Wireless communication-enabled Cooperative Adaptive Cruise Control(CACC)is expected to improve the safety and traffic capacity of vehicle platoons.Existing CACC considers a conventional communication delay with fixed ...Wireless communication-enabled Cooperative Adaptive Cruise Control(CACC)is expected to improve the safety and traffic capacity of vehicle platoons.Existing CACC considers a conventional communication delay with fixed Vehicular Communication Network(VCN)topologies.However,when the network is under attack,the communication delay may be much higher,and the stability of the system may not be guaranteed.This paper proposes a novel communication Delay Aware CACC with Dynamic Network Topologies(DADNT).The main idea is that for various communication delays,in order to maximize the traffic capacity while guaranteeing stability and minimizing the following error,the CACC should dynamically adjust the VCN network topology to achieve the minimum inter-vehicle spacing.To this end,a multi-objective optimization problem is formulated,and a 3-step Divide-And-Conquer sub-optimal solution(3DAC)is proposed.Simulation results show that with 3DAC,the proposed DADNT with CACC can reduce the inter-vehicle spacing by 5%,10%,and 14%,respectively,compared with the traditional CACC with fixed one-vehicle,two-vehicle,and three-vehicle look-ahead network topologies,thereby improving the traffic efficiency.展开更多
With the proliferation of the Internet of Things(IoT),various services are emerging with totally different features and requirements,which cannot be supported by the current fifth generation of mobile cellular network...With the proliferation of the Internet of Things(IoT),various services are emerging with totally different features and requirements,which cannot be supported by the current fifth generation of mobile cellular networks(5G).The future sixth generation of mobile cellular networks(6G)is expected to have the capability to support new and unknown services with changing requirements.Hence,in addition to enhancing its capability by 10–100 times compared with 5G,6G should also be intelligent and open to adapt to the ever-changing services in the IoT,which requires a convergence of Communication,Computing and Caching(3C).Based on the analysis of the requirements of new services for 6G,this paper identifies key enabling technologies for an intelligent and open 6G network,all featured with 3C convergence.These technologies cover fundamental and emerging topics,including 3C-based spectrum management,radio channel construction,delay-aware transmission,wireless distributed computing,and network self-evolution.From the detailed analysis of these 3C-based technologies presented in this paper,we can see that although they are promising to enable an intelligent and open 6G,more efforts are needed to realize the expected 6G network.展开更多
In this article,the secure computation efficiency(SCE)problem is studied in a massive multipleinput multiple-output(mMIMO)-assisted mobile edge computing(MEC)network.We first derive the secure transmission rate based ...In this article,the secure computation efficiency(SCE)problem is studied in a massive multipleinput multiple-output(mMIMO)-assisted mobile edge computing(MEC)network.We first derive the secure transmission rate based on the mMIMO under imperfect channel state information.Based on this,the SCE maximization problem is formulated by jointly optimizing the local computation frequency,the offloading time,the downloading time,the users and the base station transmit power.Due to its difficulty to directly solve the formulated problem,we first transform the fractional objective function into the subtractive form one via the dinkelbach method.Next,the original problem is transformed into a convex one by applying the successive convex approximation technique,and an iteration algorithm is proposed to obtain the solutions.Finally,the stimulations are conducted to show that the performance of the proposed schemes is superior to that of the other schemes.展开更多
Novel centralized base station architectures integrating computation and communication functionalities have become important for the development of future mobile communication networks.Therefore,the development of dyn...Novel centralized base station architectures integrating computation and communication functionalities have become important for the development of future mobile communication networks.Therefore,the development of dynamic high-speed interconnections between baseband units(BBUs)and remote radio heads(RRHs)is vital in centralized base station design.Herein,dynamic high-speed switches(HSSs)connecting BBUs and RRHs were designed for a centralized base station architecture.We analyzed the characteristics of actual traffic and introduced a switch traffic model suitable for the super base station architecture.Then,we proposed a data-priority-aware(DPA)scheduling algorithm based on the traffic model.Lastly,we developed the dynamic HSS model based on the OPNET platform and the prototype based on FPGA.Our results show that the DPA achieves close to 100%throughput with lower latency and provides better run-time complexity than iOCF and HE-iSLIP,thereby demonstrating that the proposed switch system can be adopted in centralized base station architectures.展开更多
A Taylor series expansion(TSE) based design for minimum mean-square error(MMSE) and QR decomposition(QRD) of multi-input and multi-output(MIMO) systems is proposed based on application specific instruction set process...A Taylor series expansion(TSE) based design for minimum mean-square error(MMSE) and QR decomposition(QRD) of multi-input and multi-output(MIMO) systems is proposed based on application specific instruction set processor(ASIP), which uses TSE algorithm instead of resource-consuming reciprocal and reciprocal square root(RSR) operations.The aim is to give a high performance implementation for MMSE and QRD in one programmable platform simultaneously.Furthermore, instruction set architecture(ISA) and the allocation of data paths in single instruction multiple data-very long instruction word(SIMD-VLIW) architecture are provided, offering more data parallelism and instruction parallelism for different dimension matrices and operation types.Meanwhile, multiple level numerical precision can be achieved with flexible table size and expansion order in TSE ISA.The ASIP has been implemented to a 28 nm CMOS process and frequency reaches 800 MHz.Experimental results show that the proposed design provides perfect numerical precision within the fixed bit-width of the ASIP, higher matrix processing rate better than the requirements of 5G system and more rate-area efficiency comparable with ASIC implementations.展开更多
