biomedical Engineering and Math Duke University DurhamNC27707 United States Institute for Digital Communications School of Engineering University of Edinburgh Edinburgh United Kingdom Department of Neurology Massachusetts General Hospital Harvard Medical School BostonMA02114 United States

Fluctuation-based dispersion entropy (FDispEn) is a new approach to estimate the dynamical variability of the fluctuations of signals. It is based on Shannon entropy and fluctuation-based dispersion patterns. To quantify the physiological dynamics over multiple time scales, multiscale FDispEn (MFDE) is developed in this article. MFDE is robust to the presence of baseline wanders, or trends, in the data. We evaluate MFDE, compared with popular multiscale sample entropy (MSE), and the recently introduced multiscale dispersion entropy (MDE), on selected synthetic data and five neurological diseases' datasets: 1) focal and non-focal electroencephalograms (EEGs);2) walking stride interval signals for young, elderly, and Parkinson's subjects;3) stride interval fluctuations for Huntington's disease and amyotrophic lateral sclerosis;4) EEGs for controls and Alzheimer's disease patients;and 5) eye movement data for Parkinson's disease and ataxia. MFDE dealt with the problem of undefined MSE values and, compared with MDE, led to more stable entropy values over the scale factors for pink noise. Overall, MFDE was the fastest and most consistent method for the discrimination of different states of neurological data, especially where the mean value of a time series considerably changes along the signal (e.g., eye movement data). This study shows that MFDE is a relevant new metric to gain further insights into the dynamics of neurological diseases recordings. Copyright © 2019, The Authors. All rights reserved.

关键词： Electroencephalography

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Constrained space information flow 11th

Constrained space information flow

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11th EAI International Conference on communications and Networking in China, ChinaCom 2016

作者： Uwitonze, Alfred Huang, Jiaqing Ye, Yuanqing Cheng, Wenqing School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan430074 China Department of Electrical and Computer Engineering Carnegie Mellon University 5000 Forbes Ave PittsburghPA15213 United States

ISBN: (纸本)9783319666273

Space Information Flow (SIF), also known as Space Network Coding, is a new research paradigm which studies network coding in Euclidean space, and it is different with Network Information Flow proposed by Ahlswede et al. This paper focuses on the problem of Constrained Space Information Flow (CSIF), which aims to find a min-cost multicast network in 2-D Euclidean space under the constraint on the number of relay nodes to be used. We propose a new polynomial-time heuristic algorithm that combines Delaunay triangulation and linear programming techniques to solve the problem. Delaunay triangulation is used to generate several candidate relay nodes, after which linear programming is applied to choose the optimal relay nodes and to compute their connection links with the terminal nodes. The simulation results shows the effectiveness of the proposed algorithm. © 2018, ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Network coding

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Cache-aided non-orthogonal multiple access for 5G-enabled vehicular networks

arXiv

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arXiv 2019年

作者： Gurugopinath, Sanjeev Sofotasios, Paschalis C. Al-Hammadi, Yousof Muhaidat, Sami Department of Electronics and Communication Engineering PES University Bengaluru560085 India Center for Cyber-Physical Systems Department of Electrical and Computer Engineering Khalifa University of Science and Technology PO Box 127788 Abu Dhabi United Arab Emirates Department of Electronics and Communications Engineering Tampere University of Technology Tampere33101 Finland Department of Electrical and Computer Engineering Khalifa University of Science and Technology PO Box 127788 Abu Dhabi United Arab Emirates Center for Cyber-Physical Systems Department of Electrical and Computer Engineering Khalifa University of Science and Technology PO Box 127788 Abu Dhabi United Arab Emirates Institute for Communication Systems University of Surrey GuildfordGU2 7XH United Kingdom

The increasing demand for rich multimedia services and the emergence of the Internet-of-Things (IoT) pose challenging requirements for the next generation vehicular networks. Such challenges are largely related to high spectral efficiency and low latency requirements in the context of massive content delivery and increased connectivity. In this respect, caching and non-orthogonal multiple access (NOMA) paradigms have been recently proposed as potential solutions to effectively address some of these key challenges. In the present contribution, we introduce cache-aided NOMA as an enabling technology for vehicular networks. In this context, we first consider the full file caching case, where each vehicle caches and requests entire files using the NOMA principle. Without loss of generality, we consider a two-user vehicular network communication scenario under double Nakagami−m fading conditions and propose an optimum power allocation policy. To this end, an optimization problem that maximizes the overall probability of successful decoding of files at each vehicle is formulated and solved. Furthermore, we consider the case of split file caching, where each file is divided into two parts. A joint power allocation optimization problem is formulated, where power allocation across vehicles and cached split files is investigated. The offered analytic results are corroborated by extensive results from computer simulations and interesting insights are developed. Indicatively, it is shown that the proposed caching-aided NOMA outperforms the conventional NOMA technique. Copyright © 2019, The Authors. All rights reserved.

关键词： 5G mobile communication systems

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