Rate-splitting multiple access(RSMA)can cope with a wide range of propagation conditions in multigroup multicast communications through rate splitting optimization.To breakthrough the grouprate limited bottleneck,reco...Rate-splitting multiple access(RSMA)can cope with a wide range of propagation conditions in multigroup multicast communications through rate splitting optimization.To breakthrough the grouprate limited bottleneck,reconfigurable intelligent surface(RIS)technique can be introduced to assist wireless communications through enhancing the channel quality.In RIS-aided RSMA multigroup multicasting,how to provide fair and high-quality multiuser service under power and spectrum constraints is essential.In this paper,we propose a max-min fair RIS-aided rate-splitting multiple access(MMF-RISRSMA)scheme for multigroup multicast communications,where the rate fairness is obtained by maximizing the minimum group-rate.In doing so,we jointly optimize the beamformers,the rate splitting vector at the transmitter,as well as the phase shifts at RIS.To solve it,we divide the original optimization problem into two subproblems and alternately optimize the variables.The beamforming and rate splitting optimization subproblem is solved by using the successive convex approximation technique.The phase shift optimization subproblem is solved through the penalty function method to achieve a rank-one locally optimal solution.Simulations demonstrate that the proposed MMF-RIS-RSMA scheme can obtain significant performance gain in terms of the minimum group-rate.展开更多
Recently,there have been several uses for digital image processing.Image fusion has become a prominent application in the domain of imaging processing.To create one final image that provesmore informative and helpful ...Recently,there have been several uses for digital image processing.Image fusion has become a prominent application in the domain of imaging processing.To create one final image that provesmore informative and helpful compared to the original input images,image fusion merges two or more initial images of the same item.Image fusion aims to produce,enhance,and transform significant elements of the source images into combined images for the sake of human visual perception.Image fusion is commonly employed for feature extraction in smart robots,clinical imaging,audiovisual camera integration,manufacturing process monitoring,electronic circuit design,advanced device diagnostics,and intelligent assembly line robots,with image quality varying depending on application.The research paper presents various methods for merging images in spatial and frequency domains,including a blend of stable and curvelet transformations,everageMax-Min,weighted principal component analysis(PCA),HIS(Hue,Intensity,Saturation),wavelet transform,discrete cosine transform(DCT),dual-tree Complex Wavelet Transform(CWT),and multiple wavelet transform.Image fusion methods integrate data from several source images of an identical target,thereby enhancing information in an extremely efficient manner.More precisely,in imaging techniques,the depth of field constraint precludes images from focusing on every object,leading to the exclusion of certain characteristics.To tackle thess challanges,a very efficient multi-focus wavelet decomposition and recompositionmethod is proposed.The use of these wavelet decomposition and recomposition techniques enables this method to make use of existing optimized wavelet code and filter choice.The simulated outcomes provide evidence that the suggested approach initially extracts particular characteristics from images in order to accurately reflect the level of clarity portrayed in the original images.This study enhances the performance of the eXtreme Gradient Boosting(XGBoost)algorithm in detecting brain malignancies with greater precision through the integration of computational image analysis and feature selection.The performance of images is improved by segmenting them employing the K-Means algorithm.The segmentation method aids in identifying specific regions of interest,using Particle Swarm Optimization(PCA)for trait selection and XGBoost for data classification.Extensive trials confirm the model’s exceptional visual performance,achieving an accuracy of up to 97.067%and providing good objective indicators.展开更多