The centralized radio access cellular network infrastructure based on centralized Super Base Station(CSBS) is a promising solution to reduce the high construction cost and energy consumption of conventional cellular n...The centralized radio access cellular network infrastructure based on centralized Super Base Station(CSBS) is a promising solution to reduce the high construction cost and energy consumption of conventional cellular networks. With CSBS, the computing resource for communication protocol processing could be managed flexibly according the protocol load to improve the resource efficiency. Since the protocol load changes frequently and may exceed the capacity of processors, load balancing is needed. However, existing load balancing mechanisms used in data centers cannot satisfy the real-time requirement of the communication protocol processing. Therefore, a new computing resource adjustment scheme is proposed for communication protocol processing in the CSBS architecture. First of all, the main principles of protocol processing resource adjustment is concluded, followed by the analysis on the processing resource outage probability that the computing resource becomes inadequate for protocol processing as load changes. Following the adjustment principles, the proposed scheme is designed to reduce the processing resource outage probability based onthe optimized connected graph which is constructed by the approximate Kruskal algorithm. Simulation re-sults show that compared with the conventional load balancing mechanisms, the proposed scheme can reduce the occurrence number of inadequate processing resource and the additional resource consumption of adjustment greatly.展开更多
The upcoming 6G wireless networks have to provide reliable communications in high-mobility scenarios at high carrier frequencies.However,high-mobility or high carrier frequencies will bring severe inter-carrier interf...The upcoming 6G wireless networks have to provide reliable communications in high-mobility scenarios at high carrier frequencies.However,high-mobility or high carrier frequencies will bring severe inter-carrier interference(ICI)to conventional orthogonal fre⁃quency-division multiplexing(OFDM)modulation.Orthogonal time frequency space(OTFS)modulation is a recently developing multi-carrier transmission scheme for wireless commu⁃nications in high-mobility environments.This paper evaluates the performance of coded OT⁃FS systems.In particular,we consider 5G low density parity check(LDPC)codes for OTFS systems based on 5G OFDM frame structures over high mobility channels.We show the per⁃formance of the OTFS systems with 5G LDPC codes when sum-product detection algorithm and iterative detection and decoding are employed.We also illustrate the effect of channel estimation error on the performance of the LDPC coded OTFS systems.展开更多
In centralized cellular network architecture,the concept of virtualized Base Station(VBS) becomes attracting since it enables all base stations(BSs) to share computing resources in a dynamic manner. This can significa...In centralized cellular network architecture,the concept of virtualized Base Station(VBS) becomes attracting since it enables all base stations(BSs) to share computing resources in a dynamic manner. This can significantly improve the utilization efficiency of computing resources. In this paper,we study the computing resource allocation strategy for one VBS by considering the non-negligible effect of delay introduced by switches. Specifically,we formulate the VBS's sum computing rate maximization as a set optimization problem. To address this problem,we firstly propose a computing resource schedule algorithm,namely,weight before one-step-greedy(WBOSG),which has linear computation complexity and considerable performance. Then,OSG retreat(OSG-R) algorithm is developed to further improve the system performance at the expense of computational complexity. Simulation results under practical setting are provided to validate the proposed two algorithms.展开更多
Location-based services(LBS)in vehicular ad hoc networks(VANETs)must protect users’privacy and address the threat of the exposure of sensitive locations during LBS requests.Users release not only their geographical b...Location-based services(LBS)in vehicular ad hoc networks(VANETs)must protect users’privacy and address the threat of the exposure of sensitive locations during LBS requests.Users release not only their geographical but also semantic information of the visited places(e.g.,hospital).This sensitive information enables the inference attacker to exploit the users’preferences and life patterns.In this paper we propose a reinforcement learning(RL)based sensitive semantic location privacy protection scheme.This scheme uses the idea of differential privacy to randomize the released vehicle locations and adaptively selects the perturbation policy based on the sensitivity of the semantic location and the attack history.This scheme enables a vehicle to optimize the perturbation policy in terms of the privacy and the quality of service(QoS)loss without being aware of the current inference attack model in a dynamic privacy protection process.To solve the location protection problem with high-dimensional and continuous-valued perturbation policy variables,a deep deterministic policy gradientbased semantic location perturbation scheme(DSLP)is developed.The actor part is used to generate continuous privacy budget and perturbation angle,and the critic part is used to estimate the performance of the policy.Simulations demonstrate the DSLP-based scheme outperforms the benchmark schemes,which increases the privacy,reduces the QoS loss,and increases the utility of the vehicle.展开更多
In the 5th generation(5G)wireless communication networks,network slicing emerges where network operators(NPs)form isolated logical slices by the same cellular network infrastructure and spectrum resource.In coverage r...In the 5th generation(5G)wireless communication networks,network slicing emerges where network operators(NPs)form isolated logical slices by the same cellular network infrastructure and spectrum resource.In coverage regions of access points(APs)shared by slices,device to device(D2D)communication can occur among different slices,i.e.,one device acts as D2D relay for another device serving by a different slice,which is defined as slice cooperation in this paper.Since selfish slices will not help other slices by cooperation voluntarily and unconditionally,this paper designs a novel resource allocation scheme to stimulate slice cooperation.The main idea is to encourage slice to perform cooperation for other slices by rewarding it with higher throughput.The proposed incentive scheme for slice cooperation is formulated by an optimal problem,where cooperative activities are introduced to the objective function.Since optimal solutions of the formulated problem are long term statistics,though can be obtained,a practical online slice scheduling algorithm is designed,which can obtain optimal solutions of the formulated maximal problem.Lastly,the throughput isolation indexes are defined to evaluate isolation performance of slice.According to simulation results,the proposed incentive scheme for slice cooperation can stimulate slice cooperation effectively,and the isolation of slice is also simulated and discussed.展开更多
