Acquiring acoustic modes with high quality data in larg e-scale nacelles is quite challenging in the engine industry because of the complex configuration,high flow speed,tremendous number of acoustic modes,and some ot...Acquiring acoustic modes with high quality data in larg e-scale nacelles is quite challenging in the engine industry because of the complex configuration,high flow speed,tremendous number of acoustic modes,and some other extraordinary interference.A complete procedure for mode detection in the engine industry that is applicable to full-size situations is proposed.Two diffe rent array patterns are adopted:a circular array for azimuthal modes in both the intake and bypass ducts,and a rotating linear array for radial modes only in the bypass duct.The azimuthal locations of sensors in the circumferential array are non-uniformly distributed to get more modes than the Nyquist limit.For each individual channel signal,an adaptive resampling method is adopted to reduce the components incoherent with source rotation and frequency shifts caused by shaft speed variation.At high flow speeds,boundary turbulence contaminates acoustic signals of wall-flush mounted sensors.A wavenumber decomposition method is used to separate the acoustic part and the dynamic pressure part in the bypass duct during radial mode detection.Finally,both the azimuthal and radial acoustic modes in bypass and intake ducts are acquired successfully.展开更多
Mobility data,based on global positioning system(GPS)tracking,have been widely used in many areas,such as analyzing travel patterns,investigating transport safety and efficiency,and evaluating travel impacts.Transport...Mobility data,based on global positioning system(GPS)tracking,have been widely used in many areas,such as analyzing travel patterns,investigating transport safety and efficiency,and evaluating travel impacts.Transport modes are essential factors in understanding mobility within the transport system.Therefore,in this study,a significant number of algorithms were tested for transport mode detection.However,no conclusive recommendations can be drawn regarding which method should be used.The evaluation of the performance of the algorithms was not discussed systematically either in current literature.This paper aims to provide an in-depth review of the methods applied in transport mode detection based on GPS tracking data.The performances of the reviewed methods are then compared and evaluated to provide guidance in choosing algorithms for transport mode detection based on GPS tracking data.The results indicate that the majority of current studies are based on a supervised learning method for transport mode detection.Many of the reviewed methods first require manual dataset labeling,which can produce major drawbacks,such as inefficiency and human errors.It was also found that deep learning approaches have the potential to deal with large amounts of unlabeled raw GPS datasets and increase the accuracy and efficiency of transport mode detection.展开更多
This research presents a methodology,to calculate the amount of physical activity during the transportation.It contains the following steps:(1)trip and activity detection(2)speed calculation(3)splitting trips into tri...This research presents a methodology,to calculate the amount of physical activity during the transportation.It contains the following steps:(1)trip and activity detection(2)speed calculation(3)splitting trips into trip-leg(4)transportation mode detection and(5)physical activity calculation.The Global Positioning System is used to record the transport activities,either single mode or multimode.During the trip execution,the travel behaviour and the travel mode are also observed to obtain the physical activity levels.The physical activity levels are calculated by taking the ratio of the Total Energy Expenditure and the Basal Metabolic Rate.To obtain the results,an automated system is presented which calculates the speed and also detects the mode of each trip-leg.It also calculates the amount of physical activity.The obtained physical activity levels for the recorded 1750 trips are unit less and range from 1.10 to 2.00.By using the motorized transportation mode,the physical activity levels stay low and the subject failed to achieve the recommended health guideline.The minimum value for the moderate level of physical activity is 1.6.The requirement can be fully achieved when the transportation mode is active i.e.walking,cycling,and performed at moderate intensity level for at least 30 min a day.展开更多
Oil spills pose a major threat to ocean ecosystems and their health. Synthetic aperture radar（SAR） sensors can detect oil spills on the sea surface. These oil spills appear as dark spots in SAR images. However, dark...Oil spills pose a major threat to ocean ecosystems and their health. Synthetic aperture radar（SAR） sensors can detect oil spills on the sea surface. These oil spills appear as dark spots in SAR images. However, dark formations can be caused by a number of phenomena. It is aimed to distinguishing oil spills or look-alike objects. A novel method based on a bidimensional empirical mode decomposition is proposed. The selected dark formations are first decomposed into several bidimensional intrinsic mode functions and the residue. Subsequently, 64 dimension feature sets are calculated using the Hilbert spectral analysis and five new features are extracted with a relief algorithm. Mahalanobis distances are then used for classification. Three data sets containing oil spills or look-alikes are used to test the accuracy rate of the method. The accuracy rate is more than 90%. The experimental results demonstrate that the novel method can detect oil spills validly and accurately.展开更多
