N-soliton (N>2) interaction in optical fibers including third-order dispersion is simulated numerically.In equal amplitude soliton transmission,the coalescence resulted from the mutual interaction among N solitons ...N-soliton (N>2) interaction in optical fibers including third-order dispersion is simulated numerically.In equal amplitude soliton transmission,the coalescence resulted from the mutual interaction among N solitons still exists,while in the unequal case,soliton interaction can not be removed but becomes more serious due to the effect of third-order dispersion.Therefore,we can not consider third-order dispersion as an utilizable factor for removing soliton interaction.展开更多
Dispersive optics quantum key distribution(DO-QKD)based on energy-time entangled photon pairs is an important QKD scheme.In DO-QKD,the arrival time of photons is used in key generation and security analysis,which woul...Dispersive optics quantum key distribution(DO-QKD)based on energy-time entangled photon pairs is an important QKD scheme.In DO-QKD,the arrival time of photons is used in key generation and security analysis,which would be greatly affected by fiber dispersion.In this work,we establish a theoretical model of the entanglement-based DO-QKD system,considering the protocol,physical processes(such as fiber transmission and single-photon detection),and the analysis of security tests.Based on this theoretical model,we investigate the influence of chromatic dispersion introduced by transmission fibers on the performance of DO-QKD.By analyzing the benefits and costs of dispersion compensation,the system performance under G.652 and G.655 optical fibers are shown,respectively.The results show that dispersion compensation is unnecessary for DO-QKD systems in campus networks and even metro networks.Whereas,it is still required in DO-QKD systems with longer fiber transmission distances.展开更多
A quasi resonant pulse width modulation（PWM） inverter is used in a solar power system to convert the solar panel and battery charger＇s direct current（DC） output to alternating current（AC）.Although much has been...A quasi resonant pulse width modulation（PWM） inverter is used in a solar power system to convert the solar panel and battery charger＇s direct current（DC） output to alternating current（AC）.Although much has been published about DC to AC PWM inverters,none of the previous work has shown modeling and simulation results for DC to AC inverters.In this study,we suggest a new topology for a quasi resonant PWM inverter.Experimental results are also presented.展开更多
For a compact quantum key distribution (QKD) sender for the polarization encoding BB84 protocol, an eavesdropper could take a side-channel attack by measuring the spatial information of photons to infer their polariza...For a compact quantum key distribution (QKD) sender for the polarization encoding BB84 protocol, an eavesdropper could take a side-channel attack by measuring the spatial information of photons to infer their polarizations. The possibility of this attack can be reduced by introducing an aperture in the QKD sender, however, the effect of the aperture on the QKD security lacks of quantitative analysis. In this paper, we analyze the mutual information between the actual keys encoded at this QKD sender and the inferred keys at the eavesdropper (Eve), demonstrating the effect of the aperture to eliminate the spatial side-channel information quantitatively. It shows that Eve’s potential on eavesdropping spatial side-channel information is totally dependent on the optical design of the QKD sender, including the source arrangement and the aperture. The height of compact QKD senders with integrated light-emitting diode (LED) arrays could be controlled under several millimeters, showing great potential on applications in portable equipment.展开更多
Abstract--With the development of clean energy, switching and distribution issues in a photovoltaic system are getting much attention in recent years. This paper designs a DC to AC inverter and power switching and dis...Abstract--With the development of clean energy, switching and distribution issues in a photovoltaic system are getting much attention in recent years. This paper designs a DC to AC inverter and power switching and distribution system between a solar power system and the municipal system by using the Darlington amplifier structure with the photosensitive resistor and accompanying relays, and details the system circuits. The proposed system can achieve a stable output of IIOV AC, as well as self-generating driving voltage and switching between the municipal electrical system and the solar power system. The mathematic analysis and actually test results demonstrate that the proposed method is an easy, inexpensive, and low cost way to build a solar power switching and distribution system.展开更多