Recent rapid rise of indoor location based services for smartphones has further increased the importance of precise localization of Wi-Fi Access Point(AP).However,most existing AP localization algorithms either exhibi...Recent rapid rise of indoor location based services for smartphones has further increased the importance of precise localization of Wi-Fi Access Point(AP).However,most existing AP localization algorithms either exhibit high errors or need specialized hardware in practical scenarios.In this paper,we propose a novel RSSI gradient-based AP localization algorithm.It consists of the following three major steps:firstly,it uses the local received signal strength variations to estimate the direction(minus gradient) of AP,then employs a direction clustering method to identify and filter measurement outliers,and finally adopts triangulation method to localize AP with the selected gradient directions.Experimental results demonstrate that the average localization error of our proposed algorithm is less than 2meters,far outperforming that of the weighted centroid approach.展开更多
Coverage challenge for small considered to be a optlmlzation is a main cell clusters which are promising solution to provide seamless cellular coverage for large indoor or outdoor areas. This paper focuses on small ce...Coverage challenge for small considered to be a optlmlzation is a main cell clusters which are promising solution to provide seamless cellular coverage for large indoor or outdoor areas. This paper focuses on small cell cluster coverage problems and proposes both centralized and distributed self-optimization methods. Modified Particle swarm optimization （MPSO） is introduced to centralized optimization which employs particle swarm optimization （PSO） and introduces a heuristic power control scheme to accelerate the algorithm to search tbr the global optimum solution. Distributed coverage optimization is modeled as a non-cooperative game, with a utility function considering both throughput and interference. An iterative power control algorithm is then proposed using game theory （DGT） which converges to Nash Equilibrium （NE）. Simulation results show that both MPSO and DGT have excellent performance in coverage optimization and outperform optimization using simulated annealing algorithm （SA）, reaching higher coverage ratio and throughput while with less iterations.展开更多
Image colorization is a classic and important topic in computer graphics,where the aim is to add color to a monochromatic input image to produce a colorful result.In this survey,we present the history of colorization ...Image colorization is a classic and important topic in computer graphics,where the aim is to add color to a monochromatic input image to produce a colorful result.In this survey,we present the history of colorization research in chronological order and summarize popular algorithms in this field.Early work on colorization mostly focused on developing techniques to improve the colorization quality.In the last few years,researchers have considered more possibilities such as combining colorization with NLP(natural language processing)and focused more on industrial applications.To better control the color,various types of color control are designed,such as providing reference images or color-scribbles.We have created a taxonomy of the colorization methods according to the input type,divided into grayscale,sketch-based and hybrid.The pros and cons are discussed for each algorithm,and they are compared according to their main characteristics.Finally,we discuss how deep learning,and in particular Generative Adversarial Networks(GANs),has changed this field.展开更多
Deep generative models allow the synthesis of realistic human faces from freehand sketches or semantic maps.However,although they are flexible,sketches and semantic maps provide too much freedom for manipulation,and t...Deep generative models allow the synthesis of realistic human faces from freehand sketches or semantic maps.However,although they are flexible,sketches and semantic maps provide too much freedom for manipulation,and thus,are not easy for novice users to control.In this study,we present DeepFaceReshaping,a novel landmarkbased deep generative framework for interactive face reshaping.To edit the shape of a face realistically by manipulating a small number of face landmarks,we employ neural shape deformation to reshape individual face components.Furthermore,we propose a novel Transformer-based partial refinement network to synthesize the reshaped face components conditioned on the edited landmarks,and fuse the components to generate the entire face using a local-to-global approach.In this manner,we limit possible reshaping effects within a feasible component-based face space.Thus,our interface is intuitive even for novice users,asconfirmed by auser study.Our experiments demonstrate that our method outperforms traditional warping-based approaches and recent deep generative techniques.展开更多
3D caricatures are important attractive elements of the interface in virtual environment such as online game. However, very limited 3D caricatures exist in the real world. Meanwhile, creating 3D caricatures manually i...3D caricatures are important attractive elements of the interface in virtual environment such as online game. However, very limited 3D caricatures exist in the real world. Meanwhile, creating 3D caricatures manually is rather costly, and even professional skills are needed. This paper proposes a novel and effective manifold transfer algorithm to reconstruct 3D caricatures according to their original 2D caricatures. We first manually create a small dataset with only 100 3D caricature models and use them to initialize the whole 3D dataset. After that, manifold transfer algorithm is carried out to refine the dataset. The algorithm comprises of two steps. The first is to perform manifold alignment between 2D and 3D caricatures to get a ＂standard＂ manifold map; the second is to reconstruct all the 3D caricatures based on the manifold map. The proposed approach utilizes and transfers knowledge of 2D caricatures to the target 3D caricatures well. Comparative experiments show that the approach reconstructs 3D caricatures more effectively and the results conform more to the styles of the original 2D caricatures than the Principal Components Analysis （PCA） based method.展开更多