The wearable lower limb exoskeleton is a typical human-in-loop human–robot coupled system,which conducts natural and close cooperation with the human by recognizing human locomotion timely.Requiring subject-specific ...The wearable lower limb exoskeleton is a typical human-in-loop human–robot coupled system,which conducts natural and close cooperation with the human by recognizing human locomotion timely.Requiring subject-specific training is the main challenge of the existing approaches,and most methods have the problem of insufficient recognition.This paper proposes an integral subject-adaptive real-time Locomotion Mode Recognition(LMR)method based on GA-CNN for a lower limb exoskeleton system.The LMR method is a combination of Convolutional Neural Networks(CNN)and Genetic Algorithm(GA)-based multi-sensor information selection.To improve network performance,the hyper-parameters are optimized by Bayesian optimization.An exoskeleton prototype system with multi-type sensors and novel sensing-shoes is used to verify the proposed method.Twelve locomotion modes,which composed an integral locomotion system for the daily application of the exoskeleton,can be recognized by the proposed method.According to a series of experiments,the recognizer shows strong comprehensive abilities including high accuracy,low delay,and sufficient adaption to different subjects.展开更多
In this study,we selected 18 SG（superconducting gravimeter）records from 15 GGP stations with 99 vertical and 69 horizontal components of IRIS broad-band seismograms during 2004 Sumatra Earthquake to detect the split...In this study,we selected 18 SG（superconducting gravimeter）records from 15 GGP stations with 99 vertical and 69 horizontal components of IRIS broad-band seismograms during 2004 Sumatra Earthquake to detect the splitting of higher-degree Earth’s free oscillations modes（0S4,0S7〈sub〉0S10,2S4,1S5,2S5,1S6）and 12 inner-core sensitive modes（25S2,27S2,6S3,9S3,13S3,15S3,11S4,18S4,8S5,11S5,23S5,16S6）by using OSE（optimal sequence estimation）method which only considers self-coupling.Results indicate that OSE can completely isolate singlets of high-degree modes in time-domain,effectively resolve the coupled multiplets independently,and reduce the possibility of mode mixing and end effect,showing that OSE could improve some signals’signal-to-noise ratio.Comparing the results of SG records with seismic data sets suggests that the number of SG records is inadequate to detect all singlets of higher modes.Hence we mainly selected plentiful seismograms of IRIS to observe the multiplets of higher modes.We estimate frequencies of the singlets using AR method and evaluate the measurement error using bootstrap method.Besides,we compared the observations with the predictions of PREM-tidal model.This study demonstrates that OSE is effective in isolating singlets of Earth’s free oscillations with higher modes.The experimental results may provide constraints to the construction of 3D Earth model.展开更多
Earth’s free oscillation can provide essential constraints for refining Earth models,inverting seismic source mechanisms,and studying the deep internal structure of the Earth.Large earthquakes can simultaneously exci...Earth’s free oscillation can provide essential constraints for refining Earth models,inverting seismic source mechanisms,and studying the deep internal structure of the Earth.Large earthquakes can simultaneously excite numerous normal modes.Due to the Earth’s ellipticity,rotation,and internal heterogeneities,these normal modes undergo splitting,with the frequencies of singlets of normal modes becoming very close(only a fewµHz apart).This imposes greater demands on the detection of normal modes.This paper introduces a novel method for normal mode detection based on the normal time-frequency transform(NTFT).Compared to classical FT spectrum methods and recent optimal sequence estimation(OSE),the proposed method not only detects more weak normal modes but also reveals the spatial distribution of the phase of each normal mode.Taking the detection of 0S2 as an example,the phase measurements of each singlet are spatially inconsistent.This phenomenon can provide prior information for other methods,such as product spectrum analysis(PSA),spherical harmonic stacking(SHS),multistation experiments(MSE),and OSE.Additionally,understanding the phase distribution patterns contributes to further study of geological structures,offering crucial foundational data and observational support.展开更多
Circulating tumor cells(CTCs)are important markers for cancer.The part of tumor cells that are detached from the primary tumor or metastatic tumor and enter the blood circulation is called CTCs.It is crucial to develo...Circulating tumor cells(CTCs)are important markers for cancer.The part of tumor cells that are detached from the primary tumor or metastatic tumor and enter the blood circulation is called CTCs.It is crucial to develop a rapid,accurate,and easy-to-implement diagnostic system for CTCs for early tumor diagnosis and for monitoring progression of the disease.In this work,we reported a colorimetric and fluorescent dual-mode assay for the detection of CTCs.Our assay used magnetic nanoparticles and aptamer for CTCs capture and gold nanoparticles-loaded covalent organic frameworks(Au@COFs)for signal amplification,respectively.The magnetic nanoparticles were modified with folic acid to capture CTCs by interaction between folic acid and the folate receptor overexpressed on the surface of tumor cells.The covalent organic frameworks were engineered to have both nitro-reductase-like and glucose–oxidase-like