As a revolutionary hardware technology that can reconfigure the propagation environment,reconfigurable intelligent surfaces(RISs)have been regarded as a promising solution to enhance wireless networks.In this paper,we...As a revolutionary hardware technology that can reconfigure the propagation environment,reconfigurable intelligent surfaces(RISs)have been regarded as a promising solution to enhance wireless networks.In this paper,we consider a multiuser multiple-input single-output(MISO)wireless power transfer(WPT)system,which is assisted by several RISs.In order to improve energy efficiency and reduce hardware cost,we consider that the energy transmitter(ET)in the WPT system is equipped with a constant-envelope analog beamformer,instead of a digital beamformer.Focusing on user fairness,we study a minimum received power maximization problem by jointly optimizing the ET beamforming and the RIS phase shifts,subject to the constant-envelope constraints.We iteratively solve this non-convex maxmin problem by leveraging both the successive convex approximation(SCA)method and the alternating direction method of multipliers(ADMM)algorithm.Numerical results demonstrate the effectiveness of the proposed algorithm and show attractive performance gain brought by RISs.展开更多
Resource allocation is crucial for satellite networks. In this paper, we propose a multi-resource fair allocation scheme, namely Dominant and Max-min Fair(DMMF), to efficiently and fairly allocate resources. It consis...Resource allocation is crucial for satellite networks. In this paper, we propose a multi-resource fair allocation scheme, namely Dominant and Max-min Fair(DMMF), to efficiently and fairly allocate resources. It consists of two allocation stages, dominant resource fair(DRF) allocation stage and max-min fairness(MMF) allocation stage. The proposed DMMF scheme exhibits desirable properties, including share incentive, strategy proofness, envy freeness and Pareto optimality. Meanwhile, DMMF can improve the allocation efficiency and reach 100% allocation efficiency.展开更多
This paper investigates the resource scheduling for heterogeneous vehicular networks, where some moving vehicles are selected and scheduled as helping relays to assist information transmission between the roadside inf...This paper investigates the resource scheduling for heterogeneous vehicular networks, where some moving vehicles are selected and scheduled as helping relays to assist information transmission between the roadside infrastructure and other moving vehicles. For such a system, we propose a mobile-service based max-min fairness resource scheduling scheme, where service amount which is more suitable for high mobility scenarios is adopted to characterize the information transmission capacity of the links and the max-min criteria is adopted to meet the fairness requirement of the moving vehicles. Simulation results demonstrate the effectiveness of our proposed scheme. It is shown that our proposed scheme archives higher throughput and better fairness compared with random scheduling scheme and non-relaying scheme.展开更多
目的利用免疫缺陷的NOD-Scid小鼠建立播散性弥漫大B细胞淋巴瘤(diffuse large B-cell lymphoma,DLBCL)小鼠模型,为动物模型的构建提供新思路。方法先将人源DLBCL细胞OCI-Ly8导入荧光素酶基因,使其长期稳定表达荧光素酶。再将OCI-Ly8-luc...目的利用免疫缺陷的NOD-Scid小鼠建立播散性弥漫大B细胞淋巴瘤(diffuse large B-cell lymphoma,DLBCL)小鼠模型,为动物模型的构建提供新思路。方法先将人源DLBCL细胞OCI-Ly8导入荧光素酶基因,使其长期稳定表达荧光素酶。再将OCI-Ly8-luc^(+)细胞经尾静脉注射到NOD-Scid小鼠体内,利用生物发光成像系统每隔3天观察1次小鼠体内肿瘤细胞播散情况。结果实验第7天监测到OCI-Ly8-luc^(+)细胞在小鼠体内发生播散,并且进展迅速,20天时出现小鼠死亡。结论利用OCI-Ly8-luc^(+)细胞尾静脉注射成功构建了NOD-Scid小鼠DLBCL模型,为DLBCL的动物模型构建提供新方法。展开更多
基金supported in part by the Project of International Cooperation and Exchanges NSFC under Grant No.61860206005in part by the National Natural Science Foundation of China under Grant No.62201329,No.62171262in part by Shandong Provincial Natural Science Foundation under Grant ZR2021YQ47。
文摘Rate-splitting multiple access(RSMA)can cope with a wide range of propagation conditions in multigroup multicast communications through rate splitting optimization.To breakthrough the grouprate limited bottleneck,reconfigurable intelligent surface(RIS)technique can be introduced to assist wireless communications through enhancing the channel quality.In RIS-aided RSMA multigroup multicasting,how to provide fair and high-quality multiuser service under power and spectrum constraints is essential.In this paper,we propose a max-min fair RIS-aided rate-splitting multiple access(MMF-RISRSMA)scheme for multigroup multicast communications,where the rate fairness is obtained by maximizing the minimum group-rate.In doing so,we jointly optimize the beamformers,the rate splitting vector at the transmitter,as well as the phase shifts at RIS.To solve it,we divide the original optimization problem into two subproblems and alternately optimize the variables.The beamforming and rate splitting optimization subproblem is solved by using the successive convex approximation technique.The phase shift optimization subproblem is solved through the penalty function method to achieve a rank-one locally optimal solution.Simulations demonstrate that the proposed MMF-RIS-RSMA scheme can obtain significant performance gain in terms of the minimum group-rate.
