The symbiotic FM radio data system(SRDS)is a radio data system that a specially designed OFDM signal co-lives with FM signal,which enables a significantly higher data rate than existing radio data systems.The cyclic p...The symbiotic FM radio data system(SRDS)is a radio data system that a specially designed OFDM signal co-lives with FM signal,which enables a significantly higher data rate than existing radio data systems.The cyclic prefix of the OFDM symbol has the same length as the OFDM body,which enables the analytic separation of the co-channel OFDM and FM signal at receiver side,utilizing the fact that the OFDM body and prefix is equal.In this work,we show that the OFDM body and prefix cannot be viewed as equal when there is sufficient carrier frequency offset(CFO).Thus,we propose a two-step CFO estimation algorithm for FM and SRDS hybrid signal.The first step estimates the coarse CFO by exploring the characteristics of the FM signal.Once the coarse CFO is removed,the residual CFO is small enough for FM and OFDM separation.The second step fine estimates CFO from the OFDM-only signal using its repeated PN structure after the separation.Detailed mathematical equations are formulated and simulation results are given.The results show that the proposed algorithm works fine with the simulation setup and has a final residual CFO less than 3.9Hz.展开更多
The principle of the support vector regression machine（SVR） is first analysed. Then the new data-dependent kernel function is constructed from information geometry perspective. The current waveforms change regularly...The principle of the support vector regression machine（SVR） is first analysed. Then the new data-dependent kernel function is constructed from information geometry perspective. The current waveforms change regularly in accordance with the different horizontal offset when the rotational frequency of the high speed rotational arc sensor is in the range from 15 Hz to 30 Hz. The welding current data is pretreated by wavelet filtering, mean filtering and normalization treatment. The SVR model is constructed by making use of the evolvement laws, the decision function can be achieved by training the SVR and the seam offset can be identified. The experimental results show that the precision of the offset identification can be greatly improved by modifying the SVR and applying mean filteringfrom the longitudinal direction.展开更多
基金supported by the National Natural Science Foundation of China (Grant No.61671264)Basic scientific research project of Beijing University of Posts and Telecommunications (Grant No. 2019RC02)National Key R&D Program of China(Grant No.2018YFE0101000)
文摘The symbiotic FM radio data system(SRDS)is a radio data system that a specially designed OFDM signal co-lives with FM signal,which enables a significantly higher data rate than existing radio data systems.The cyclic prefix of the OFDM symbol has the same length as the OFDM body,which enables the analytic separation of the co-channel OFDM and FM signal at receiver side,utilizing the fact that the OFDM body and prefix is equal.In this work,we show that the OFDM body and prefix cannot be viewed as equal when there is sufficient carrier frequency offset(CFO).Thus,we propose a two-step CFO estimation algorithm for FM and SRDS hybrid signal.The first step estimates the coarse CFO by exploring the characteristics of the FM signal.Once the coarse CFO is removed,the residual CFO is small enough for FM and OFDM separation.The second step fine estimates CFO from the OFDM-only signal using its repeated PN structure after the separation.Detailed mathematical equations are formulated and simulation results are given.The results show that the proposed algorithm works fine with the simulation setup and has a final residual CFO less than 3.9Hz.
基金Supported by National Natural Science Foundation of China（ No. 50705030）.
文摘The principle of the support vector regression machine（SVR） is first analysed. Then the new data-dependent kernel function is constructed from information geometry perspective. The current waveforms change regularly in accordance with the different horizontal offset when the rotational frequency of the high speed rotational arc sensor is in the range from 15 Hz to 30 Hz. The welding current data is pretreated by wavelet filtering, mean filtering and normalization treatment. The SVR model is constructed by making use of the evolvement laws, the decision function can be achieved by training the SVR and the seam offset can be identified. The experimental results show that the precision of the offset identification can be greatly improved by modifying the SVR and applying mean filteringfrom the longitudinal direction.
