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Swept-sine integration method for complex amplitude extraction of swept-sine signal

JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY 2020年第12期34卷 4981-4988页

作者： Zheng, Wei Cui, Xuli Chen, Huaihai Zheng, Ronghui Nanjing Univ Aeronaut & Astronaut State Key Lab Mech & Control Mech Struct Nanjing Jiangsu Peoples R China BSH Elect Appliances Co Ltd Jiangsu Nanjing Jiangsu Peoples R China

Swept-sine vibration test plays a significant role in product validations. As its basic step, the accuracy and efficiency of complex amplitude (which includes the amplitude and phase information of swept-sine signal) extraction have an important impact on the performance of swept-sine vibration test. In order to improve the efficiency while ensuring its accuracy, a swept-sine integration method is proposed. The proposed swept-sine integration method, which is inspired by tracking filter method and tracking integration method, utilizes a weighted integral process to extract the complex amplitude. A numeral example is presented to compare the performance of the proposed method with several other methods for complex amplitude extraction which are also reviewed in this paper. By comparing the results of the numerical example, some light is shed on the strength of the method proposed. Afterwards, the swept-sine integration method is applied in a real test, further validating the appliance value of this method.

关键词： Complex amplitude extraction Hilbert transform multi-input multi-output Swept-sine vibration Tracking filter

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Optimization of Energy Consumption in the MEC-Assisted multi-User FD-SWIPT System

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IEEE ACCESS 2020年 8卷 21345-21354页

作者： Fu, Jiafei Hua, Jingyu Wen, Jiangang Chen, Hao Lu, Weidang Li, Jiamin Zhejiang Gongshang Univ Sch Informat & Elect Engn Hangzhou 310018 Peoples R China Zhejiang Univ Technol Coll Informat Engn Hangzhou 310023 Peoples R China Southeast Univ Natl Commun Res Lab Nanjing 210096 Peoples R China

That alleviating the heavy computing task, improving spectral efficiency and prolonging battery lifetime have been the key design challenges in Internet of Things (IoT) and intelligent connected vehicles (ICV). This paper studies the optimization of communication, computation and energy resource to minimize the energy consumption in the mobile terminal, where some superior technologies are included, such as Full-Duplex (FD), Simultaneous Wireless Information and Power Transfer (SWIPT), Mobile-Edge Computing (MEC) and multi-input multi-output (MIMO). In this model, the MEC-assisted Base station (BS) works in FD mode, then it can transmit and receive signals in the same frequency and time. Moreover, the mobile devices offload some computation tasks to the BS and complete local computations at the same time. Besides, the mobile device harvests the energy from the BS to support its energy consumption. And, our target is to minimize the energy consumption of mobile devices. Since the problem is non-convex, we propose an iterative solving algorithm including a multi-step optimization. First, we obtain the closed-form solution of the CPU frequency. And then, we transform the remain problem into a convex one to solve it by the interior point algorithm. Finally, we obtain the approximate solution by multiple iterations. Simulation results show that the proposed algorithm is superior to the compared schemes.

关键词： Mobile-edge computing simultaneous wireless information and power transfer multi-input multi-output full-duplex multi-step iteration vehicular communications

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Performance enhancement based on machine learning scheme for space multiplexing 2x2 MIMO VLC system employing joint IQ independent component analysis

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OPTICS COMMUNICATIONS 2020年 458卷 124733-000页

作者： Wang, Zhe Han, Siqi Chi, Nan Fudan Univ Dept Commun Sci & Engn Key Lab Electromagnet Wave Informat Sci Shanghai Peoples R China

With the increasing demand for Visible Light Communication (VLC) bandwidth, the space-multiplexing technique has been widely utilized to enhance the capability of the VLC system. In this paper, we proposed a novel MIMO detection scheme to decompose the superposed signals in a 2x2 multiple-input-multiple-output (MIMO) VLC system. With the help of the proposed machine learning scheme, two received optical signals can be separated into two independent parallel signals. By simulation, the unmixing matrix can be quickly converged by iterations. Extensive experiments demonstrate an average BER of 6.191x10(-4) is achieved at a bitrate of 750 Mbps over a 1.3-m line of sight (LOS) in the 2x2 MIMO scenario. Finally, to evaluate the performance of the algorithm, the Q factor yielded a gain of about 2.5 dB compared with the traditional Alamouti Space-Time Block Coding (STBC) scheme.