activities.The nitro-reductase-like activity converted the substrate p-nitrophenol to p-nitroaniline for colorimetric detection,and the glucose-oxidase-like activity enabled fluorescence detection.Specifically,Au@COFs catalyzed glucose oxidation and generated hydrogen peroxide to oxidize Fe 2+to Fe 3+,which converted MIL(Al)-MOF to MIL(Fe)-MOF through ion exchange,resulting in the fluorescence quenching of MIL(Al)-MOF.Our assay showed high sensitivity with a detection limit of 17 cells/mL using MCF-7 cells as model cancer cells.This work provided an e fficient and ultrasensitive strategy for CTCs detection and has potential applications in cancer identification and diagnosis.Dual-mode detection system,combining colorimetric and fluorescent signals,integration of magnetic nanoparticles and aptamers for CTC capture,and utilization of covalent organic frameworks loaded with gold nanoparticles for signal amplification can improve sensitivity and accuracy.展开更多
Gyroscopes are crucial components of inertial navigation systems,with ongoing development emphasizing miniaturization and enhanced accuracy.The recent advances in chip-scale optical gyroscopes utilizing integrated opt...Gyroscopes are crucial components of inertial navigation systems,with ongoing development emphasizing miniaturization and enhanced accuracy.The recent advances in chip-scale optical gyroscopes utilizing integrated optics have attracted considerable attention,demonstrating significant advantages in achieving tactical-grade accuracy.In this paper,a new,to our knowledge,integrated optical gyroscope scheme based on the multi-mode co-detection technology is proposed,which takes the high-Q microcavity as its core sensitive element and uses the multi-mode characteristics of the microcavity to achieve the measurement of rotational angular velocity.This detection scheme breaks the tradition of optical gyroscopes based on a single mode within the sensitive ring to detect the angular rotation rate,which not only greatly simplifies the optical and electrical system of the optical gyroscope,but also has a higher detection accuracy.The gyroscope based on this detection scheme has successfully detected the Earth's rotation on a 9.2 mm diameter microcavity with a bias instability as low as 1 deg/h,which is the best performance among the chip-scale integrated optical gyroscopes known to us.展开更多
The COVID-19 pandemic has brought great challenges to traditional nucleic acid detection technology.Thus,it is urgent to develop a more simple and efficient nucleic acid detection technology.CRISPR-Cas12 has signal am...The COVID-19 pandemic has brought great challenges to traditional nucleic acid detection technology.Thus,it is urgent to develop a more simple and efficient nucleic acid detection technology.CRISPR-Cas12 has signal amplification ability,high sensitivity and high nucleic acid recognition specificity,so it is considered as a nucleic acid detection tool with broad development prospects and high application value.This review paper discusses recent advances in CRISPR-Cas12-based nucleic acid detection,with an emphasis on the new research methods and means to improve the nucleic acid detection capability of CRISPR-Cas12.Strategies for improving sensitivity,optimization of integrated detection,development of sim-plified detection mode and improvement of quantitative detection capabilities are included.Finally,the future development of CRISPR-Cas12-based nucleic acids detection is prospected.展开更多
A few-mode fiber （FMF） is designed to support three spatial modes （LP01, LP 11a, and LP 11 b） and fabricated through plasma chemical vapor deposition （PCVD）and rod-in-tube （RIT） method. Using PDM-DFTS-OFDM- 32...A few-mode fiber （FMF） is designed to support three spatial modes （LP01, LP 11a, and LP 11 b） and fabricated through plasma chemical vapor deposition （PCVD）and rod-in-tube （RIT） method. Using PDM-DFTS-OFDM- 32QAM modulation, wavelength division multiplexing, mode multiplexing, and coherent detection, we successfully demonstrated 200Tb/s （375× 3 × 178.125Gb/s） signal over 1 km FMF using C and L bands with 25 GHz channel spacing. After 1 km FMF transmission, all the tested bit error rates （BERs） are below 20% forward error correction （FEC） threshold （2.0 × 10-2）. Within each sub-channel, we achieved a spectral efficiency of 21.375 bits/Hz in the C and L bands.展开更多
基金supported by the National Key R&D Program of China(2021YFB3703900)。
文摘Acquiring acoustic modes with high quality data in larg e-scale nacelles is quite challenging in the engine industry because of the complex configuration,high flow speed,tremendous number of acoustic modes,and some other extraordinary interference.A complete procedure for mode detection in the engine industry that is applicable to full-size situations is proposed.Two diffe rent array patterns are adopted:a circular array for azimuthal modes in both the intake and bypass ducts,and a rotating linear array for radial modes only in the bypass duct.The azimuthal locations of sensors in the circumferential array are non-uniformly distributed to get more modes than the Nyquist limit.For each individual channel signal,an adaptive resampling method is adopted to reduce the components incoherent with source rotation and frequency shifts caused by shaft speed variation.At high flow speeds,boundary turbulence contaminates acoustic signals of wall-flush mounted sensors.A wavenumber decomposition method is used to separate the acoustic part and the dynamic pressure part in the bypass duct during radial mode detection.Finally,both the azimuthal and radial acoustic modes in bypass and intake ducts are acquired successfully.