3D shape editing is widely used in a range of applications such as movie production,computer games and computer aided design.It is also a popular research topic in computer graphics and computer vision.In past decades...3D shape editing is widely used in a range of applications such as movie production,computer games and computer aided design.It is also a popular research topic in computer graphics and computer vision.In past decades,researchers have developed a series of editing methods to make the editing process faster,more robust,and more reliable.Traditionally,the deformed shape is determined by the optimal transformation and weights for an energy formulation.With increasing availability of 3D shapes on the Internet,data-driven methods were proposed to improve the editing results.More recently as the deep neural networks became popular,many deep learning based editing methods have been developed in this field,which are naturally data-driven.We mainly survey recent research studies from the geometric viewpoint to those emerging neural deformation techniques and categorize them into organic shape editing methods and man-made model editing methods.Both traditional methods and recent neural network based methods are reviewed.展开更多
Federated multi-task learning(FMTL)has emerged as a promising framework for learning multiple tasks simultaneously with client-aware personalized models.While the majority of studies have focused on dealing with the n...Federated multi-task learning(FMTL)has emerged as a promising framework for learning multiple tasks simultaneously with client-aware personalized models.While the majority of studies have focused on dealing with the non-independent and identically distributed(Non-IID)characteristics of client datasets,the issue of task heterogeneity has largely been overlooked.Dealing with task heterogeneity often requires complex models,making it impractical for federated learning in resource-constrained environments.In addition,the varying nature of these heterogeneous tasks introduces inductive biases,leading to interference during aggregation and potentially resulting in biased global models.To address these issues,we propose a hierarchical FMTL framework,referred to as FedBone,to facilitate the construction of large-scale models with improved generalization.FedBone leverages server-client split learning and gradient projection to split the entire model into two components:1)a large-scale general model(referred to as the general model)on the cloud server,and 2)multiple task-specific models(referred to as client models)on edge clients,accommodating devices with limited compute power.To enhance the robustness of the large-scale general model,we incorporate the conflicting gradient projection technique into FedBone to rectify the skewed gradient direction caused by aggregating gradients from heterogeneous tasks.The proposed FedBone framework is evaluated on three benchmark datasets and one real ophthalmic dataset.The comprehensive experiments demonstrate that FedBone efficiently adapts to the heterogeneous local tasks of each client and outperforms existing federated learning algorithms in various dense prediction and classification tasks while utilizing off-the-shelf computational resources on the client side.展开更多
Recent advancements in the field have resulted in significant progress in achieving realistic head reconstruction and manipulation using neural radiance fields(NeRF).Despite these advances,capturing intricate facial d...Recent advancements in the field have resulted in significant progress in achieving realistic head reconstruction and manipulation using neural radiance fields(NeRF).Despite these advances,capturing intricate facial details remains a persistent challenge.Moreover,casually captured input,involving both head poses and camera movements,introduces additional difficulties to existing methods of head avatar reconstruction.To address the challenge posed by video data captured with camera motion,we propose a novel method,AvatarWild,for reconstructing head avatars from monocular videos taken by consumer devices.Notably,our approach decouples the camera pose and head pose,allowing reconstructed avatars to be visualized with different poses and expressions from novel viewpoints.To enhance the visual quality of the reconstructed facial avatar,we introduce a view-dependent detail enhancement module designed to augment local facial details without compromising viewpoint consistency.Our method demonstrates superior performance compared to existing approaches,as evidenced by reconstruction and animation results on both multi-view and single-view datasets.Remarkably,our approach stands out by exclusively relying on video data captured by portable devices,such as smartphones.This not only underscores the practicality of our method but also extends its applicability to real-world scenarios where accessibility and ease of data capture are crucial.展开更多
Automatic translation of Chinese text to Chinese Braille is important for blind people in China to acquire information using computers or smart phones. In this paper, a novel scheme of Chinese-Braille translation is p...Automatic translation of Chinese text to Chinese Braille is important for blind people in China to acquire information using computers or smart phones. In this paper, a novel scheme of Chinese-Braille translation is proposed. Under the scheme, a Braille word segmentation model based on statistical machine learning is trained on a Braille corpus, and Braille word segmentation is carried out using the statistical model directly without the stage of Chinese word segmentation. This method avoids establishing rules concerning syntactic and semantic information and uses statistical model to learn the rules stealthily and automatically. To further improve the performance, an algorithm of fusing the results of Chinese word segmentation and Braille word segmentation is also proposed. Our results show that the proposed method achieves accuracy of 92.81% for Braille word segmentation and considerably outperforms current approaches using the segmentation-merging scheme.展开更多
基金supported by the National Natural Science Foundation of China under Grant U21A20449in part by Jiangsu Provincial Key Research and Development Program under Grant BE2021013-2。
文摘Wireless communication-enabled Cooperative Adaptive Cruise Control(CACC)is expected to improve the safety and traffic capacity of vehicle platoons.Existing CACC considers a conventional communication delay with fixed Vehicular Communication Network(VCN)topologies.However,when the network is under attack,the communication delay may be much higher,and the stability of the system may not be guaranteed.This paper proposes a novel communication Delay Aware CACC with Dynamic Network Topologies(DADNT).The main idea is that for various communication delays,in order to maximize the traffic capacity while guaranteeing stability and minimizing the following error,the CACC should dynamically adjust the VCN network topology to achieve the minimum inter-vehicle spacing.To this end,a multi-objective optimization problem is formulated,and a 3-step Divide-And-Conquer sub-optimal solution(3DAC)is proposed.Simulation results show that with 3DAC,the proposed DADNT with CACC can reduce the inter-vehicle spacing by 5%,10%,and 14%,respectively,compared with the traditional CACC with fixed one-vehicle,two-vehicle,and three-vehicle look-ahead network topologies,thereby improving the traffic efficiency.
