In this paper,we investigate the reconfigurable intelligent surface(RIS)-enabled multiple-input-single-output orthogonal frequency division multiplexing(MISO-OFDM)system under frequency-selective channels,and propose ...In this paper,we investigate the reconfigurable intelligent surface(RIS)-enabled multiple-input-single-output orthogonal frequency division multiplexing(MISO-OFDM)system under frequency-selective channels,and propose a low-complexity alternating optimization(AO)based joint beamforming and RIS phase shifts optimization algorithm to maximize the achievable rate.First,with fixed RIS phase shifts,we devise the optimal closedform transmit beamforming vectors corresponding to different subcarriers.Then,with given active beamforming vectors,near-optimal RIS reflection coefficients can be determined efficiently leveraging fractional programming(FP)combined with manifold optimization(MO)or majorization-minimization(MM)framework.Additionally,we also propose a heuristic RIS phase shifts design approach based on the sum of subcarrier gain maximization(SSGM)criterion requiring lower complexity.Numerical results indicate that the proposed MO/MM algorithm can achieve almost the same rate as the upper bound achieved by the semidefinite relaxation(SDR)algorithm,and the proposed SSGM based scheme is only slightly inferior to the upper bound while has much lower complexity.These results demonstrate the effectiveness of the proposed algorithms.展开更多
The prediction of liquefaction-induced lateral spreading/displacement(Dh)is a challenging task for civil/geotechnical engineers.In this study,a new approach is proposed to predict Dh using gene expression programming(...The prediction of liquefaction-induced lateral spreading/displacement(Dh)is a challenging task for civil/geotechnical engineers.In this study,a new approach is proposed to predict Dh using gene expression programming(GEP).Based on statistical reasoning,individual models were developed for two topographies:free-face and gently sloping ground.Along with a comparison with conventional approaches for predicting the Dh,four additional regression-based soft computing models,i.e.Gaussian process regression(GPR),relevance vector machine(RVM),sequential minimal optimization regression(SMOR),and M5-tree,were developed and compared with the GEP model.The results indicate that the GEP models predict Dh with less bias,as evidenced by the root mean square error(RMSE)and mean absolute error(MAE)for training(i.e.1.092 and 0.815;and 0.643 and 0.526)and for testing(i.e.0.89 and 0.705;and 0.773 and 0.573)in free-face and gently sloping ground topographies,respectively.The overall performance for the free-face topology was ranked as follows:GEP>RVM>M5-tree>GPR>SMOR,with a total score of 40,32,24,15,and 10,respectively.For the gently sloping condition,the performance was ranked as follows:GEP>RVM>GPR>M5-tree>SMOR with a total score of 40,32,21,19,and 8,respectively.Finally,the results of the sensitivity analysis showed that for both free-face and gently sloping ground,the liquefiable layer thickness(T_(15))was the major parameter with percentage deterioration(%D)value of 99.15 and 90.72,respectively.展开更多
Existing vehicle experiment systems tend to focus on the research of vehicle dynamics by conducting performance tests on every system or some parts of the vehicle so as to improve the entire performance of the vehicle...Existing vehicle experiment systems tend to focus on the research of vehicle dynamics by conducting performance tests on every system or some parts of the vehicle so as to improve the entire performance of the vehicle. Virtual technology is widely utilized in various vehicle test-beds. These test-beds are mainly used to simulate the driving training, conduct the research on drivers＇ behaviors, or give virtual demonstrations of the transportation environment. However, the study on the active safety of the running vehicle in the virtual environment is still insufficient. A virtual scene including roads and vehicles is developed by using the software Creator and Vega, and radars and cameras are also simulated in the scene. Based on dSPACE＇s rapid prototyping simulation and its single board DS1103, a simulation model including vehicle control signals is set up in MATLAB/Simulink, the model is then built into C code, and the system defined file（SDF） is downloaded to the DS1103 board through the experiment debug software ControlDesk and is kept running. Programming is made by mixing Visual C＋＋ 6.0, MATLAB API and Vega API. Control signals are read out by invoking library function MLIB/MTRACE of dSPACE. All the input, output, and system state values are acquired by arithmetic and are dynamically associated with the running status of the virtual vehicle. An intelligent vehicle experiment system is thus developed by virtue of program and integration. The system has not only the demonstration function, such as general driving, cruise control, active avoiding collision, but also the function of virtual experiment. Parameters of the system can be set according to needs, and the virtual test results can be analyzed and studied and used for the comparison with the existing models. The system reflects the running of the intelligent vehicle in the virtual traffic environment, at the same time, the system is a new attempt performed on the intelligent vehicle travel research and provides also a new research method for 展开更多
基金supported in part by the National Natural Science Foundation of China under Grants 61971126 and 61921004ZTE CorporationState Key Laboratory of Mobile Network and Mobile Multimedia Technology.