基金the financial supported by the Swedish Energy Agency (project no. 46068-1)
文摘Mobility data,based on global positioning system(GPS)tracking,have been widely used in many areas,such as analyzing travel patterns,investigating transport safety and efficiency,and evaluating travel impacts.Transport modes are essential factors in understanding mobility within the transport system.Therefore,in this study,a significant number of algorithms were tested for transport mode detection.However,no conclusive recommendations can be drawn regarding which method should be used.The evaluation of the performance of the algorithms was not discussed systematically either in current literature.This paper aims to provide an in-depth review of the methods applied in transport mode detection based on GPS tracking data.The performances of the reviewed methods are then compared and evaluated to provide guidance in choosing algorithms for transport mode detection based on GPS tracking data.The results indicate that the majority of current studies are based on a supervised learning method for transport mode detection.Many of the reviewed methods first require manual dataset labeling,which can produce major drawbacks,such as inefficiency and human errors.It was also found that deep learning approaches have the potential to deal with large amounts of unlabeled raw GPS datasets and increase the accuracy and efficiency of transport mode detection.
文摘This research presents a methodology,to calculate the amount of physical activity during the transportation.It contains the following steps:(1)trip and activity detection(2)speed calculation(3)splitting trips into trip-leg(4)transportation mode detection and(5)physical activity calculation.The Global Positioning System is used to record the transport activities,either single mode or multimode.During the trip execution,the travel behaviour and the travel mode are also observed to obtain the physical activity levels.The physical activity levels are calculated by taking the ratio of the Total Energy Expenditure and the Basal Metabolic Rate.To obtain the results,an automated system is presented which calculates the speed and also detects the mode of each trip-leg.It also calculates the amount of physical activity.The obtained physical activity levels for the recorded 1750 trips are unit less and range from 1.10 to 2.00.By using the motorized transportation mode,the physical activity levels stay low and the subject failed to achieve the recommended health guideline.The minimum value for the moderate level of physical activity is 1.6.The requirement can be fully achieved when the transportation mode is active i.e.walking,cycling,and performed at moderate intensity level for at least 30 min a day.
基金The National Science and Technology Support Project under contract No.2014BAB12B02the Natural Science Foundation of Liaoning Province under contract No.201602042
文摘Oil spills pose a major threat to ocean ecosystems and their health. Synthetic aperture radar（SAR） sensors can detect oil spills on the sea surface. These oil spills appear as dark spots in SAR images. However, dark formations can be caused by a number of phenomena. It is aimed to distinguishing oil spills or look-alike objects. A novel method based on a bidimensional empirical mode decomposition is proposed. The selected dark formations are first decomposed into several bidimensional intrinsic mode functions and the residue. Subsequently, 64 dimension feature sets are calculated using the Hilbert spectral analysis and five new features are extracted with a relief algorithm. Mahalanobis distances are then used for classification. Three data sets containing oil spills or look-alikes are used to test the accuracy rate of the method. The accuracy rate is more than 90%. The experimental results demonstrate that the novel method can detect oil spills validly and accurately.
