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arXiv 2022年

作者： Liu, Aiping Xu, Lei Xu, Xin-Biao Chen, Guang-Jie Zhang, Pengfei Xiang, Guo-Yong Guo, Guang-Can Wang, Qin Zou, Chang-Ling Institute of quantum information and technology Nanjing University of Posts and Telecommunications Nanjing210003 China CAS Key Laboratory of Quantum Information University of Science and Technology of China Hefei230026 China State Key Laboratory of Quantum Optics and Quantum Optics Devices Institute of Opto-Electronics Shanxi University Taiyuan030006 China Broadband wireless communication and sensor network technology Key lab of Ministry of Education Nanjing University of Posts and Telecommunications Nanjing210003 China CAS Center for Excellence in Quantum Information and Quantum Physics University of Science and Technology of China Hefei230026 China

The hybrid photon-atom integrated circuits, which include photonic microcavities and trapped single neutral atom in their evanescent field, are of great potential for quantum information processing. In this platform, the atoms provide the single-photon nonlinearity and long-lived memory, which are complementary to the excellent passive photonics devices in conventional quantum photonic circuits. In this work, we propose a stable platform for realizing the hybrid photon-atom circuits based on an unsuspended photonic chip. By introducing high-order modes in the microring, a feasible evanescent-field trap potential well ∼ 0.3mK could be obtained by only 10mW-level power in the cavity, compared with 100mW-level power required in the scheme based on fundamental modes. Based on our scheme, stable single atom trapping with relatively low laser power is feasible for future studies on high-fidelity quantum gates, single-photon sources, as well as many-body quantum physics based on a controllab.e atom array in a microcavity. © 2022, CC BY.

关键词： Atoms

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Optimization-driven hierarchical learning framework for wireless powered backscatter-aided relay communications

arXiv

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arXiv 2020年

作者： Gong, Shimin Zou, Yuze Xu, Jing Thai Hoang, Dinh Lyu, Bin Niyato, Dusit School of Intelligent Systems Engineering Sun Yat-sen University Guangzhou510275 China School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan430074 China Faculty of Engineering and Information Technology University of Technology Sydney UltimoNSW2007 Australia Key Laboratory of Ministry of Education in Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Nanjing210003 China School of Computer Science and Engineering Nanyang Technological University Singapore

In this paper, we employ multiple wireless-powered relays to assist information transmission from a multi-antenna access point to a single-antenna receiver. The wireless relays can operate in either the passive mode via backscatter communications or the active mode via RF communications, depending on their channel conditions and energy states. We aim to maximize the overall throughput by jointly optimizing the access point’s beamforming and the relays’ radio modes and operating parameters. Due to the non-convex and combinatorial structure, we develop a novel optimization-driven hierarchical deep deterministic policy gradient (H-DDPG) approach to adapt the beamforming and relay strategies dynamically. The optimization-driven H-DDPG algorithm firstly decomposes the binary relay mode selection into the outer-loop deep Q-network (DQN) algorithm and then optimizes the continuous beamforming and relaying parameters by using the inner-loop DDPG algorithm. Secondly, to improve the learning efficiency, we integrate the model-based optimization into the DDPG framework by providing a better-informed target estimation for DNN training. Simulation results reveal that these two special designs ensure a more stable learning and achieve a higher reward performance, up to nearly 20%, compared to the conventional DDPG approach. Copyright © 2020, The Authors. All rights reserved.

关键词： Deep learning

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Optimization of grant-free NOMA with multiple configured-grants for mURLLC

arXiv

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arXiv 2021年

作者： Liu, Yan Deng, Yansha Elkashlan, Maged Nallanathan, Arumugam Karagiannidis, George K. The Key Laboratory of Ministry of Education in Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Nanjing210003 China School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom Department of Engineering King’s College London London United Kingdom Department of Electrical and Computer Engineering Aristotle University of Thessaloniki Thessaloniki54 124 Greece