With the rapid development of smart devices and mobile networks,multimedia services will dominate most of data traffic in 4G/5G networks.Applications -such as conversational videos,online multimedia sharing,remote edu...With the rapid development of smart devices and mobile networks,multimedia services will dominate most of data traffic in 4G/5G networks.Applications -such as conversational videos,online multimedia sharing,remote education,etc.have gained their popularity and will become more ubiquitous among customers.Tra-展开更多
This study uses the smart phone with the Android system to construct a cloud-side smart switch system in the client-server architecture with the Android open platform system, using microprocessors(MCU 16F690) as the t...This study uses the smart phone with the Android system to construct a cloud-side smart switch system in the client-server architecture with the Android open platform system, using microprocessors(MCU 16F690) as the thermostat controller and combined with Raspberry Pi. The computing technology extends the control of the constant temperature from the local to the cloud, allowing the user to view the temperature status recorded by the cloud server using the smart phone application(App) or web browser. It can even remotely control the heating power of the smart switch for the heating device in the Internet control environment and use the proportional-integral-derivative(PID) control and the pulse-width modulation(PWM) technology to achieve intelligent constant temperature control.The proposed control system uses the expert PID control as the core to calculate the duty cycle of the PWM signal to control the power output of the smart switch for the constant temperature water tank. The experiment results verify the effectiveness of the proposed system.展开更多
We consider an image semantic communication system in a time-varying fading Gaussian MIMO channel,with a finite number of channel states.A deep learning-aided broadcast approach scheme is proposed to benefit the adapt...We consider an image semantic communication system in a time-varying fading Gaussian MIMO channel,with a finite number of channel states.A deep learning-aided broadcast approach scheme is proposed to benefit the adaptive semantic transmission in terms of different channel states.We combine the classic broadcast approach with the image transformer to implement this adaptive joint source and channel coding(JSCC)scheme.Specifically,we utilize the neural network(NN)to jointly optimize the hierarchical image compression and superposition code mapping within this scheme.The learned transformers and codebooks allow recovering of the image with an adaptive quality and low error rate at the receiver side,in each channel state.The simulation results exhibit our proposed scheme can dynamically adapt the coding to the current channel state and outperform some existing intelligent schemes with the fixed coding block.展开更多
Channel prediction is critical to address the channel aging issue in mobile scenarios.Existing channel prediction techniques are mainly designed for discrete channel prediction,which can only predict the future channe...Channel prediction is critical to address the channel aging issue in mobile scenarios.Existing channel prediction techniques are mainly designed for discrete channel prediction,which can only predict the future channel in a fixed time slot per frame,while the other intra-frame channels are usually recovered by interpolation.However,these approaches suffer from a serious interpolation loss,especially for mobile millimeter-wave communications.To solve this challenging problem,we propose a tensor neural ordinary differential equation(TN-ODE)based continuous-time channel prediction scheme to realize the direct prediction of intra-frame channels.Specifically,inspired by the recently developed continuous mapping model named neural ODE in the field of machine learning,we first utilize the neural ODE model to predict future continuous-time channels.To improve the channel prediction accuracy and reduce computational complexity,we then propose the TN-ODE scheme to learn the structural characteristics of the high-dimensional channel by low-dimensional learnable transform.Simulation results show that the proposed scheme is able to achieve higher intra-frame channel prediction accuracy than existing schemes.展开更多
IEEE International Conference on Communication Technology(ICCT)was jointly initiated and organized by IEEE Beijing Section and IEEE Com Soc in 1986.It is one of the highest-level academic events in the field of commun...IEEE International Conference on Communication Technology(ICCT)was jointly initiated and organized by IEEE Beijing Section and IEEE Com Soc in 1986.It is one of the highest-level academic events in the field of communication technology in China.It is also an international gathering for research for information and communication technology.展开更多