关键词： Joint IQ independent component analysis multi-input multi-output Blind source separation Visible light communication

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Network traffic forecasting model based on long-term intuitionistic fuzzy time series

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INFORMATION SCIENCES 2020年 506卷 131-147页

作者： Fan, Xiaoshi Wang, Yanan Zhang, Mengyu Natl Def Univ PLA Jonit Logist Coll Beijing 100039 Peoples R China Air Force Engn Univ Air & Missile Def Coll Xian 710051 Shaanxi Peoples R China Univ Int Business & Econ Beijing 100029 Peoples R China

In this paper, a network traffic forecasting model based on long-term intuitionistic fuzzy time series (LT-IFTS) is proposed. It describes the fuzziness and uncertainty of network flow and improves the traffic forecasting performance. The multi-input multi-output (MIMO) intuitionistic fuzzy time series forecasting model, namely, (p-q) IFTS is defined. An intuitionistic fuzzy time series vectors clustering algorithm based on vector variation pattern is given. The cluster centroid in the proposed model is quite different from the traditional method. As a kind of typical time series data, the network flow forecasting system is constructed particularly. Characteristic intuitionistic fuzzy is a practical method to manage the fuzziness and uncertainty of network traffic data. The network traffic data is intuitionistic fuzzified and vector quantized. The time series vectors are gathered based on the improved intuitionistic fuzzy c-means clustering and matched with centroids by coordinate translation. Compared with other traditional forecasting models, the improved FCM clustering algorithm increases discrimination of time series segments. In addition, the long-term scheme improves forecasting efficiency and reduces computational complexity than other single-output models. In experiments, the proposed model and relevant models are implemented on four different scales network traffic dataset from MAWI. The experiment result indicates that the proposed model is with better generalization performance. (C) 2019 Elsevier Inc. All rights reserved.

关键词： Intuitionistic fuzzy time series Vector quantization Network traffic Long-term forecasting multi-input multi-output

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Novel hybrid approaches based on evolutionary strategy for streamflow forecasting in the Chellif River, Algeria

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ACTA GEOPHYSICA 2020年第1期68卷 167-180页

作者： Zakhrouf, Mousaab Bouchelkia, Hamid Stamboul, Madani Kim, Sungwon Univ Tlemcen Fac Technol Dept Hydraul URMER Lab Tilimsen Algeria Amar Telidji Univ Fac Architecture & Civil Engn Dept Civil Engn Res Lab Water Resources Soil & Environm Laghouat Algeria Dongyang Univ Dept Railroad Construct & Safety Engn Yeongju 36040 South Korea

In this study, the feedforward neural networks (FFNNs) were proposed to forecast the multi-day-ahead streamflow. The parameters of FFNNs model were optimized utilizing genetic algorithm (GA). Moreover, discrete wavelet transform was utilized to enhance the accuracy of FFNNs model's forecasting. Therefore, the wavelet-based feedforward neural networks (WFFNNs-GA) model was developed for the multi-day-ahead streamflow forecasting based on three evolutionary strategies [i.e., multi-input multi-output (MIMO), multi-input single-output (MISO), and multi-input several multi-output (MISMO)]. In addition, the developed models were evaluated utilizing five different statistical indices including root mean squared error, signal-to-noise ratio, correlation coefficient, Nash-Sutcliffe efficiency, and peak flow criteria. Results provided that the statistical values of WFFNNs-GA model based on MISMO evolutionary strategy were superior to those of WFFNNs-GA model based on MISO and MIMO evolutionary strategies for the multi-day-ahead streamflow forecasting. Results indicated that the performance of WFFNNs-GA model based on MISMO evolutionary strategy provided the best accuracy. Results also explained that the hybrid model suggested better performance compared with stand-alone model based on the corresponding evolutionary strategies. Therefore, the hybrid model can be an efficient and robust implement to forecast the multi-day-ahead streamflow in the Chellif River, Algeria.

