The understanding of urban traffic pattern can benefit the urban operation a lot, including the traffic forecasting, traffic jam resolution, emergency response and future infrastructure planning. In modern cities, tho...
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With rapid development of unmanned aerial vehicles(UAVs), more and more UAVs access satellite networks for data transmission. To improve the spectral efficiency, non-orthogonal multiple access(NOMA) is adopted to inte...
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With rapid development of unmanned aerial vehicles(UAVs), more and more UAVs access satellite networks for data transmission. To improve the spectral efficiency, non-orthogonal multiple access(NOMA) is adopted to integrate UAVs into the satellite network, where multiple satellites cooperatively serve the UAVs and mobile terminal using the Ku-band and above. Taking into account the rain fading and the fading correlation, the outage performance is first analytically obtained for fixed power allocation and then efficiently calculated by the proposed power allocation algorithm to guarantee the user fairness. Simulation results verify the outage performance analysis and show the performance improvement of the proposed power allocation scheme.
Objective In phase-sensitive optical time-domain reflectometers (Ф‑OTDRs), coherent and polarization fading caused by inherent destructive interference and polarization mismatch, affect phase restoration performance....
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Objective In phase-sensitive optical time-domain reflectometers (Ф‑OTDRs), coherent and polarization fading caused by inherent destructive interference and polarization mismatch, affect phase restoration performance. Traditional signal fading suppression methods typically require additional hardware structures, which increases system complexity and cost. Moreover, vibration signals are non- stationary with complex frequency components, which further increases the fading suppression challenge. Therefore, it is of paramount significance to investigate a novel signal fading suppression method to achieve accurate phase reconstruction on the simplest structure in scientific research and engineering applications. Methods In this study, the random signal fading process in Ф- OTDR is analyzed, and it is confirmed that the fading point phase is a random noise value that follows uniform distribution. Using the empirical mode decomposition (EMD) algorithm, phase noise including phase accumulation noise and laser frequency drift is filtered out and phase information modulated by external vibration is extracted. The extracted phase data are subsequently organized into a two-dimensional space-time map, which are input into a generative adversarial network (GAN) to realize the repair of the fading data. The GAN training dataset, which is generated using software simulation, contains a total of 12000 images including the phase spectra of sinusoidal, square, and triangular wave vibration signals, Gaussian pulse vibration signal, and random vibration signal. Results and Discussions Experiments are designed as follows. The total length of the sensing fiber is 10.12 km, which is connected by three sections of single-mode fibers of 4.17, 1.92, and 3.95 km in length, respectively. A piezoelectric ceramic (PZT) is connected between each section of fiber and driven by the signal generator to produce the required vibration signal. Phase demodulation is performed at two vibration positions (
Detecting target echo in the existence of self-screen jamming is a challenging work for radar system, especially when digital radio frequency memory(DRFM) technique is employed that mixes the jamming and target echo b...
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Detecting target echo in the existence of self-screen jamming is a challenging work for radar system, especially when digital radio frequency memory(DRFM) technique is employed that mixes the jamming and target echo both in spatial and time-frequency domain. The conventional way to solve this problem would suffer from performance degradation when physical target(PT) and false target(FT) are superposed in time. In this paper, we propose a new spatial filter according to the different correlation characteristic between PT and FT. The filter takes the ratio of expected signal power to expected jamming and noise power as the objective function under the constant filter modulus constraint. The optimal filter coefficients are derived with a generalized rayleigh quotient approach. Moreover, we analytically compute the target detection probability and demonstrate the applicability of the proposed method to the correlation coefficient. Monte Carlo simulations are provided to corroborate the proposed studies. Furthermore, the proposed method has simple architecture and low computation complexity, making it easily applied in modern radar system.
Three-dimensional distributed circuit modeling based on SPICE software can simulate the electrical performance and the uniformity of electroluminescence (EL) intensity. To solve the problem that traditional methods re...
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This study investigates the mechanical properties and thicknesses distribution of yttria-stabilized zirconia (YSZ) films deposited via plasma-assisted aerosol deposition (PAD), with and without a convergent–divergent...
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Bitcoin, which was initially introduced by Nakamoto, is the most disruptive and impactive cryptocurrency. The core Bitcoin technology is the so-called blockchain protocol. In recent years, several studies have focused...