Reconfigurable intelligent surface(RIS)is more likely to develop into extremely large-scale RIS(XL-RIS)to efficiently boost the system capacity for future 6 G communications.Beam training is an effective way to acquir...Reconfigurable intelligent surface(RIS)is more likely to develop into extremely large-scale RIS(XL-RIS)to efficiently boost the system capacity for future 6 G communications.Beam training is an effective way to acquire channel state information(CSI)for XL-RIS.Existing beam training schemes rely on the far-field codebook.However,due to the large aperture of XL-RIS,the scatters are more likely to be in the near-field region of XL-RIS.The far-field codebook mismatches the near-field channel model.Thus,the existing far-field beam training scheme will cause severe performance loss in the XL-RIS assisted nearfield communications.To solve this problem,we propose the efficient near-field beam training schemes by designing the near-field codebook to match the nearfield channel model.Specifically,we firstly design the near-field codebook by considering the near-field cascaded array steering vector of XL-RIS.Then,the optimal codeword for XL-RIS is obtained by the exhausted training procedure.To reduce the beam training overhead,we further design a hierarchical nearfield codebook and propose the corresponding hierarchical near-field beam training scheme,where different levels of sub-codebooks are searched in turn with reduced codebook size.Simulation results show the proposed near-field beam training schemes outperform the existing far-field beam training scheme.展开更多
Terahertz(THz)communication is considered to be a promising technology for future 6G network.To overcome the severe attenuation and relieve the high power consumption,massive multipleinput multiple-output(MIMO)with hy...Terahertz(THz)communication is considered to be a promising technology for future 6G network.To overcome the severe attenuation and relieve the high power consumption,massive multipleinput multiple-output(MIMO)with hybrid precoding has been widely considered for THz communication.However,accurate wideband channel estimation,which is essential for hybrid precoding,is challenging in THz massive MIMO systems.The existing wideband channel estimation schemes based on the ideal assumption of common sparse channel support will suffer from a severe performance loss due to the beam split effect.In this paper,we propose a beam split pattern detection based channel estimation scheme to realize reliable wideband channel estimation in THz massive MIMO systems.Specifically,a comprehensive analysis on the angle-domain sparse structure of the wideband channel is provided by considering the beam split effect.Based on the analysis,we define a series of index sets called as beam split patterns,which are proved to have a one-to-one match to different physical channel directions.Inspired by this one-to-one match,we propose to estimate the physical channel direction by exploiting beam split patterns at first.Then,the sparse channel supports at different subcarriers can be obtained by utilizing a support detection window.This support detection window is generated by expanding the beam split pattern which is determined by the obtained physical channel direction.The above estimation procedure will be repeated path by path until all path components are estimated.Finally,the wideband channel can be recovered by calculating the elements on the total sparse channel support at all subcarriers.The proposed scheme exploits the wideband channel property implied by the beam split effect,i.e.,beam split pattern,which can significantly improve the channel estimation accuracy.Simulation results show that the proposed scheme is able to achieve higher accuracy than existing schemes.展开更多
With the proliferation of end devices, such as smart?phones, wearable sensors and drones, an enor?mous amount of data is generated at the networkedge. This motivates the deployment of machine learning algorithms at th...With the proliferation of end devices, such as smart?phones, wearable sensors and drones, an enor?mous amount of data is generated at the networkedge. This motivates the deployment of machine learning algorithms at the edge that exploit the data to train ar?tificial intelligence (AI) models for making intelligent deci?sions. Traditional machine learning procedures, including both training and inference, are carried out in a centralized da?ta center, thus requiring devices to upload their raw data to the center.展开更多
Images are generally corrupted by impulse noise during acquisition and transmission.Noise deteriorates the quality of images.To remove corruption noise,we propose a hybrid approach to restoring a random noisecorrupted...Images are generally corrupted by impulse noise during acquisition and transmission.Noise deteriorates the quality of images.To remove corruption noise,we propose a hybrid approach to restoring a random noisecorrupted image,including a block matching 3D(BM3D)method,an adaptive non-local mean(ANLM)scheme,and the K-singular value decomposition(K-SVD)algorithm.In the proposed method,we employ the morphological component analysis(MCA)to decompose an image into the texture,structure,and edge parts.Then,the BM3D method,ANLM scheme,and K-SVD algorithm are utilized to eliminate noise in the texture,structure,and edge parts of the image,respectively.Experimental results show that the proposed approach can effectively remove interference random noise in different parts;meanwhile,the deteriorated image is able to be reconstructed well.展开更多