文摘The wearable lower limb exoskeleton is a typical human-in-loop human–robot coupled system,which conducts natural and close cooperation with the human by recognizing human locomotion timely.Requiring subject-specific training is the main challenge of the existing approaches,and most methods have the problem of insufficient recognition.This paper proposes an integral subject-adaptive real-time Locomotion Mode Recognition(LMR)method based on GA-CNN for a lower limb exoskeleton system.The LMR method is a combination of Convolutional Neural Networks(CNN)and Genetic Algorithm(GA)-based multi-sensor information selection.To improve network performance,the hyper-parameters are optimized by Bayesian optimization.An exoskeleton prototype system with multi-type sensors and novel sensing-shoes is used to verify the proposed method.Twelve locomotion modes,which composed an integral locomotion system for the daily application of the exoskeleton,can be recognized by the proposed method.According to a series of experiments,the recognizer shows strong comprehensive abilities including high accuracy,low delay,and sufficient adaption to different subjects.
基金supported by the National 973 Project of China (No.2013CB733305)the NSFC (Nos.41174011,41429401,41574007,41210006,41128003,41021061)
文摘In this study,we selected 18 SG（superconducting gravimeter）records from 15 GGP stations with 99 vertical and 69 horizontal components of IRIS broad-band seismograms during 2004 Sumatra Earthquake to detect the splitting of higher-degree Earth’s free oscillations modes（0S4,0S7〈sub〉0S10,2S4,1S5,2S5,1S6）and 12 inner-core sensitive modes（25S2,27S2,6S3,9S3,13S3,15S3,11S4,18S4,8S5,11S5,23S5,16S6）by using OSE（optimal sequence estimation）method which only considers self-coupling.Results indicate that OSE can completely isolate singlets of high-degree modes in time-domain,effectively resolve the coupled multiplets independently,and reduce the possibility of mode mixing and end effect,showing that OSE could improve some signals’signal-to-noise ratio.Comparing the results of SG records with seismic data sets suggests that the number of SG records is inadequate to detect all singlets of higher modes.Hence we mainly selected plentiful seismograms of IRIS to observe the multiplets of higher modes.We estimate frequencies of the singlets using AR method and evaluate the measurement error using bootstrap method.Besides,we compared the observations with the predictions of PREM-tidal model.This study demonstrates that OSE is effective in isolating singlets of Earth’s free oscillations with higher modes.The experimental results may provide constraints to the construction of 3D Earth model.
基金supported by Natural Science Foundation of China(No.41704003)Shandong Provincial Natural Science Foundation(No.ZR2021MD031).
文摘Earth’s free oscillation can provide essential constraints for refining Earth models,inverting seismic source mechanisms,and studying the deep internal structure of the Earth.Large earthquakes can simultaneously excite numerous normal modes.Due to the Earth’s ellipticity,rotation,and internal heterogeneities,these normal modes undergo splitting,with the frequencies of singlets of normal modes becoming very close(only a fewµHz apart).This imposes greater demands on the detection of normal modes.This paper introduces a novel method for normal mode detection based on the normal time-frequency transform(NTFT).Compared to classical FT spectrum methods and recent optimal sequence estimation(OSE),the proposed method not only detects more weak normal modes but also reveals the spatial distribution of the phase of each normal mode.Taking the detection of 0S2 as an example,the phase measurements of each singlet are spatially inconsistent.This phenomenon can provide prior information for other methods,such as product spectrum analysis(PSA),spherical harmonic stacking(SHS),multistation experiments(MSE),and OSE.Additionally,understanding the phase distribution patterns contributes to further study of geological structures,offering crucial foundational data and observational support.