基金This work is supported by the National Natural Science Youth Fund of China granted by No.61901452 and Innovative Project of ICT/CAS granted by No.20196110
文摘With the proliferation of the Internet of Things(IoT),various services are emerging with totally different features and requirements,which cannot be supported by the current fifth generation of mobile cellular networks(5G).The future sixth generation of mobile cellular networks(6G)is expected to have the capability to support new and unknown services with changing requirements.Hence,in addition to enhancing its capability by 10–100 times compared with 5G,6G should also be intelligent and open to adapt to the ever-changing services in the IoT,which requires a convergence of Communication,Computing and Caching(3C).Based on the analysis of the requirements of new services for 6G,this paper identifies key enabling technologies for an intelligent and open 6G network,all featured with 3C convergence.These technologies cover fundamental and emerging topics,including 3C-based spectrum management,radio channel construction,delay-aware transmission,wireless distributed computing,and network self-evolution.From the detailed analysis of these 3C-based technologies presented in this paper,we can see that although they are promising to enable an intelligent and open 6G,more efforts are needed to realize the expected 6G network.
基金The Natural Science Foundation of Henan Province(No.232300421097)the Program for Science&Technology Innovation Talents in Universities of Henan Province(No.23HASTIT019,24HASTIT038)+2 种基金the China Postdoctoral Science Foundation(No.2023T160596,2023M733251)the Open Research Fund of National Mobile Communications Research Laboratory,Southeast University(No.2023D11)the Song Shan Laboratory Foundation(No.YYJC022022003)。
文摘In this article,the secure computation efficiency(SCE)problem is studied in a massive multipleinput multiple-output(mMIMO)-assisted mobile edge computing(MEC)network.We first derive the secure transmission rate based on the mMIMO under imperfect channel state information.Based on this,the SCE maximization problem is formulated by jointly optimizing the local computation frequency,the offloading time,the downloading time,the users and the base station transmit power.Due to its difficulty to directly solve the formulated problem,we first transform the fractional objective function into the subtractive form one via the dinkelbach method.Next,the original problem is transformed into a convex one by applying the successive convex approximation technique,and an iteration algorithm is proposed to obtain the solutions.Finally,the stimulations are conducted to show that the performance of the proposed schemes is superior to that of the other schemes.
基金This work is supported by the National Natural Science Foundation of China （61070109） and Opening Project of Beijing Key Laboratory of Mobile Computing and Pervasive Device.
基金the key project of the National Science and Technology Major Project(Grant No.2018ZX03001017)the project of the CAS engineering laboratory for intelligent agricultural machinery equipment(Grant No.GC201907-02).
文摘Novel centralized base station architectures integrating computation and communication functionalities have become important for the development of future mobile communication networks.Therefore,the development of dynamic high-speed interconnections between baseband units(BBUs)and remote radio heads(RRHs)is vital in centralized base station design.Herein,dynamic high-speed switches(HSSs)connecting BBUs and RRHs were designed for a centralized base station architecture.We analyzed the characteristics of actual traffic and introduced a switch traffic model suitable for the super base station architecture.Then,we proposed a data-priority-aware(DPA)scheduling algorithm based on the traffic model.Lastly,we developed the dynamic HSS model based on the OPNET platform and the prototype based on FPGA.Our results show that the DPA achieves close to 100%throughput with lower latency and provides better run-time complexity than iOCF and HE-iSLIP,thereby demonstrating that the proposed switch system can be adopted in centralized base station architectures.
基金Supported by the Industrial Internet Innovation and Development Project of Ministry of Industry and Information Technology (No.GHBJ2004)。
文摘A Taylor series expansion(TSE) based design for minimum mean-square error(MMSE) and QR decomposition(QRD) of multi-input and multi-output(MIMO) systems is proposed based on application specific instruction set processor(ASIP), which uses TSE algorithm instead of resource-consuming reciprocal and reciprocal square root(RSR) operations.The aim is to give a high performance implementation for MMSE and QRD in one programmable platform simultaneously.Furthermore, instruction set architecture(ISA) and the allocation of data paths in single instruction multiple data-very long instruction word(SIMD-VLIW) architecture are provided, offering more data parallelism and instruction parallelism for different dimension matrices and operation types.Meanwhile, multiple level numerical precision can be achieved with flexible table size and expansion order in TSE ISA.The ASIP has been implemented to a 28 nm CMOS process and frequency reaches 800 MHz.Experimental results show that the proposed design provides perfect numerical precision within the fixed bit-width of the ASIP, higher matrix processing rate better than the requirements of 5G system and more rate-area efficiency comparable with ASIC implementations.