This paper proposes a Reinforcement learning(RL)algorithm to find an optimal scheduling policy to minimize the delay for a given energy constraint in communication system where the environments such as traffic arrival...This paper proposes a Reinforcement learning(RL)algorithm to find an optimal scheduling policy to minimize the delay for a given energy constraint in communication system where the environments such as traffic arrival rates are not known in advance and can change over time.For this purpose,this problem is formulated as an infinite-horizon Constrained Markov Decision Process(CMDP).To handle the constrained optimization problem,we first adopt the Lagrangian relaxation technique to solve it.Then,we propose a variant of Q-learning,Q-greedyUCB that combinesε-greedy and Upper Confidence Bound(UCB)algorithms to solve this constrained MDP problem.We mathematically prove that the Q-greedyUCB algorithm converges to an optimal solution.Simulation results also show that Q-greedyUCB finds an optimal scheduling strategy,and is more efficient than Q-learning withε-greedy,R-learning and the Averagepayoff RL(ARL)algorithm in terms of the cumulative regret.We also show that our algorithm can learn and adapt to the changes of the environment,so as to obtain an optimal scheduling strategy under a given power constraint for the new environment.展开更多
With the rapid development of marine activities,there has been an increasing use of Internet-of-Things(IoT) devices for maritime applications.This leads to a growing demand for high-speed and ultra-reliable maritime c...With the rapid development of marine activities,there has been an increasing use of Internet-of-Things(IoT) devices for maritime applications.This leads to a growing demand for high-speed and ultra-reliable maritime communications.Current maritime communication networks (MCNs) mainly rely on satellites and on-shore base stations (BSs).The former generally provides limited transmission rate while the latter lacks wide-area coverage capability.As a result,the development of current MCN lags far behind the terrestrial fifth-generation (5G) network.展开更多
Reversible data hiding(RDH)is a method to embed messages into an image that human eyes are difficult to recognize the differences between the original image and the embedded image.The method needs to make sure that th...Reversible data hiding(RDH)is a method to embed messages into an image that human eyes are difficult to recognize the differences between the original image and the embedded image.The method needs to make sure that the original image and the embedded information can be exactly recovered.The prediction-error expansion(PEE)is a successful way to realize RDH.However,it is fixed when pairing the conventional twodimensional prediction-error histogram(2D-PEH).So,the embedding capacity(EC)and embedding distortion(ED)are not satisfactory.In this study,we propose a method called greedy pairing prediction-error expansion(GPPEE)based on pairwise RDH and demonstrate GPPEE can achieve a more efficient embedding goal and reduce ED.展开更多
文摘N-soliton (N>2) interaction in optical fibers including third-order dispersion is simulated numerically.In equal amplitude soliton transmission,the coalescence resulted from the mutual interaction among N solitons still exists,while in the unequal case,soliton interaction can not be removed but becomes more serious due to the effect of third-order dispersion.Therefore,we can not consider third-order dispersion as an utilizable factor for removing soliton interaction.
基金the National Key R&D Program of China under Grants No.2017YFA0303704 and No.2018YFB2200400Natural Science Foundation of Beijing under Grant No.Z180012National Natural Science Foundation of China under Grants No.61875101 and No.91750206.
文摘Dispersive optics quantum key distribution(DO-QKD)based on energy-time entangled photon pairs is an important QKD scheme.In DO-QKD,the arrival time of photons is used in key generation and security analysis,which would be greatly affected by fiber dispersion.In this work,we establish a theoretical model of the entanglement-based DO-QKD system,considering the protocol,physical processes(such as fiber transmission and single-photon detection),and the analysis of security tests.Based on this theoretical model,we investigate the influence of chromatic dispersion introduced by transmission fibers on the performance of DO-QKD.By analyzing the benefits and costs of dispersion compensation,the system performance under G.652 and G.655 optical fibers are shown,respectively.The results show that dispersion compensation is unnecessary for DO-QKD systems in campus networks and even metro networks.Whereas,it is still required in DO-QKD systems with longer fiber transmission distances.