基金Princess Nourah bint Abdulrahman University and Researchers Supporting Project Number(PNURSP2024R346)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Recently,there have been several uses for digital image processing.Image fusion has become a prominent application in the domain of imaging processing.To create one final image that provesmore informative and helpful compared to the original input images,image fusion merges two or more initial images of the same item.Image fusion aims to produce,enhance,and transform significant elements of the source images into combined images for the sake of human visual perception.Image fusion is commonly employed for feature extraction in smart robots,clinical imaging,audiovisual camera integration,manufacturing process monitoring,electronic circuit design,advanced device diagnostics,and intelligent assembly line robots,with image quality varying depending on application.The research paper presents various methods for merging images in spatial and frequency domains,including a blend of stable and curvelet transformations,everageMax-Min,weighted principal component analysis(PCA),HIS(Hue,Intensity,Saturation),wavelet transform,discrete cosine transform(DCT),dual-tree Complex Wavelet Transform(CWT),and multiple wavelet transform.Image fusion methods integrate data from several source images of an identical target,thereby enhancing information in an extremely efficient manner.More precisely,in imaging techniques,the depth of field constraint precludes images from focusing on every object,leading to the exclusion of certain characteristics.To tackle thess challanges,a very efficient multi-focus wavelet decomposition and recompositionmethod is proposed.The use of these wavelet decomposition and recomposition techniques enables this method to make use of existing optimized wavelet code and filter choice.The simulated outcomes provide evidence that the suggested approach initially extracts particular characteristics from images in order to accurately reflect the level of clarity portrayed in the original images.This study enhances the performance of the eXtreme Gradient Boosting(XGBoost)algorithm in detecting brain malignancies with greater precision through the integration of computational image analysis and feature selection.The performance of images is improved by segmenting them employing the K-Means algorithm.The segmentation method aids in identifying specific regions of interest,using Particle Swarm Optimization(PCA)for trait selection and XGBoost for data classification.Extensive trials confirm the model’s exceptional visual performance,achieving an accuracy of up to 97.067%and providing good objective indicators.
基金supported by General Program of National Natural Science Foundation of China(No.62071090)Sichuan Science and Technology Program(No.2021YFH0014).
文摘As a revolutionary hardware technology that can reconfigure the propagation environment,reconfigurable intelligent surfaces(RISs)have been regarded as a promising solution to enhance wireless networks.In this paper,we consider a multiuser multiple-input single-output(MISO)wireless power transfer(WPT)system,which is assisted by several RISs.In order to improve energy efficiency and reduce hardware cost,we consider that the energy transmitter(ET)in the WPT system is equipped with a constant-envelope analog beamformer,instead of a digital beamformer.Focusing on user fairness,we study a minimum received power maximization problem by jointly optimizing the ET beamforming and the RIS phase shifts,subject to the constant-envelope constraints.We iteratively solve this non-convex maxmin problem by leveraging both the successive convex approximation(SCA)method and the alternating direction method of multipliers(ADMM)algorithm.Numerical results demonstrate the effectiveness of the proposed algorithm and show attractive performance gain brought by RISs.
基金supported by the National High-Tech R&D Program (863 Program) No. 2015AA01A705the National Natural Science Foundation of China under Grant No. 61572072+1 种基金the National Science and Technology Major Project No. 2015ZX03001041Fundamental Research Funds for the Central Universities "Research on the System of Personalized Education using Big Data"
文摘Resource allocation is crucial for satellite networks. In this paper, we propose a multi-resource fair allocation scheme, namely Dominant and Max-min Fair(DMMF), to efficiently and fairly allocate resources. It consists of two allocation stages, dominant resource fair(DRF) allocation stage and max-min fairness(MMF) allocation stage. The proposed DMMF scheme exhibits desirable properties, including share incentive, strategy proofness, envy freeness and Pareto optimality. Meanwhile, DMMF can improve the allocation efficiency and reach 100% allocation efficiency.
基金supported by the Chinese Postdoctoral Science Foundation No. 2015M570937the Open Research Fund of National Mobile Communications Research Laboratory,Southeast University No. 2014D03+2 种基金the National High-Tech R&D Program(863 Program) No.2015AA010301the National Natural Science Foundation of Chinaunder Grant No.61572072the Fundamental Research Funds for the Central Universities "Research on the System of Personalized Education using Big Data"
文摘This paper investigates the resource scheduling for heterogeneous vehicular networks, where some moving vehicles are selected and scheduled as helping relays to assist information transmission between the roadside infrastructure and other moving vehicles. For such a system, we propose a mobile-service based max-min fairness resource scheduling scheme, where service amount which is more suitable for high mobility scenarios is adopted to characterize the information transmission capacity of the links and the max-min criteria is adopted to meet the fairness requirement of the moving vehicles. Simulation results demonstrate the effectiveness of our proposed scheme. It is shown that our proposed scheme archives higher throughput and better fairness compared with random scheduling scheme and non-relaying scheme.
文摘目的利用免疫缺陷的NOD-Scid小鼠建立播散性弥漫大B细胞淋巴瘤(diffuse large B-cell lymphoma,DLBCL)小鼠模型,为动物模型的构建提供新思路。方法先将人源DLBCL细胞OCI-Ly8导入荧光素酶基因,使其长期稳定表达荧光素酶。再将OCI-Ly8-luc^(+)细胞经尾静脉注射到NOD-Scid小鼠体内,利用生物发光成像系统每隔3天观察1次小鼠体内肿瘤细胞播散情况。结果实验第7天监测到OCI-Ly8-luc^(+)细胞在小鼠体内发生播散,并且进展迅速,20天时出现小鼠死亡。结论利用OCI-Ly8-luc^(+)细胞尾静脉注射成功构建了NOD-Scid小鼠DLBCL模型,为DLBCL的动物模型构建提供新方法。
