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Intellicise Model Transmission for Semantic communication in Intelligence-Native 6G networks

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China communications 2024年第7期21卷 95-112页

作者： Wang Yining Han Shujun Xu Xiaodong Meng Rui Liang Haotai Dong Chen Zhang Ping State Key laboratory of network and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China Department of broadband communication Peng Cheng LaboratoryShenzhen 518066China

To facilitate emerging applications and demands of edge intelligence(EI)-empowered 6G networks,model-driven semantic communications have been proposed to reduce transmission volume by deploying artificial intelligence(AI)models that provide abilities of semantic extraction and ***,it is not feasible to preload all AI models on resource-constrained ***,in-time model transmission becomes a crucial *** paper proposes an intellicise model transmission architecture to guarantee the reliable transmission of models for semantic *** mathematical relationship between model size and performance is formulated by employing a recognition error function supported with experimental *** consider the characteristics of wireless channels and derive the closed-form expression of model transmission outage probability(MTOP)over the Rayleigh ***,we define the effective model accuracy(EMA)to evaluate the model transmission performance of both communication and *** we propose a joint model selection and resource allocation(JMSRA)algorithm to maximize the average EMA of all *** results demonstrate that the average EMA of the JMSRA algorithm outperforms baseline algorithms by about 22%.

关键词： edge intelligence(EI) model transmission outage probability and accuracy resource allocation semantic communication

Gray code based gradient-free optimization algorithm for parameterized quantum circuit

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Chinese Physics B 2024年第2期33卷 189-194页

作者：张安琪武春辉赵生妹 Institute of Signal Processing and Transmission Nanjing University of Posts and TelecommunicationsNanjing 210003China Key laboratory of broadband Wireless communication and Sensor network Technology(Ministry of Education) Nanjing University of Posts and TelecommunicationsNanjing 210003China

A Gray code based gradient-free optimization(GCO)algorithm is proposed to update the parameters of parameterized quantum circuits(PQCs)in this *** parameter of PQCs is encoded as a binary string,named as a gene,and a genetic-based method is adopted to select the *** individuals in the offspring are decoded in Gray code way to keep Hamming distance,and then are evaluated to obtain the best one with the lowest cost value in each *** algorithm is performed iteratively for all parameters one by one until the cost value satisfies the stop condition or the number of iterations is *** GCO algorithm is demonstrated for classification tasks in Iris and MNIST datasets,and their performance are compared by those with the Bayesian optimization algorithm and binary code based optimization *** simulation results show that the GCO algorithm can reach high accuracies steadily for quantum classification ***,the GCO algorithm has a robust performance in the noise environment.

关键词： gradient-free optimization Gray code genetic-based method

Cross-Modal Graph Semantic communication Assisted by Generative AI in the Metaverse for 6G

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Research 2024年第2期2024卷 19-27页

作者： Mingkai Chen Minghao Liu Congyan Wang Xingnuo Song Zhe Zhang Yannan Xie Lei Wang Key laboratory of broadband Wireless communication and Sensor network Technology Nanjing University of Posts and TelecommunicationsNanjng 210003China State Key laboratory of Organic Electronics and Information Displays&Institute of Advanced Materials(IAM) Nanjing University of Posts and TelecommunicationsNanjing 210023China

Recently, the development of the Metaverse has become a frontier spotlight, which is an important demonstration of the integration innovation of advanced technologies in the Internet. Moreover, artificial intelligence (AI) and 6G communications will be widely used in our daily lives. However, the effective interactions with the representations of multimodal data among users via 6G communications is the main challenge in the Metaverse. In this work, we introduce an intelligent cross-modal graph semantic communication approach based on generative AI and 3-dimensional (3D) point clouds to improve the diversity of multimodal representations in the Metaverse. Using a graph neural network, multimodal data can be recorded by key semantic features related to the real scenarios. Then, we compress the semantic features using a graph transformer encoder at the transmitter, which can extract the semantic representations through the cross-modal attention mechanisms. Next, we leverage a graph semantic validation mechanism to guarantee the exactness of the overall data at the receiver. Furthermore, we adopt generative AI to regenerate multimodal data in virtual scenarios. Simultaneously, a novel 3D generative reconstruction network is constructed from the 3D point clouds, which can transfer the data from images to 3D models, and we infer the multimodal data into the 3D models to increase realism in virtual scenarios. Finally, the experiment results demonstrate that cross-modal graph semantic communication, assisted by generative AI, has substantial potential for enhancing user interactions in the 6G communications and Metaverse.