基金supported by the Ming Chuan University Internal Research Fund
文摘A quasi resonant pulse width modulation（PWM） inverter is used in a solar power system to convert the solar panel and battery charger＇s direct current（DC） output to alternating current（AC）.Although much has been published about DC to AC PWM inverters,none of the previous work has shown modeling and simulation results for DC to AC inverters.In this study,we suggest a new topology for a quasi resonant PWM inverter.Experimental results are also presented.
基金supported by the National Key Research and Development Program of China under Grant No.2017YFA0303704National Natural Science Foundation of China under Grants No.61575102,No.61671438,No.61875101,and No.61621064+1 种基金Beijing Natural Science Foundation under Grant No.Z180012Beijing Academy of Quantum Information Sciences under Grant No.Y18G26
文摘For a compact quantum key distribution (QKD) sender for the polarization encoding BB84 protocol, an eavesdropper could take a side-channel attack by measuring the spatial information of photons to infer their polarizations. The possibility of this attack can be reduced by introducing an aperture in the QKD sender, however, the effect of the aperture on the QKD security lacks of quantitative analysis. In this paper, we analyze the mutual information between the actual keys encoded at this QKD sender and the inferred keys at the eavesdropper (Eve), demonstrating the effect of the aperture to eliminate the spatial side-channel information quantitatively. It shows that Eve’s potential on eavesdropping spatial side-channel information is totally dependent on the optical design of the QKD sender, including the source arrangement and the aperture. The height of compact QKD senders with integrated light-emitting diode (LED) arrays could be controlled under several millimeters, showing great potential on applications in portable equipment.
文摘Abstract--With the development of clean energy, switching and distribution issues in a photovoltaic system are getting much attention in recent years. This paper designs a DC to AC inverter and power switching and distribution system between a solar power system and the municipal system by using the Darlington amplifier structure with the photosensitive resistor and accompanying relays, and details the system circuits. The proposed system can achieve a stable output of IIOV AC, as well as self-generating driving voltage and switching between the municipal electrical system and the solar power system. The mathematic analysis and actually test results demonstrate that the proposed method is an easy, inexpensive, and low cost way to build a solar power switching and distribution system.
基金support from National Natural Science Foundation of China (Grant No. 61622110)
文摘With the rapid development of smart devices and mobile networks,multimedia services will dominate most of data traffic in 4G/5G networks.Applications -such as conversational videos,online multimedia sharing,remote education,etc.have gained their popularity and will become more ubiquitous among customers.Tra-
文摘This study uses the smart phone with the Android system to construct a cloud-side smart switch system in the client-server architecture with the Android open platform system, using microprocessors(MCU 16F690) as the thermostat controller and combined with Raspberry Pi. The computing technology extends the control of the constant temperature from the local to the cloud, allowing the user to view the temperature status recorded by the cloud server using the smart phone application(App) or web browser. It can even remotely control the heating power of the smart switch for the heating device in the Internet control environment and use the proportional-integral-derivative(PID) control and the pulse-width modulation(PWM) technology to achieve intelligent constant temperature control.The proposed control system uses the expert PID control as the core to calculate the duty cycle of the PWM signal to control the power output of the smart switch for the constant temperature water tank. The experiment results verify the effectiveness of the proposed system.
基金supported in part by the National Key R&D Project of China under Grant 2020YFA0712300National Natural Science Foundation of China under Grant NSFC-62231022,12031011supported in part by the NSF of China under Grant 62125108。
文摘We consider an image semantic communication system in a time-varying fading Gaussian MIMO channel,with a finite number of channel states.A deep learning-aided broadcast approach scheme is proposed to benefit the adaptive semantic transmission in terms of different channel states.We combine the classic broadcast approach with the image transformer to implement this adaptive joint source and channel coding(JSCC)scheme.Specifically,we utilize the neural network(NN)to jointly optimize the hierarchical image compression and superposition code mapping within this scheme.The learned transformers and codebooks allow recovering of the image with an adaptive quality and low error rate at the receiver side,in each channel state.The simulation results exhibit our proposed scheme can dynamically adapt the coding to the current channel state and outperform some existing intelligent schemes with the fixed coding block.