关键词： Daily streamflow forecasting Wavelet transform Feed forward neural networks multi-input multi-output multi-input single-output multi-input several multi-output Chellif River

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Performance of MIMO IEEE802.11n WLAN in Presence of QPSK Jammer with Inphase/Quadrature Origin Offsets

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WIRELESS PERSONAL COMMUNICATIONS 2020年第1期113卷 555-574页

作者： Shaheen, Ehab M. Mil Tech Coll Elect Warfare Dept Cairo Egypt

In this paper a novel jamming technique is presented. The idea of the proposed jamming technique is based on adding inphase and quadrature impairments to the jamming signal. The jammer is simply a quadrature phase shift keying signal. The bit error rate probability (BER) of the proposed jamming signal is derived analytically and validated with the aid of the software defined radio SystemVue design software. The standard multi input multi output (MIMO) wireless local area network (WLAN) IEEE802.11n communication system is chosen as the victim system. Its BER performance is simulated in the presence of the proposed jamming signal in multipath fading channel. Finally, the efficiency of the proposed jamming signal on the MIMO WLAN IEEE802.11n communication system is practically measured in the laboratory where a practical experiment is held and the efficiency of the proposed jamming signal is compared with the traditional single tone jamming signal. It will be shown practically that the proposed jamming technique outperforms the traditional single tone jamming signal by nearly 15 dBm on the impact of efficiently jam the MIMO WLAN IEEE802.11n communication system.

关键词： multi-input multi-output IEEE802 11n Jamming Bit error rate probability Inphase and quadrature offsets

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A Sequential Subspace Method for Millimeter Wave MIMO Channel Estimation

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2020年第5期69卷 5355-5368页

作者： Zhang, Wei Kim, Taejoon Leung, Shu-Hung City Univ Hong Kong Dept Elect Engn Hong Kong Peoples R China Univ Kansas Dept Elect Engn & Comp Sci Lawrence KS 66045 USA City Univ Hong Kong Dept Elect Engn State Key Lab Terahertz & Millimeter Waves Hong Kong Peoples R China

Data transmission over the millimeter wave (mmWave) in fifth-generation wireless networks aims to support very high speed wireless communications. A substantial increase in spectrum efficiency for mmWave transmission can be achieved by using advanced hybrid analog-digital precoding, for which accurate channel state information (CSI) is the key. Rather than estimating the entire channel matrix, it is now well-understood that directly estimating subspace information, which contains fewer parameters, does have enough information to design transceivers. However, the large channel use overhead and associated computational complexity in the existing channel subspace estimation techniques are major obstacles to deploy the subspace approach for channel estimation. In this paper, we propose a sequential two-stage subspace estimation method that can resolve the overhead issues and provide accurate subspace information. Utilizing a sequential method enables us to avoid manipulating the entire high-dimensional training signal, which greatly reduces the computational complexity. Specifically, in the first stage, the proposed method samples the columns of channel matrix to estimate its column subspace. Then, based on the obtained column subspace, it optimizes the training signals to estimate the row subspace. For a channel with N-r receive antennas and N-t transmit antennas, our analysis shows that the proposed technique only requires O(N-t) channel uses, while providing a guarantee of subspace estimation accuracy. By theoretical analysis, it is shown that the similarity between the estimated subspace and the true subspace is linearly related to the signal-to-noise ratio (SNR), i.e., O(SNR), at high SNR, while quadratically related to the SNR, i.e., O(SNR2), at low SNR. Simulation results show that the proposed sequential subspace method can provide improved subspace accuracy, normalized mean squared error, and spectrum efficiency over existing methods.