基金supported in part by the National Science Foundationof China under Grant number 61431001the Beijing Talents Fund under Grant number 2015000021223ZK31
文摘The centralized radio access cellular network infrastructure based on centralized Super Base Station(CSBS) is a promising solution to reduce the high construction cost and energy consumption of conventional cellular networks. With CSBS, the computing resource for communication protocol processing could be managed flexibly according the protocol load to improve the resource efficiency. Since the protocol load changes frequently and may exceed the capacity of processors, load balancing is needed. However, existing load balancing mechanisms used in data centers cannot satisfy the real-time requirement of the communication protocol processing. Therefore, a new computing resource adjustment scheme is proposed for communication protocol processing in the CSBS architecture. First of all, the main principles of protocol processing resource adjustment is concluded, followed by the analysis on the processing resource outage probability that the computing resource becomes inadequate for protocol processing as load changes. Following the adjustment principles, the proposed scheme is designed to reduce the processing resource outage probability based onthe optimized connected graph which is constructed by the approximate Kruskal algorithm. Simulation re-sults show that compared with the conventional load balancing mechanisms, the proposed scheme can reduce the occurrence number of inadequate processing resource and the additional resource consumption of adjustment greatly.
基金supported by National Key R&D Program of Chi⁃na(No.2020YFB1807802)the National Science Fund for Distinguished Young Scholars(No.61901453)Jiangsu Provincial Key Research and Development Program(No.BE2021013-2)。
文摘The upcoming 6G wireless networks have to provide reliable communications in high-mobility scenarios at high carrier frequencies.However,high-mobility or high carrier frequencies will bring severe inter-carrier interference(ICI)to conventional orthogonal fre⁃quency-division multiplexing(OFDM)modulation.Orthogonal time frequency space(OTFS)modulation is a recently developing multi-carrier transmission scheme for wireless commu⁃nications in high-mobility environments.This paper evaluates the performance of coded OT⁃FS systems.In particular,we consider 5G low density parity check(LDPC)codes for OTFS systems based on 5G OFDM frame structures over high mobility channels.We show the per⁃formance of the OTFS systems with 5G LDPC codes when sum-product detection algorithm and iterative detection and decoding are employed.We also illustrate the effect of channel estimation error on the performance of the LDPC coded OTFS systems.
基金funded by the key project of the National Natural Science Foundation of China (No.61431001)the National High-Tech R&D Program (863 Program 2015AA01A705)New Technology Star Plan of Beijing (No.xx2013052)
文摘In centralized cellular network architecture,the concept of virtualized Base Station(VBS) becomes attracting since it enables all base stations(BSs) to share computing resources in a dynamic manner. This can significantly improve the utilization efficiency of computing resources. In this paper,we study the computing resource allocation strategy for one VBS by considering the non-negligible effect of delay introduced by switches. Specifically,we formulate the VBS's sum computing rate maximization as a set optimization problem. To address this problem,we firstly propose a computing resource schedule algorithm,namely,weight before one-step-greedy(WBOSG),which has linear computation complexity and considerable performance. Then,OSG retreat(OSG-R) algorithm is developed to further improve the system performance at the expense of computational complexity. Simulation results under practical setting are provided to validate the proposed two algorithms.
基金This work was supported in part by National Natural Science Foundation of China under Grant 61971366 and 61771474,and in part by the Fundamental Research Funds for the central universities No.20720200077,and in part by Major Science and Technology Innovation Projects of Shandong Province 2019JZZY020505 and Key R&D Projects of Xuzhou City KC18171,and in part by NSF EARS-1839818,CNS1717454,CNS-1731424,and CNS-1702850.
文摘Location-based services(LBS)in vehicular ad hoc networks(VANETs)must protect users’privacy and address the threat of the exposure of sensitive locations during LBS requests.Users release not only their geographical but also semantic information of the visited places(e.g.,hospital).This sensitive information enables the inference attacker to exploit the users’preferences and life patterns.In this paper we propose a reinforcement learning(RL)based sensitive semantic location privacy protection scheme.This scheme uses the idea of differential privacy to randomize the released vehicle locations and adaptively selects the perturbation policy based on the sensitivity of the semantic location and the attack history.This scheme enables a vehicle to optimize the perturbation policy in terms of the privacy and the quality of service(QoS)loss without being aware of the current inference attack model in a dynamic privacy protection process.To solve the location protection problem with high-dimensional and continuous-valued perturbation policy variables,a deep deterministic policy gradientbased semantic location perturbation scheme(DSLP)is developed.The actor part is used to generate continuous privacy budget and perturbation angle,and the critic part is used to estimate the performance of the policy.Simulations demonstrate the DSLP-based scheme outperforms the benchmark schemes,which increases the privacy,reduces the QoS loss,and increases the utility of the vehicle.
基金supported by Beijing Natural Science Foundation under Grant number L172049the National Science and CAS Engineering Laboratory for Intelligent Agricultural Machinery Equipment GC201907-02
文摘In the 5th generation(5G)wireless communication networks,network slicing emerges where network operators(NPs)form isolated logical slices by the same cellular network infrastructure and spectrum resource.In coverage regions of access points(APs)shared by slices,device to device(D2D)communication can occur among different slices,i.e.,one device acts as D2D relay for another device serving by a different slice,which is defined as slice cooperation in this paper.Since selfish slices will not help other slices by cooperation voluntarily and unconditionally,this paper designs a novel resource allocation scheme to stimulate slice cooperation.The main idea is to encourage slice to perform cooperation for other slices by rewarding it with higher throughput.The proposed incentive scheme for slice cooperation is formulated by an optimal problem,where cooperative activities are introduced to the objective function.Since optimal solutions of the formulated problem are long term statistics,though can be obtained,a practical online slice scheduling algorithm is designed,which can obtain optimal solutions of the formulated maximal problem.Lastly,the throughput isolation indexes are defined to evaluate isolation performance of slice.According to simulation results,the proposed incentive scheme for slice cooperation can stimulate slice cooperation effectively,and the isolation of slice is also simulated and discussed.