基金supported in part by the National Key Research and Development Program of China(Grant No.2020YFB1805005)in part by the National Natural Science Foundation of China(Grant No.62031019)in part by the European Commission through the H2020-MSCA-ITN META WIRELESS Research Project under Grant 956256。
文摘Channel prediction is critical to address the channel aging issue in mobile scenarios.Existing channel prediction techniques are mainly designed for discrete channel prediction,which can only predict the future channel in a fixed time slot per frame,while the other intra-frame channels are usually recovered by interpolation.However,these approaches suffer from a serious interpolation loss,especially for mobile millimeter-wave communications.To solve this challenging problem,we propose a tensor neural ordinary differential equation(TN-ODE)based continuous-time channel prediction scheme to realize the direct prediction of intra-frame channels.Specifically,inspired by the recently developed continuous mapping model named neural ODE in the field of machine learning,we first utilize the neural ODE model to predict future continuous-time channels.To improve the channel prediction accuracy and reduce computational complexity,we then propose the TN-ODE scheme to learn the structural characteristics of the high-dimensional channel by low-dimensional learnable transform.Simulation results show that the proposed scheme is able to achieve higher intra-frame channel prediction accuracy than existing schemes.
文摘IEEE International Conference on Communication Technology(ICCT)was jointly initiated and organized by IEEE Beijing Section and IEEE Com Soc in 1986.It is one of the highest-level academic events in the field of communication technology in China.It is also an international gathering for research for information and communication technology.
基金supported in part by the National Key Research and Development Program of China(Grant No.2020YFB1807205)in part by the National Natural Science Foundation of China(Grant No.62031019)in part by the European Commission through the H2020-MSCA-ITN META WIRELESS Research Project under Grant 956256。
文摘Reconfigurable intelligent surface(RIS)is more likely to develop into extremely large-scale RIS(XL-RIS)to efficiently boost the system capacity for future 6 G communications.Beam training is an effective way to acquire channel state information(CSI)for XL-RIS.Existing beam training schemes rely on the far-field codebook.However,due to the large aperture of XL-RIS,the scatters are more likely to be in the near-field region of XL-RIS.The far-field codebook mismatches the near-field channel model.Thus,the existing far-field beam training scheme will cause severe performance loss in the XL-RIS assisted nearfield communications.To solve this problem,we propose the efficient near-field beam training schemes by designing the near-field codebook to match the nearfield channel model.Specifically,we firstly design the near-field codebook by considering the near-field cascaded array steering vector of XL-RIS.Then,the optimal codeword for XL-RIS is obtained by the exhausted training procedure.To reduce the beam training overhead,we further design a hierarchical nearfield codebook and propose the corresponding hierarchical near-field beam training scheme,where different levels of sub-codebooks are searched in turn with reduced codebook size.Simulation results show the proposed near-field beam training schemes outperform the existing far-field beam training scheme.
基金supported in part by the National Key Research and Development Program of China(Grant No.2020YFB1805005)the National Natural Science Foundation of China(Grant No.62031019)the European Commission through the H2020-MSCA-ITN META WIRELESS Research Project under Grant 956256.
文摘Terahertz(THz)communication is considered to be a promising technology for future 6G network.To overcome the severe attenuation and relieve the high power consumption,massive multipleinput multiple-output(MIMO)with hybrid precoding has been widely considered for THz communication.However,accurate wideband channel estimation,which is essential for hybrid precoding,is challenging in THz massive MIMO systems.The existing wideband channel estimation schemes based on the ideal assumption of common sparse channel support will suffer from a severe performance loss due to the beam split effect.In this paper,we propose a beam split pattern detection based channel estimation scheme to realize reliable wideband channel estimation in THz massive MIMO systems.Specifically,a comprehensive analysis on the angle-domain sparse structure of the wideband channel is provided by considering the beam split effect.Based on the analysis,we define a series of index sets called as beam split patterns,which are proved to have a one-to-one match to different physical channel directions.Inspired by this one-to-one match,we propose to estimate the physical channel direction by exploiting beam split patterns at first.Then,the sparse channel supports at different subcarriers can be obtained by utilizing a support detection window.This support detection window is generated by expanding the beam split pattern which is determined by the obtained physical channel direction.The above estimation procedure will be repeated path by path until all path components are estimated.Finally,the wideband channel can be recovered by calculating the elements on the total sparse channel support at all subcarriers.The proposed scheme exploits the wideband channel property implied by the beam split effect,i.e.,beam split pattern,which can significantly improve the channel estimation accuracy.Simulation results show that the proposed scheme is able to achieve higher accuracy than existing schemes.