关键词： Channel estimation compressed sensing millimeter wave communication multi-input multi-output subspace estimation

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On the Performance of MIMO Full-Duplex Relaying System With SWIPT Under Outdated CSI

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2020年第12期69卷 15580-15593页

作者： Hoang, Tran Manh Tran, Xuan Nam Nguyen, Ba Cao Dung, Le The Telecommun Univ Nha Trang 650000 Khanh Hoa Provi Vietnam Le Quy Don Tech Univ Adv Wireless Commun Grp Ha Noi City 100000 Vietnam Le Quy Don Tech Univ Fac Radio Elect Ha Noi City 100000 Vietnam Ton Duc Thang Univ Inst Computat Sci Div Computat Phys Ho Chi Minh City 700000 Vietnam Ton Duc Thang Univ Fac Elect & Elect Engn Ho Chi Minh City 700000 Vietnam

In this paper, we propose a full-duplex (FD) relaying system with multi-input multi-output (MIMO) with simultaneous wireless information and power transfer (SWIPT), where the communication from source to destination is assisted by a full-duplex decode-and-forward (DF) relay. The time switching (TS) protocol is used at the relay to harvest the energy of radio-frequency (RF) signals transmitted from the source. To improve both system performance and the amount of harvested energy, multiple antennas are used at source and destination. Transmit antenna selection (TAS) is employed at the source with an assumption that the feedback of channel state information (CSI) is outdated. Meanwhile, both selection combining (SC) and maximal ratio combining (MRC) techniques are applied at the destination. The closed-form expressions of the outage probability (OP), optimal throughput, and symbol error probability (SEP) are derived subject to the outdated CSI over Rayleigh fading channels. We also make a comparison between the performance of the proposed MIMO-FD relaying system with SWIPT and that of MIMO half-duplex (HD) relaying systems with and without SWIPT. The validity of derived mathematical expressions is verified by Monte-Carlo simulations. Numerical results show that the TAS/MRC scheme gives better system performance than the TAS/SC scheme. Moreover, higher energy harvesting time is needed to maximize the throughput than to minimize the OP.

关键词： multi-input multi-output full-duplex wireless power transfer decode-and-forward outage probability symbol error probability throughput

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Line-of-Sight multi-input multi-output Capacity Improvement using Change of Carrier Frequency

Line-of-Sight Multi-Input Multi-Output Capacity Improvement ...

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2nd International Conference on Advances in Computing, Communications and Informatics (ICACCI)

作者： Gill, Satinder Singh Petersen, Brent R. Univ New Brunswick Dept Elect & Comp Engn Fredericton NB Canada

ISBN: (纸本)9781479924325;9781479926596

In this paper, a technique for realizing a low condition number channel matrix for line-of-sight (LOS) multi-input multi-output (MEMO) transmission scenario is presented. The main idea behind the proposed work is to make use of a change in carrier frequency of adjacent transmit antennas to increase the MIMO capacity gain without requiring any additional bandwidth. We derive the criteria for the maximum capacity in terms of difference between carrier frequency for adjacent transmit antennas. The performance of this technique is investigated with the help of simulation results.

关键词： multi-input multi-output Line-of-Sight Ricean Channel MIMO Capacity

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Interval Forecasting of Financial Time Series by Accelerated Particle Swarm-Optimized multi-output Machine Learning System

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IEEE ACCESS 2020年 8卷 14798-14808页

作者： Chou, Jui-Sheng Dinh-Nhat Truong Thuy-Linh Le Natl Taiwan Univ Sci & Technol Dept Civil & Construct Engn Taipei 10607 Taiwan Univ Technol & Educ Univ Danang Dept Ind Educ Danang 550000 Vietnam

By providing a range of values rather than a point estimate, accurate interval forecasting is critical to the success of investment decisions in exchange rate markets. This work proposes a sliding-window metaheuristic optimization for interval-valued time series forecasting using multi-output least squares support vector regression (MLSSVR). The hyperparameters in MLSSVR are finetuned using an accelerated particle swarm optimization algorithm to yield the best predictions and fastest convergence. The proposed system has a graphical user interface that is developed in a computing environment and functions as a stand-alone application. The system is validated using stock prices as well as exchange rates and outputs are compared with published results. Finally, the proposed interval time series prediction method is tested in two case studies;one involves the daily Australian dollar and Japanese yen rates (AUD/JPY) and the other involves US dollar and Canadian dollar rates (USD/CAD). The proposed model is promising for interval time series forecasting.

关键词： Sliding window multi-input multi-output time series interval forecasting financial services industry accelerated particle swarm optimization least squares support vector regression hybrid system

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