Institution
Nanjing University of Aeronautics and Astronautics
Education•Nanjing, China•
About: Nanjing University of Aeronautics and Astronautics is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Computer science & Microstructure. The organization has 33704 authors who have published 37321 publications receiving 438855 citations. The organization is also known as: Nanjing College of Aviation Industry & Nanjing Aeronautical Institute.
Papers published on a yearly basis
Papers
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TL;DR: This paper sheds light on three UAV-enabled mobile edge computing (MEC) architectures, and presents a comprehensive survey for the state-of-the-art research in this domain.
Abstract: Unmanned aerial vehicle (UAV)-enabled communication networks are promising in the fifth and beyond wireless communication systems. In this paper, we shed light on three UAV-enabled mobile edge computing (MEC) architectures. Those architectures have been receiving ever increasing research attention for improving computation performance and decreasing execution latency by integrating UAV into MEC networks. We present a comprehensive survey for the state-of-the-art research in this domain. Important implementation issues are clarified. Moreover, in order to provide an enlightening guidance for future research directions, key challenges and open issues are discussed.
130 citations
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TL;DR: In this paper, the authors used the linear approximation of the Almost Ideal Demand System model and simulation analysis to estimate the direct rebound effect for passenger transport in urban China and found that a majority of the expected reduction in transport energy consumption from efficiency improvement could be offset due to the existence of rebound effect.
129 citations
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TL;DR: Under principal component analysis (PCA) framework, a new data-driven FDD method is proposed, which is named probability-relevant PCA (PRPCA), for electrical drives in high-speed trains and can greatly improve the fault detectability and achieve accurate fault diagnosis via support vector machine.
Abstract: Incipient faults in electrical drives can corrupt overall performance of high-speed trains; however, they are difficult to discover because of their slight fault symptoms. By sufficiently exploiting the distribution information of incipient faults, this paper presents the reason why incipient faults cannot be detected by the existing fault detection and diagnosis (FDD) methods. Under principal component analysis (PCA) framework, we propose a new data-driven FDD method, which is named probability-relevant PCA (PRPCA), for electrical drives in high-speed trains. The salient strengths of the PRPCA-based FDD method are: 1) it can greatly improve the fault detectability; it is suitable for non-Gaussian electrical drives; 2) based on the improved fault detectability, it can achieve accurate fault diagnosis via support vector machine; and 3) it can be easily applied to electrical drives even if neither physical models or parameters nor expert knowledge of drive systems is given; and it is of highly computational efficiency that can meet requirements on the real-time FDD. A set of experiments on a dSPACE platform-based traction system of the CRH2A-type high-speed train are carried out to demonstrate the effectiveness of the proposed method.
129 citations
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TL;DR: Investigation of the average throughput of a wireless-powered communications system, where an energy constrained source, powered by a dedicated power beacon (PB), communicates with a destination, shows that increasing the number of transmit antennas at the PB is an effective tool to improve theaverage throughput.
Abstract: This paper investigates the average throughput of a wireless-powered communications system, where an energy constrained source, powered by a dedicated power beacon (PB), communicates with a destination. It is assumed that the PB is capable of performing channel estimation, digital beamforming, and spectrum sensing as a communication device. Considering a time-splitting approach, the source first harvests energy from the PB equipped with multiple antennas, and then transmits information to the destination. Assuming Nakagami- $m$ fading channels, analytical expressions for the average throughput are derived for two different transmission modes, namely, delay tolerant and delay intolerant . In addition, closed-form solutions for the optimal time split, which maximize the average throughput are obtained in some special cases, i.e., high-transmit power regime and large number of antennas. Finally, the impact of cochannel interference is studied. Numerical and simulation results have shown that increasing the number of transmit antennas at the PB is an effective tool to improve the average throughput and the interference can be potentially exploited to enhance the average throughput, since it can be utilized as an extra source of energy. Also, the impact of fading severity level of the energy transfer link on the average throughput is not significant, especially if the number of PB antennas is large. Finally, it is observed that the source position has a great impact on the average throughput.
129 citations
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TL;DR: In this paper, a recursive convolutional neural network was designed to cope with the challenge of infinite state of spectrum waterfall, and an anti-jamming deep reinforcement learning algorithm was proposed to obtain the optimal antijamming strategies.
Abstract: This letter investigates the problem of anti-jamming communications in a dynamic and intelligent jamming environment through machine learning. Different from existing studies which need to know (estimate) the jamming patterns and parameters, we use the temporal and spectral information, i.e., the spectrum waterfall, directly. First, to cope with the challenge of infinite state of spectrum waterfall, a recursive convolutional neural network is designed. Then, an anti-jamming deep reinforcement learning algorithm is proposed to obtain the optimal anti-jamming strategies. Finally, simulation results validate the proposed approach. The proposed algorithm does not need to model the jamming patterns, and naturally has the ability to explore the unknown environment, which implies that it can be widely used for combating dynamic and intelligent jamming.
129 citations
Authors
Showing all 34050 results
Name | H-index | Papers | Citations |
---|---|---|---|
Chao Zhang | 127 | 3119 | 84711 |
Guoxiu Wang | 117 | 654 | 46145 |
Zhongfan Liu | 115 | 743 | 49364 |
Xiaoming Li | 113 | 1932 | 72445 |
Wei Liu | 102 | 2927 | 65228 |
Shihua Li | 101 | 616 | 35335 |
Junjie Zhu | 100 | 719 | 46374 |
Lei Wang | 95 | 1486 | 44636 |
Gui-Rong Liu | 95 | 595 | 36641 |
Yongyao Xia | 95 | 389 | 30430 |
Haibo Zeng | 94 | 604 | 39226 |
Wei Zhou | 93 | 1640 | 39772 |
Xiaogang Zhang | 91 | 448 | 30136 |
Wei Chen | 90 | 938 | 35799 |
Xihong Lu | 88 | 337 | 29367 |