关键词： modal frontier guarantee

Modeling and Performance Analysis of UAV-Aided Millimeter Wave Cellular networks with Stochastic Geometry

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China communications 2024年第6期21卷 146-162页

作者： Li Junruo Wang Yuanjie Cui Qimei Hou Yanzhao Tao Xiaofeng National Engineering laboratory for Mobile network Technologies Beijing University of Posts and TelecommunicationsBeijing 100876China National Computer network Emergency Response Technical Team/Coordination Center of China(CNCERT/CC) Beijing 100029China Department of broadband communication Peng Cheng LaboratoryShenzhen 518055China

UAV-aided cellular networks,millimeter wave(mm-wave) communications and multi-antenna techniques are viewed as promising components of the solution for beyond-5G(B5G) and even 6G *** leveraging the power of stochastic geometry,this paper aims at providing an effective framework for modeling and analyzing a UAV-aided heterogeneous cellular network,where the terrestrial base stations(TBSs) and the UAV base stations(UBSs) coexist,and the UBSs are provided with mm-wave and multi-antenna *** modeling the TBSs as a PPP and the UBSs as a Matern hard-core point process of type Ⅱ(MPH-Ⅱ),approximated but accurate analytical results for the average rate of the typical user of both tiers are derived through an approximation method based on the mean interference-to-signal ratio(MISR) *** influence of some relevant parameters is discussed in detail,and some insights into the network deployment and optimization are *** results show that some trade-offs are worthy of being considered,such as the antenna array size,the altitude of the UAVs and the power control factor of the UBSs.

关键词： average rate downlink millimeter wave point process theory SIR stochastic geometry UAVaided cellular networks

Diffraction deep neural network-based classification for vector vortex beams

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Chinese Physics B 2024年第3期33卷 387-392页

作者：彭怡翔陈兵王乐赵生妹 Institute of Signal Processing and Transmission Nanjing University of Posts and Telecommunications (NJUPT)Nanjing 210003China Key laboratory of broadband Wireless communication and Sensor network Technology Ministry of EducationNanjing 210003China National laboratory of Solid State Microstructures Nanjing UniversityNanjing 210093China

The vector vortex beam(VVB)has attracted significant attention due to its intrinsic diversity of information and has found great applications in both classical and quantum ***,a VVB is unavoidably affected by atmospheric turbulence(AT)when it propagates through the free-space optical communication environment,which results in detection errors at the *** this paper,we propose a VVB classification scheme to detect VVBs with continuously changing polarization states under AT,where a diffractive deep neural network(DDNN)is designed and trained to classify the intensity distribution of the input distorted VVBs,and the horizontal direction of polarization of the input distorted beam is adopted as the feature for the classification through the *** numerical simulations and experimental results demonstrate that the proposed scheme has high accuracy in classification *** energy distribution percentage remains above 95%from weak to medium AT,and the classification accuracy can remain above 95%for various strengths of *** has a faster convergence and better accuracy than that based on a convolutional neural network.

关键词： vector vortex beam diffractive deep neural network classification atmospheric turbulence

Joint Optimization of Resource Allocation and Trajectory Based on User Trajectory for UAV-Assisted Backscatter communication System

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China communications 2024年第2期21卷 197-209页

作者： Peizhong Xie Junjie Jiang Ting Li Yin Lu School of communication and Information Engineering Nanjing University of Posts and TelecommunicationsNanjing 210003China Key Lab of broadband Wireless communication and Sensor network Technology(Nanjing University of Posts and Telecommunications) Ministry of EducationNanjing 210003China

The Backscatter communication has gained widespread attention from academia and industry in recent years. In this paper, A method of resource allocation and trajectory optimization is proposed for UAV-assisted backscatter communication based on user trajectory. This paper will establish an optimization problem of jointly optimizing the UAV trajectories, UAV transmission power and BD scheduling based on the large-scale channel state signals estimated in advance of the known user trajectories, taking into account the constraints of BD data and working energy consumption, to maximize the energy efficiency of the system. The problem is a non-convex optimization problem in fractional form, and there is nonlinear coupling between optimization *** iterative algorithm is proposed based on Dinkelbach algorithm, block coordinate descent method and continuous convex optimization technology. First, the objective function is converted into a non-fractional programming problem based on Dinkelbach method,and then the block coordinate descent method is used to decompose the original complex problem into three independent sub-problems. Finally, the successive convex approximation method is used to solve the trajectory optimization sub-problem. The simulation results show that the proposed scheme and algorithm have obvious energy efficiency gains compared with the comparison scheme.