文摘In this paper,we investigate the reconfigurable intelligent surface(RIS)-enabled multiple-input-single-output orthogonal frequency division multiplexing(MISO-OFDM)system under frequency-selective channels,and propose a low-complexity alternating optimization(AO)based joint beamforming and RIS phase shifts optimization algorithm to maximize the achievable rate.First,with fixed RIS phase shifts,we devise the optimal closedform transmit beamforming vectors corresponding to different subcarriers.Then,with given active beamforming vectors,near-optimal RIS reflection coefficients can be determined efficiently leveraging fractional programming(FP)combined with manifold optimization(MO)or majorization-minimization(MM)framework.Additionally,we also propose a heuristic RIS phase shifts design approach based on the sum of subcarrier gain maximization(SSGM)criterion requiring lower complexity.Numerical results indicate that the proposed MO/MM algorithm can achieve almost the same rate as the upper bound achieved by the semidefinite relaxation(SDR)algorithm,and the proposed SSGM based scheme is only slightly inferior to the upper bound while has much lower complexity.These results demonstrate the effectiveness of the proposed algorithms.
文摘The prediction of liquefaction-induced lateral spreading/displacement(Dh)is a challenging task for civil/geotechnical engineers.In this study,a new approach is proposed to predict Dh using gene expression programming(GEP).Based on statistical reasoning,individual models were developed for two topographies:free-face and gently sloping ground.Along with a comparison with conventional approaches for predicting the Dh,four additional regression-based soft computing models,i.e.Gaussian process regression(GPR),relevance vector machine(RVM),sequential minimal optimization regression(SMOR),and M5-tree,were developed and compared with the GEP model.The results indicate that the GEP models predict Dh with less bias,as evidenced by the root mean square error(RMSE)and mean absolute error(MAE)for training(i.e.1.092 and 0.815;and 0.643 and 0.526)and for testing(i.e.0.89 and 0.705;and 0.773 and 0.573)in free-face and gently sloping ground topographies,respectively.The overall performance for the free-face topology was ranked as follows:GEP>RVM>M5-tree>GPR>SMOR,with a total score of 40,32,24,15,and 10,respectively.For the gently sloping condition,the performance was ranked as follows:GEP>RVM>GPR>M5-tree>SMOR with a total score of 40,32,21,19,and 8,respectively.Finally,the results of the sensitivity analysis showed that for both free-face and gently sloping ground,the liquefiable layer thickness(T_(15))was the major parameter with percentage deterioration(%D)value of 99.15 and 90.72,respectively.
基金supported by Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20070006011)
文摘Existing vehicle experiment systems tend to focus on the research of vehicle dynamics by conducting performance tests on every system or some parts of the vehicle so as to improve the entire performance of the vehicle. Virtual technology is widely utilized in various vehicle test-beds. These test-beds are mainly used to simulate the driving training, conduct the research on drivers＇ behaviors, or give virtual demonstrations of the transportation environment. However, the study on the active safety of the running vehicle in the virtual environment is still insufficient. A virtual scene including roads and vehicles is developed by using the software Creator and Vega, and radars and cameras are also simulated in the scene. Based on dSPACE＇s rapid prototyping simulation and its single board DS1103, a simulation model including vehicle control signals is set up in MATLAB/Simulink, the model is then built into C code, and the system defined file（SDF） is downloaded to the DS1103 board through the experiment debug software ControlDesk and is kept running. Programming is made by mixing Visual C＋＋ 6.0, MATLAB API and Vega API. Control signals are read out by invoking library function MLIB/MTRACE of dSPACE. All the input, output, and system state values are acquired by arithmetic and are dynamically associated with the running status of the virtual vehicle. An intelligent vehicle experiment system is thus developed by virtue of program and integration. The system has not only the demonstration function, such as general driving, cruise control, active avoiding collision, but also the function of virtual experiment. Parameters of the system can be set according to needs, and the virtual test results can be analyzed and studied and used for the comparison with the existing models. The system reflects the running of the intelligent vehicle in the virtual traffic environment, at the same time, the system is a new attempt performed on the intelligent vehicle travel research and provides also a new research method for