基金financially supported by Major science and technology project of Yunnan Province(202302AE090022)Key Research and Development Program of Yunnan(202203AC100010)+6 种基金the National Natural Science Foundation of China(32160597,32160236,32371463)National Key Research and Development Program of China(2022YFC2601604)Cardiovascular Ultrasound Innovation Team of Yunnan Province(202305AS350021)Spring City Plan:the High-level Talent Promotion and Training Project of Kunming(2022SCP001)the Association Foundation Program of Yunnan Provincial Science and TechnologyDepar tmentKunming Medical University(202101AY070001-278)the second phase of“Double-First Class”program construction of Yunnan University。
文摘Circulating tumor cells(CTCs)are important markers for cancer.The part of tumor cells that are detached from the primary tumor or metastatic tumor and enter the blood circulation is called CTCs.It is crucial to develop a rapid,accurate,and easy-to-implement diagnostic system for CTCs for early tumor diagnosis and for monitoring progression of the disease.In this work,we reported a colorimetric and fluorescent dual-mode assay for the detection of CTCs.Our assay used magnetic nanoparticles and aptamer for CTCs capture and gold nanoparticles-loaded covalent organic frameworks(Au@COFs)for signal amplification,respectively.The magnetic nanoparticles were modified with folic acid to capture CTCs by interaction between folic acid and the folate receptor overexpressed on the surface of tumor cells.The covalent organic frameworks were engineered to have both nitro-reductase-like and glucose–oxidase-like activities.The nitro-reductase-like activity converted the substrate p-nitrophenol to p-nitroaniline for colorimetric detection,and the glucose-oxidase-like activity enabled fluorescence detection.Specifically,Au@COFs catalyzed glucose oxidation and generated hydrogen peroxide to oxidize Fe 2+to Fe 3+,which converted MIL(Al)-MOF to MIL(Fe)-MOF through ion exchange,resulting in the fluorescence quenching of MIL(Al)-MOF.Our assay showed high sensitivity with a detection limit of 17 cells/mL using MCF-7 cells as model cancer cells.This work provided an e fficient and ultrasensitive strategy for CTCs detection and has potential applications in cancer identification and diagnosis.Dual-mode detection system,combining colorimetric and fluorescent signals,integration of magnetic nanoparticles and aptamers for CTC capture,and utilization of covalent organic frameworks loaded with gold nanoparticles for signal amplification can improve sensitivity and accuracy.
基金National Key Research and Development Program of China(2023YFB3906402)。
文摘Gyroscopes are crucial components of inertial navigation systems,with ongoing development emphasizing miniaturization and enhanced accuracy.The recent advances in chip-scale optical gyroscopes utilizing integrated optics have attracted considerable attention,demonstrating significant advantages in achieving tactical-grade accuracy.In this paper,a new,to our knowledge,integrated optical gyroscope scheme based on the multi-mode co-detection technology is proposed,which takes the high-Q microcavity as its core sensitive element and uses the multi-mode characteristics of the microcavity to achieve the measurement of rotational angular velocity.This detection scheme breaks the tradition of optical gyroscopes based on a single mode within the sensitive ring to detect the angular rotation rate,which not only greatly simplifies the optical and electrical system of the optical gyroscope,but also has a higher detection accuracy.The gyroscope based on this detection scheme has successfully detected the Earth's rotation on a 9.2 mm diameter microcavity with a bias instability as low as 1 deg/h,which is the best performance among the chip-scale integrated optical gyroscopes known to us.
基金supported by the National Natural Science Foundation of China(91959128,21874049).
文摘The COVID-19 pandemic has brought great challenges to traditional nucleic acid detection technology.Thus,it is urgent to develop a more simple and efficient nucleic acid detection technology.CRISPR-Cas12 has signal amplification ability,high sensitivity and high nucleic acid recognition specificity,so it is considered as a nucleic acid detection tool with broad development prospects and high application value.This review paper discusses recent advances in CRISPR-Cas12-based nucleic acid detection,with an emphasis on the new research methods and means to improve the nucleic acid detection capability of CRISPR-Cas12.Strategies for improving sensitivity,optimization of integrated detection,development of sim-plified detection mode and improvement of quantitative detection capabilities are included.Finally,the future development of CRISPR-Cas12-based nucleic acids detection is prospected.
基金Aeknowledgements This work was supported by the Major Scientific and Technological hmovation Projects of Hubci Province （No. 2014AAA001）, the National Basic Research Program of China （Nos. 2014CB340100, 2014CB340101, and 2014CB340105）. and the Natural Science Foundation of Hubei Prov incc （No. 2015CFA056）.
文摘A few-mode fiber （FMF） is designed to support three spatial modes （LP01, LP 11a, and LP 11 b） and fabricated through plasma chemical vapor deposition （PCVD）and rod-in-tube （RIT） method. Using PDM-DFTS-OFDM- 32QAM modulation, wavelength division multiplexing, mode multiplexing, and coherent detection, we successfully demonstrated 200Tb/s （375× 3 × 178.125Gb/s） signal over 1 km FMF using C and L bands with 25 GHz channel spacing. After 1 km FMF transmission, all the tested bit error rates （BERs） are below 20% forward error correction （FEC） threshold （2.0 × 10-2）. Within each sub-channel, we achieved a spectral efficiency of 21.375 bits/Hz in the C and L bands.