文摘With the proliferation of end devices, such as smart?phones, wearable sensors and drones, an enor?mous amount of data is generated at the networkedge. This motivates the deployment of machine learning algorithms at the edge that exploit the data to train ar?tificial intelligence (AI) models for making intelligent deci?sions. Traditional machine learning procedures, including both training and inference, are carried out in a centralized da?ta center, thus requiring devices to upload their raw data to the center.
基金supported by MOST under Grant No.104-2221-E-468-007
文摘Images are generally corrupted by impulse noise during acquisition and transmission.Noise deteriorates the quality of images.To remove corruption noise,we propose a hybrid approach to restoring a random noisecorrupted image,including a block matching 3D(BM3D)method,an adaptive non-local mean(ANLM)scheme,and the K-singular value decomposition(K-SVD)algorithm.In the proposed method,we employ the morphological component analysis(MCA)to decompose an image into the texture,structure,and edge parts.Then,the BM3D method,ANLM scheme,and K-SVD algorithm are utilized to eliminate noise in the texture,structure,and edge parts of the image,respectively.Experimental results show that the proposed approach can effectively remove interference random noise in different parts;meanwhile,the deteriorated image is able to be reconstructed well.
基金This work was supported by the research fund of Hanyang University(HY-2019-N)This work was supported by the National Key Research&Development Program 2018YFA0701601.
文摘This paper proposes a Reinforcement learning(RL)algorithm to find an optimal scheduling policy to minimize the delay for a given energy constraint in communication system where the environments such as traffic arrival rates are not known in advance and can change over time.For this purpose,this problem is formulated as an infinite-horizon Constrained Markov Decision Process(CMDP).To handle the constrained optimization problem,we first adopt the Lagrangian relaxation technique to solve it.Then,we propose a variant of Q-learning,Q-greedyUCB that combinesε-greedy and Upper Confidence Bound(UCB)algorithms to solve this constrained MDP problem.We mathematically prove that the Q-greedyUCB algorithm converges to an optimal solution.Simulation results also show that Q-greedyUCB finds an optimal scheduling strategy,and is more efficient than Q-learning withε-greedy,R-learning and the Averagepayoff RL(ARL)algorithm in terms of the cumulative regret.We also show that our algorithm can learn and adapt to the changes of the environment,so as to obtain an optimal scheduling strategy under a given power constraint for the new environment.
文摘With the rapid development of marine activities,there has been an increasing use of Internet-of-Things(IoT) devices for maritime applications.This leads to a growing demand for high-speed and ultra-reliable maritime communications.Current maritime communication networks (MCNs) mainly rely on satellites and on-shore base stations (BSs).The former generally provides limited transmission rate while the latter lacks wide-area coverage capability.As a result,the development of current MCN lags far behind the terrestrial fifth-generation (5G) network.
基金supported by MOST under Grants No.107-2221-E-845-002-MY3 and No.110-2221-E-845-002-。
文摘Reversible data hiding(RDH)is a method to embed messages into an image that human eyes are difficult to recognize the differences between the original image and the embedded image.The method needs to make sure that the original image and the embedded information can be exactly recovered.The prediction-error expansion(PEE)is a successful way to realize RDH.However,it is fixed when pairing the conventional twodimensional prediction-error histogram(2D-PEH).So,the embedding capacity(EC)and embedding distortion(ED)are not satisfactory.In this study,we propose a method called greedy pairing prediction-error expansion(GPPEE)based on pairwise RDH and demonstrate GPPEE can achieve a more efficient embedding goal and reduce ED.
