A hybrid calibration approach based on support vector machines （SVM） is proposed to characterize nonlinear cross coupling of multi-dimensional transducer. It is difficult to identify these unknown nonlinearities and...A hybrid calibration approach based on support vector machines （SVM） is proposed to characterize nonlinear cross coupling of multi-dimensional transducer. It is difficult to identify these unknown nonlinearities and crosstalk just with a single conventional calibration approach. In this paper, a hybrid model comprising calibration matrix and SVM model for calibrating linearity and nonlinearity respectively is built up. The calibration matrix is determined by linear artificial neural network （ANN）, and the SVM is used to compensate for the nonlinear cross coupling among each dimension. A simulation of the calibration of a multi-dimensional sensor is conducted by the SVM hybrid calibration method, which is then utilized to calibrate a six-component force/torque transducer of wind tunnel balance. From the calibrating results, it can be indicated that the SVM hybrid calibration method has improved the calibration accuracy significantly without increasing data samples, compared with calibration matrix. Moreover, with the calibration matrix, the hybrid model can provide a basis for the design of transducers.展开更多
A segmentation multi-dimensional crest factor reduction （SMD-CFR） algorithm is proposed for multi-service supporting digital radio over fibre （DRoF） system. Benefit from segmentation dynamic clipping threshold and...A segmentation multi-dimensional crest factor reduction （SMD-CFR） algorithm is proposed for multi-service supporting digital radio over fibre （DRoF） system. Benefit from segmentation dynamic clipping threshold and clipping factor got basing on characteristics of all service bands, the SMD-CFR is able to get better peak clipping and peak to average power ratio （PAPR） reduction for multi-band combined signal. Simulation results show that SMD-CFR gets more than 2.3 reduction in PAPR for two-bands combined signal of long term evolution （LTE） , which is much better than traditional one dimensional （1D）-CFR. Meanwhile, for 64-quadrature amplitude modulation （QAM） modulation and demodulation link, it has very small effect on bit error rate （BER） and error vector magnitude （EVM） , which are controlled less than 0. 1% and 0.2% respectively. For hardware experiment, SMD-CFR obtains 4.5% increase in drain efficiency and about 4 dBc increase in adjacent channel leakage ratio （ACLR）. These are very significant for the wide band power amplifier （PA） in multi-service supporting DRoF system.展开更多
基金National Science Foundation of China(Grant No.10772142)National Natural Science Key Foundation of China(Grant No.10832002)the Fundamental Research Funds for the Central Universities
文摘A hybrid calibration approach based on support vector machines （SVM） is proposed to characterize nonlinear cross coupling of multi-dimensional transducer. It is difficult to identify these unknown nonlinearities and crosstalk just with a single conventional calibration approach. In this paper, a hybrid model comprising calibration matrix and SVM model for calibrating linearity and nonlinearity respectively is built up. The calibration matrix is determined by linear artificial neural network （ANN）, and the SVM is used to compensate for the nonlinear cross coupling among each dimension. A simulation of the calibration of a multi-dimensional sensor is conducted by the SVM hybrid calibration method, which is then utilized to calibrate a six-component force/torque transducer of wind tunnel balance. From the calibrating results, it can be indicated that the SVM hybrid calibration method has improved the calibration accuracy significantly without increasing data samples, compared with calibration matrix. Moreover, with the calibration matrix, the hybrid model can provide a basis for the design of transducers.
基金supported by the projects of ‘Smart in-building Wireless System using Flexible Digital Transmission Technology(SWIFT)’‘Research on in-building Signal Coverage System of Mobile IOT Based on Cloud’
文摘A segmentation multi-dimensional crest factor reduction （SMD-CFR） algorithm is proposed for multi-service supporting digital radio over fibre （DRoF） system. Benefit from segmentation dynamic clipping threshold and clipping factor got basing on characteristics of all service bands, the SMD-CFR is able to get better peak clipping and peak to average power ratio （PAPR） reduction for multi-band combined signal. Simulation results show that SMD-CFR gets more than 2.3 reduction in PAPR for two-bands combined signal of long term evolution （LTE） , which is much better than traditional one dimensional （1D）-CFR. Meanwhile, for 64-quadrature amplitude modulation （QAM） modulation and demodulation link, it has very small effect on bit error rate （BER） and error vector magnitude （EVM） , which are controlled less than 0. 1% and 0.2% respectively. For hardware experiment, SMD-CFR obtains 4.5% increase in drain efficiency and about 4 dBc increase in adjacent channel leakage ratio （ACLR）. These are very significant for the wide band power amplifier （PA） in multi-service supporting DRoF system.