基金This work was supported in part by the National Natural Science Foundation of China，the Major Projects of Ministry of Industry and Information Technology，the National High Technology Research and Development Program of China
文摘Recent rapid rise of indoor location based services for smartphones has further increased the importance of precise localization of Wi-Fi Access Point(AP).However,most existing AP localization algorithms either exhibit high errors or need specialized hardware in practical scenarios.In this paper,we propose a novel RSSI gradient-based AP localization algorithm.It consists of the following three major steps:firstly,it uses the local received signal strength variations to estimate the direction(minus gradient) of AP,then employs a direction clustering method to identify and filter measurement outliers,and finally adopts triangulation method to localize AP with the selected gradient directions.Experimental results demonstrate that the average localization error of our proposed algorithm is less than 2meters,far outperforming that of the weighted centroid approach.
基金supported by the National High-Tech Development 863 Program of China (Grant DOS. 2012AA012801)National Natural Science Foundation of China(No.61331009)
文摘Coverage challenge for small considered to be a optlmlzation is a main cell clusters which are promising solution to provide seamless cellular coverage for large indoor or outdoor areas. This paper focuses on small cell cluster coverage problems and proposes both centralized and distributed self-optimization methods. Modified Particle swarm optimization （MPSO） is introduced to centralized optimization which employs particle swarm optimization （PSO） and introduces a heuristic power control scheme to accelerate the algorithm to search tbr the global optimum solution. Distributed coverage optimization is modeled as a non-cooperative game, with a utility function considering both throughput and interference. An iterative power control algorithm is then proposed using game theory （DGT） which converges to Nash Equilibrium （NE）. Simulation results show that both MPSO and DGT have excellent performance in coverage optimization and outperform optimization using simulated annealing algorithm （SA）, reaching higher coverage ratio and throughput while with less iterations.
基金This work was supported by grants from the National Nat-ural Science Foundation of China(No.61872440,No.62061136007 and No.62102403)the Beijing Municipal Natural Science Foun-dation for Distinguished Young Scholars(No.JQ21013)+1 种基金the Youth Innovation Promotion Association CAS,Royal Society Newton Advanced Fellowship(No.NAF\R2\192151)the Open Project Program of State Key Laboratory of Virtual Reality Technology and Systems,Beihang University(No.VRLAB2022C07).
文摘Image colorization is a classic and important topic in computer graphics,where the aim is to add color to a monochromatic input image to produce a colorful result.In this survey,we present the history of colorization research in chronological order and summarize popular algorithms in this field.Early work on colorization mostly focused on developing techniques to improve the colorization quality.In the last few years,researchers have considered more possibilities such as combining colorization with NLP(natural language processing)and focused more on industrial applications.To better control the color,various types of color control are designed,such as providing reference images or color-scribbles.We have created a taxonomy of the colorization methods according to the input type,divided into grayscale,sketch-based and hybrid.The pros and cons are discussed for each algorithm,and they are compared according to their main characteristics.Finally,we discuss how deep learning,and in particular Generative Adversarial Networks(GANs),has changed this field.
基金supported by grants from the Open Researchh Projects of Zhejiang Lab(No.2021KE0AB06)the National Natural Science Foundation of China(Nos.62061136007 and 62102403)+1 种基金the Beijing Municipal Natural Science Foundation for Distinguished Young Scholars(No.JQ21013)d the Open Project Program of the State Key Laboratory of Virtual Reality Technology and Systems,Beihang University(No.VRLAB2022C07).
文摘Deep generative models allow the synthesis of realistic human faces from freehand sketches or semantic maps.However,although they are flexible,sketches and semantic maps provide too much freedom for manipulation,and thus,are not easy for novice users to control.In this study,we present DeepFaceReshaping,a novel landmarkbased deep generative framework for interactive face reshaping.To edit the shape of a face realistically by manipulating a small number of face landmarks,we employ neural shape deformation to reshape individual face components.Furthermore,we propose a novel Transformer-based partial refinement network to synthesize the reshaped face components conditioned on the edited landmarks,and fuse the components to generate the entire face using a local-to-global approach.In this manner,we limit possible reshaping effects within a feasible component-based face space.Thus,our interface is intuitive even for novice users,asconfirmed by auser study.Our experiments demonstrate that our method outperforms traditional warping-based approaches and recent deep generative techniques.
基金supported by the National Natural Foundation of China under Grant Nos. 61070110 and 61173066
文摘3D caricatures are important attractive elements of the interface in virtual environment such as online game. However, very limited 3D caricatures exist in the real world. Meanwhile, creating 3D caricatures manually is rather costly, and even professional skills are needed. This paper proposes a novel and effective manifold transfer algorithm to reconstruct 3D caricatures according to their original 2D caricatures. We first manually create a small dataset with only 100 3D caricature models and use them to initialize the whole 3D dataset. After that, manifold transfer algorithm is carried out to refine the dataset. The algorithm comprises of two steps. The first is to perform manifold alignment between 2D and 3D caricatures to get a ＂standard＂ manifold map; the second is to reconstruct all the 3D caricatures based on the manifold map. The proposed approach utilizes and transfers knowledge of 2D caricatures to the target 3D caricatures well. Comparative experiments show that the approach reconstructs 3D caricatures more effectively and the results conform more to the styles of the original 2D caricatures than the Principal Components Analysis （PCA） based method.
