Space-Time Network Coding With Transmit Antenna Selection and Maximal-Ratio Combining

Yang, Kai; Yang, Nan; Xing, Chengwen; Wu, Jinsong; Zhang, Zhongshan

doi:10.1109/twc.2014.2381217

Cited by 35 publications

(18 citation statements)

References 26 publications

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“…In recent years, bionics design ideas have been applied to vehicles more and more extensively. By simulating shapes of animals and plants, designers combined vehicles with animals and plants in the nature perfectively [21][22][23][24]. Clever utilization of bionics has achieved obvious effects in engineering field, science and technologies, fully indicating the finite application prospect and development space of bionics [25][26][27][28][29].…”

Section: Introductionmentioning

confidence: 99%

Numerical investigation and experimental test on aerodynamic noises of the bionic rear view mirror in vehicles

Wan¹,

Ma²

2017

J. vibroeng.

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At present, there are some researches focusing on optimization of aerodynamic noises on rear view mirrors, but researches on bionic noise reduction of rear view mirrors are rarely reported. Therefore, with an original rear view mirror as the basic model, the paper applied a head convex hull of a dung beetle to the original rear view mirror cover to obtain a bionic rear view mirror, then conducted numerical computation for aerodynamic noises of the bionic rear view mirror and compared the computational results with the original model. Finally, in order to verify correctness of computational results of aerodynamic noises of the rear view mirror, wind tunnel test was conducted on the rear view mirror. Experimental and numerical simulation results were highly consistent in the whole frequency band, so the wind tunnel test could be replaced by numerical simulation. Only one obvious vortex was behind the bionic rear view mirror, but two obvious vortexes with the opposite rotation directions were behind the original rear view mirror. The bionic rear view mirror did not present vortexes near the lateral window, so impacts of vortexes on noises in the vehicle could be eliminated effectively. Pressure difference in front of and behind the bionic view mirror was smaller than the pressure difference in front of and behind the original rear view mirror. Pressure resistance caused by the convex structure outside the rear view mirror was reduced, so noise reduction could be promoted. The convex structure mainly affected the aerodynamic noise in mid-high frequency regions. Compared with the original rear view mirror, noise reduction effects of the bionic rear view mirror were obvious, where the noise reduction amplitude reached 10dB. Noise source size and intensity of the bionic rear view mirror were reduced obviously.

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Section: Introductionmentioning

confidence: 99%

Numerical investigation and experimental test on aerodynamic noises of the bionic rear view mirror in vehicles

Wan¹,

Ma²

2017

J. vibroeng.

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“…In view of the large bridge spans, monitoring with traditionally wired sensor networks must be confronted with long wiring and high monitoring difficulty. Thanks to the rapid development of big data technology [22,23], microcomputer system, sensor technology, wireless communication technology [24,25], and low-power consumption embedding technology, it is possible to acquire and process data with a wireless sensor network [26,27]. A wireless sensor network is composed of micro and flexible sensor nodes distributed in a monitoring area and transmits information of collecting objects to a processing system through wireless communication, so the collector can analyze and use the information.…”

Section: Random Traffic Flow In a Big Data Environmentmentioning

confidence: 99%

The Performance Study on the Long‐Span Bridge Involving the Wireless Sensor Network Technology in a Big Data Environment

Zhang

Sun

et al. 2018

Complexity

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The random traffic flow model which considers parameters of all the vehicles passing through the bridge, including arrival time, vehicle speed, vehicle type, vehicle weight, and horizontal position as well as the bridge deck roughness, is input into the vehiclebridge coupling vibration program. In this way, vehicle-bridge coupling vibration responses with considering the random traffic flow can be numerically simulated. Experimental test is used to validate the numerical simulation, and they had the consistent changing trends. This result proves the reliability of the vehicle-bridge coupling model in this paper. However, the computational process of this method is complicated and proposes high requirements for computer performance and resources. Therefore, this paper considers using a more advanced intelligent method to predict vibration responses of the long-span bridge. The PSO-BP (particle swarm optimization-back propagation) neural network model is proposed to predict vibration responses of the long-span bridge. Predicted values and real values at each point basically have the consistent changing trends, and the maximum error is less than 10%. Hence, it is feasible to predict vibration responses of the long-span bridge using the PSO-BP neural network model. In order to verify advantages of the predicting model, it is compared with the BP neural network model and GA-BP neural network model. The PSO-BP neural network model converges to the set critical error after it is iterated to the 226th generation, while the other two neural network models are not converged. In addition, the relative error of predicted values using PSO-BP neural network is only 2.71%, which is obviously less than the predicted results of other two neural network models. We can find that the PSO-BP neural network model proposed by the paper in predicting vibration responses is highly efficient and accurate.

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“…The stress of DSIMBS was obtained by resistance strain gauges, and 3-axis acceleration sensors were applied to measure the displacements of VSDSIMBS. Related experimental instruments were connected, and test signals were collected and processed [28][29][30][31]. The flow chart of field tests is shown in Fig.…”

Section: Full-scale Experimental Tests On Vsdsimbs and Comparisons Bementioning

confidence: 99%

A novel high-strength large vibrating screen with duplex statically indeterminate mesh beam structure

Wang¹,

Liu²,

Wu³

et al. 2017

J. vibroeng.

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Screening is an indispensable unit process for separation of materials. Large vibrating screen is extensively used in coal processing because of its large production capacity. In this study, a novel large vibrating screen with duplex statically indeterminate mesh beam structure (VSDSIMBS) was presented. The dynamic model of VSDSIMBS was proposed, and characteristic parameters were obtained by theoretical calculations. In order to obtain more reliable and believable research results, model of a traditional vibrating screen (TVS) with the same mass was also established for comparisons with VSDSIMBS. The finite element (FE) method was applied to study the performance of VSDSIMBS and FE analysis of VSDSIMBS and TVS was completed by using characteristic parameters. Modal analysis results indicated that VSDSIMBS could avoid the resonance and run more smoothly than TVS. Furthermore, harmonic response analysis results showed that VSDSIMBS could improve the entire stress distribution, reduce high stress areas, and increase the strength of vibrating screen. With DSIMBS, the maximum stress of vibrating screen decreased from 130.53 to 64.54 MPa. The full-scale experimental tests were performed to validate the credibility and accuracy of FE analysis results. The stress and displacements of VSDSIMBS were measured under working conditions. The test results obtained are in good agreement with simulation results, and accord with conclusions made from FE analysis.

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Space-Time Network Coding With Transmit Antenna Selection and Maximal-Ratio Combining

Cited by 35 publications

References 26 publications

Numerical investigation and experimental test on aerodynamic noises of the bionic rear view mirror in vehicles

Numerical investigation and experimental test on aerodynamic noises of the bionic rear view mirror in vehicles

The Performance Study on the Long‐Span Bridge Involving the Wireless Sensor Network Technology in a Big Data Environment

A novel high-strength large vibrating screen with duplex statically indeterminate mesh beam structure

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