关键词： energy efficiency joint optimization UAV-assisted backscatter communication user trajectory

Generation of orbital angular momentum hologram using a modified U-net

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Chinese Physics B 2024年第3期33卷 401-407页

作者：郑志刚韩菲菲王乐赵生妹 Institute of Signal Processing and Transmission Nanjing University of Posts and TelecommunicationsNanjing 210003China Key laboratory of broadband Wireless communication and Sensor network Technology (Ministry of Education) Nanjing University of Posts and TelecommunicationsNanjing 210003China National laboratory of Solid State Microstructures Nanjing UniversityNanjing 210093China

Orbital angular momentum(OAM)holography has become a promising technique in information encryption,data storage and opto-electronic computing,owing to the infinite topological charge of one single OAM mode and the orthogonality of different OAM *** this paper,we propose a novel OAM hologram generation method based on a densely connected U-net(DCU),where the densely connected convolution blocks(DCB)replace the convolution blocks of the ***,the reconstruction process of the OAM hologram is integrated into DCU as its output layer,so as to eliminate the requirement to prepare training data for the OAM hologram,which is required by conventional neural networks through an iterative *** experimental and simulation results show that the OAM hologram can rapidly be generated with the well-trained DCU,and the reconstructed image's quality from the generated OAM hologram is significantly improved in comparison with those from the Gerchberg-Saxton generation method,the Gerchberg-Saxton based generation method and the U-net *** addition,a 10-bit OAM multiplexing hologram scheme is numerically demonstrated to have a high capacity with OAM hologram.

关键词： orbital angular momentum(OAM) holography OAM holography deep learning

Stackelberg Game for Wireless Powered and Backscattering Enabled Sensor networks

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China communications 2024年第3期21卷 189-204页

作者： Lyu Bin Cao Yi Wang Shuai Guo Haiyan Hao Chengyao Key laboratory of Ministry of Education in broadband Wireless communication and Sensor network Technology Nanjing University of Posts and TelecommunicationsNanjing 210003China Jiangsu Engineering Research Center of Novel Optical Fiber Technology and communication network Suzhou 215006China Guangdong-Hong Kong-Macao Joint laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China

This paper investigates a wireless powered and backscattering enabled sensor network based on the non-linear energy harvesting model, where the power beacon(PB) delivers energy signals to wireless sensors to enable their passive backscattering and active transmission to the access point(AP). We propose an efficient time scheduling scheme for network performance enhancement, based on which each sensor can always harvest energy from the PB over the entire block except its time slots allocated for passive and active information delivery. Considering the PB and wireless sensors are from two selfish service providers, we use the Stackelberg game to model the energy interaction among them. To address the non-convexity of the leader-level problem, we propose to decompose the original problem into two subproblems and solve them iteratively in an alternating manner. Specifically, the successive convex approximation, semi-definite relaxation(SDR) and variable substitution techniques are applied to find a nearoptimal solution. To evaluate the performance loss caused by the interaction between two providers, we further investigate the social welfare maximization problem. Numerical results demonstrate that compared to the benchmark schemes, the proposed scheme can achieve up to 35.4% and 38.7% utility gain for the leader and the follower, respectively.

关键词： backscatter communication energy interaction stackelberg game wireless powered sensor network

Task-Oriented Semantic communication with Foundation Models

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China communications 2024年第7期21卷 65-77页

作者： Chen Mingkai Liu Minghao Zhang Zhe Xu Zhiping Wang Lei Key laboratory of broadband Wireless communication and Sensor network Technology Ministry of EducationNanjing University of Posts and TelecommunicationsNanjing 210003China School of Ocean Information Engineering Jimei UniversityXiamen 361021China Key laboratory of Underwater Acoustic communication and Marine Information Technology(Xiamen University) Ministry EducationXiamen 361005China

In the future development direction of the sixth generation(6G)mobile communication,several communication models are proposed to face the growing challenges of the *** rapid development of artificial intelligence(AI)foundation models provides significant support for efficient and intelligent communication *** this paper,we propose an innovative semantic communication paradigm called task-oriented semantic communication system with foundation ***,we segment the image by using task prompts based on the segment anything model(SAM)and contrastive language-image pretraining(CLIP).Meanwhile,we adopt Bezier curve to enhance the mask to improve the segmentation ***,we have differentiated semantic compression and transmission approaches for segmented ***,we fuse different semantic information based on the conditional diffusion model to generate high-quality images that satisfy the users'specific task ***,the experimental results show that the proposed system compresses the semantic information effectively and improves the robustness of semantic communication.

关键词： diffusion model foundation model joint source-channel coding task-oriented semantic communication