基金supported by the National Natural Science Foundation of China under Grant Nos.62061136007 and 61872440the Royal Society Newton Advanced Fellowship under Grant No.NAF\R2\192151Youth Innovation Promotion Association CAS,and Science and Technology Service Network Initiative,Chinese Academy of Sciences under Grant No.KFJ-STS-QYZD-2021-11-001。
文摘3D shape editing is widely used in a range of applications such as movie production,computer games and computer aided design.It is also a popular research topic in computer graphics and computer vision.In past decades,researchers have developed a series of editing methods to make the editing process faster,more robust,and more reliable.Traditionally,the deformed shape is determined by the optimal transformation and weights for an energy formulation.With increasing availability of 3D shapes on the Internet,data-driven methods were proposed to improve the editing results.More recently as the deep neural networks became popular,many deep learning based editing methods have been developed in this field,which are naturally data-driven.We mainly survey recent research studies from the geometric viewpoint to those emerging neural deformation techniques and categorize them into organic shape editing methods and man-made model editing methods.Both traditional methods and recent neural network based methods are reviewed.
基金supported by the Beijing Municipal Science and Technology Commission under Grant No.Z221100002722009the National Natural Science Foundation of China under Grant No.62202455+1 种基金the Youth Innovation Promotion Association of Chinese Academy of Sciences(CAS),the Hunan Provincial Natural Science Foundation of China under Grant No.2023JJ70034the Science Research Foundation of the CAS-Aier Joint Laboratory on Digital Ophthalmology under Grant No.SZYK202201.
文摘Federated multi-task learning(FMTL)has emerged as a promising framework for learning multiple tasks simultaneously with client-aware personalized models.While the majority of studies have focused on dealing with the non-independent and identically distributed(Non-IID)characteristics of client datasets,the issue of task heterogeneity has largely been overlooked.Dealing with task heterogeneity often requires complex models,making it impractical for federated learning in resource-constrained environments.In addition,the varying nature of these heterogeneous tasks introduces inductive biases,leading to interference during aggregation and potentially resulting in biased global models.To address these issues,we propose a hierarchical FMTL framework,referred to as FedBone,to facilitate the construction of large-scale models with improved generalization.FedBone leverages server-client split learning and gradient projection to split the entire model into two components:1)a large-scale general model(referred to as the general model)on the cloud server,and 2)multiple task-specific models(referred to as client models)on edge clients,accommodating devices with limited compute power.To enhance the robustness of the large-scale general model,we incorporate the conflicting gradient projection technique into FedBone to rectify the skewed gradient direction caused by aggregating gradients from heterogeneous tasks.The proposed FedBone framework is evaluated on three benchmark datasets and one real ophthalmic dataset.The comprehensive experiments demonstrate that FedBone efficiently adapts to the heterogeneous local tasks of each client and outperforms existing federated learning algorithms in various dense prediction and classification tasks while utilizing off-the-shelf computational resources on the client side.
基金supported by National Natural Science Foundation of China(No.6247075018 and No.62322210)the Innovation Funding of ICT,CAS(No.E461020)+1 种基金Beijing Munici-pal Natural Science Foundation for Distinguished Young Scholars(No.JQ21013)Beijing Municipal Science and Technology Commission(No.Z231100005923031).
文摘Recent advancements in the field have resulted in significant progress in achieving realistic head reconstruction and manipulation using neural radiance fields(NeRF).Despite these advances,capturing intricate facial details remains a persistent challenge.Moreover,casually captured input,involving both head poses and camera movements,introduces additional difficulties to existing methods of head avatar reconstruction.To address the challenge posed by video data captured with camera motion,we propose a novel method,AvatarWild,for reconstructing head avatars from monocular videos taken by consumer devices.Notably,our approach decouples the camera pose and head pose,allowing reconstructed avatars to be visualized with different poses and expressions from novel viewpoints.To enhance the visual quality of the reconstructed facial avatar,we introduce a view-dependent detail enhancement module designed to augment local facial details without compromising viewpoint consistency.Our method demonstrates superior performance compared to existing approaches,as evidenced by reconstruction and animation results on both multi-view and single-view datasets.Remarkably,our approach stands out by exclusively relying on video data captured by portable devices,such as smartphones.This not only underscores the practicality of our method but also extends its applicability to real-world scenarios where accessibility and ease of data capture are crucial.
基金Fthe National Key Technology R&D Program of China(No.2014BAK15B02)the National Natural Science Foundation of China(No.61202209)
文摘Automatic translation of Chinese text to Chinese Braille is important for blind people in China to acquire information using computers or smart phones. In this paper, a novel scheme of Chinese-Braille translation is proposed. Under the scheme, a Braille word segmentation model based on statistical machine learning is trained on a Braille corpus, and Braille word segmentation is carried out using the statistical model directly without the stage of Chinese word segmentation. This method avoids establishing rules concerning syntactic and semantic information and uses statistical model to learn the rules stealthily and automatically. To further improve the performance, an algorithm of fusing the results of Chinese word segmentation and Braille word segmentation is also proposed. Our results show that the proposed method achieves accuracy of 92.81% for Braille word segmentation and considerably outperforms current approaches using the segmentation-merging scheme.