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Bitcoin, which was initially introduced by Nakamoto, is the most disruptive and impactive cryptocurrency. The core Bitcoin technology is the so-called blockchain protocol. In recent years, several studies have focused on rigorous analyses of the security of Nakamoto’s blockchain protocol in an asynchronous network where network delay must be considered. Wei, Yuan, and Zheng investigated the effect of a long delay attack against Nakamoto’s blockchain protocol. However, their proof only holds in the honest miner setting. In this study, we improve Wei, Yuan and Zheng’s result using a stronger model where the adversary can perform long delay attacks and corrupt a certain fraction of the miners. We propose a method to analyze the converge event and demonstrate that the properties of chain growth, common prefix, and chain quality still hold with reasonable parameters in our stronger model.
The purpose of unsupervised domain adaptation is to use the knowledge of the source domain whose data distribution is different from that of the target domain for promoting the learning task in the target *** key bott...
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The purpose of unsupervised domain adaptation is to use the knowledge of the source domain whose data distribution is different from that of the target domain for promoting the learning task in the target *** key bottleneck in unsupervised domain adaptation is how to obtain higher-level and more abstract feature representations between source and target domains which can bridge the chasm of domain ***,deep learning methods based on autoencoder have achieved sound performance in representation learning,and many dual or serial autoencoderbased methods take different characteristics of data into consideration for improving the effectiveness of unsupervised domain ***,most existing methods of autoencoders just serially connect the features generated by different autoencoders,which pose challenges for the discriminative representation learning and fail to find the real cross-domain *** address this problem,we propose a novel representation learning method based on an integrated autoencoders for unsupervised domain adaptation,called *** capture the inter-and inner-domain features of the raw data,two different autoencoders,which are the marginalized autoencoder with maximum mean discrepancy(mAE)and convolutional autoencoder(CAE)respectively,are proposed to learn different feature *** higher-level features are obtained by these two different autoencoders,a sparse autoencoder is introduced to compact these inter-and inner-domain *** addition,a whitening layer is embedded for features processed before the mAE to reduce redundant features inside a local *** results demonstrate the effectiveness of our proposed method compared with several state-of-the-art baseline methods.
Wireless sensor and actuator networks （WSANs） have a wide range of applications. To perform effective sensing and acting tasks, multiple coordination mechanisms among the nodes are required. As attempt in this direc...
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Wireless sensor and actuator networks （WSANs） have a wide range of applications. To perform effective sensing and acting tasks, multiple coordination mechanisms among the nodes are required. As attempt in this direction, this paper describes collaborative estimation and control algorithms design for WSANs. First, a sensor-actuator coordination model is proposed based on distributed Kalman filter in federated configuration. This method provides the capability of fault tolerance and multi-source information fusion. On this basis, an actuator-actuator coordination model based on even-driven task allocation is introduced. Actuators utilize fused sensory information to adjust their action that incur the minimum energy cost to the system subject to the constraints that user＇s preferences regarding the states of the system are approximately satisfied. Finally, according to system requirements, a distributed algorithm is proposed to solve the task allocation problem. Simulations demonstrate the effectiveness of our proposed methods.
In this paper,we investigate the matched filter based spectrum sensing in a more reasonable cognitive radio(CR) scenario when the primary user(PU) has more than one transmit power levels,as regulated in most standards...
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In this paper,we investigate the matched filter based spectrum sensing in a more reasonable cognitive radio(CR) scenario when the primary user(PU) has more than one transmit power levels,as regulated in most standards,i.e.,IEEE 802.11 Series,GSM,LTE,LTE-A,*** new multiple primary transmit power(MPTP) scenario is specialized by two different targets:detecting the presence of PU and identifying the power *** to the traditional binary sensing where only the presence of PU is checked,SU may attain more information about the primary network(making CR more "intelligent") and design the subsequent optimization *** key technology is the multiple hypothesis testing as opposed to the traditional binary hypothesis *** discuss two situations under whether the channel phase is known or not,and we derive the closed form solutions for decision regions and several performance metrics,from which some interesting phenomenons are observed and the related discussions are *** examples are provided to corroborate the proposed studies.
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