Massive Ultra-Reliable and Low-Latency communications (mURLLC), which integrates URLLC with massive access, is emerging as a new and important service class in the next generation (6G) for time-sensitive traffics and has recently received tremendous research attention. However, realizing efficient, delay-bounded, and reliable communications for a massive number of user equipments (UEs) in mURLLC, is extremely challenging as it needs to simultaneously take into account the latency, reliability, and massive access requirements. To support these requirements, the third generation partnership project (3GPP) has introduced enhanced grant-free (GF) transmission in the uplink (UL), with multiple active configured-grants (CGs) for URLLC UEs. With multiple CGs (MCG) for UL, UE can choose any of these grants as soon as the data arrives. In addition, non-orthogonal multiple access (NOMA) has been proposed to synergize with GF transmission to mitigate the serious transmission delay and network congestion problems. In this paper, we develop a novel learning framework for MCG-GF-NOMA systems with bursty traffic. We first design the MCG-GF-NOMA model by characterizing each CG using the parameters: the number of contention-transmission units (CTUs), the starting slot of each CG within a subframe, and the number of repetitions of each CG. Based on the model, the latency and reliability performances are characterized. We then formulate the MCG-GF-NOMA resources configuration problem taking into account three constraints. Finally, we propose a Cooperative Multi-Agent based Double Deep Q-network (CMA-DDQN) algorithm to balance the allocations of the channel resources among MCGs so as to maximize the number of successful transmissions under the latency constraint. Our results show that the MCG-GF-NOMA framework can simultaneously improve the low latency and high reliability performances in massive URLLC. Copyright © 2021, The Authors. All rights reserved.

关键词： Deep learning

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Spectral Efficiency Analysis of Downlink Transmission for Two-Way Cell-Free Massive MIMO System With Few-Bit ADCs

Spectral Efficiency Analysis of Downlink Transmission for Tw...

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IEEE International Symposium on Personal, Indoor and Mobile Radio communications (PIMRC)

作者： Jiaxi Cui Pei Liu Kehao Wang Hongkuan Zhou Yue Zhang Xinghua Sun Stefano Buzzi School of Information Engineering Wuhan University of Technology Wuhan China Ministry of Education Key Lab of Broadband Wireless Communication and Sensor Network Technology (Nanjing University of Posts and Telecommunications) Nanjing China Science and Technology on Thermal Energy and Power Laboratory Wuhan 2nd Ship Design and Research Institute Wuhan China Department of Electronic and Information Engineering Shantou University Shantou China School of Electronics and Communication Engineering Sun Yat-sen University Guangdong China University of Cassino and Southern Lazio Cassino Italy Politecnico di Milano Milano Italy

This paper studies the downlink spectral efficiency of a two-way cell-free massive multiple-input multiple-output system with few-bit analog-to-digital converts (ADCs). By utilizing minimum mean squared error channel estimation method and maximal-ratio transmission precoder, we derive a closed-form expression for the effective downlink signal-to-interference-plus-noise ratio (SINR), which applies to any number of access point (AP) antennas M and distortion factors of ADCs in both AP and user pair sides. Additionally, the obtained analytical expression specializes to the conventional one when the ideal ADCs are adopted. Moreover, the asymptotic performance and power scaling law of the effective SINR in high M regime are studied. The corresponding analysis indicates that increasing M can provide considerable gains to compensate the rate loss caused by non-ideal ADCs and also, appropriately cutting down the pilot power and transmission power will not affect the SINR performance in high M region. Finally, all the theoretical results are verified via simulations.

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Cross-modal communication technology: A survey

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Fundamental Research 2024年

作者： Wei, Xin Wu, Dan Zhou, Liang Guizani, Mohsen School of Communications and Information Engineering Nanjing University of Posts and Telecommunications Nanjing 210003 China Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing 210003 China College of Communications Engineering Army Engineering University of PLA Nanjing 210007 China Machine Learning Department Mohamed Bin Zayed University of Artificial Intelligence Abu Dhabi 999041 United Arab Emirates

In the 5G era and beyond, multi-modal services that integrate audio, visual, and haptic signals are expected to become dominant applications. To support multi-modal services, the concept of cross-modal communications, which involves collab.rative audio-visual and haptic interactions, has emerged. Despite significant research about cross-modal communication technology being conducted, a comprehensive literature review on this topic is lacking. To fill this gap, this paper presents a detailed survey on cross-modal communication technology. First, it provides a highly summarized description of representative research attempts in audio-visual and haptic communications, which serve as the foundation for cross-modal communications. Then, it delves into various aspects of cross-modal communications, including architectural, cross-modal coding, cross-modal transmission, cross-modal signal reconstruction, the essence of semantics, and prototype systems. Finally, it discusses conclusions and future research directions. This paper is expected to promote the theoretical research and practical applications of cross-modal communications. © 2023

关键词： Audio-visual Cross-modal communications Haptic Multi-modal service Semantics

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Beamforming Design and Power Allocation for secure transmission with NOMA

arXiv

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arXiv 2018年

作者： Feng, Youhong Yan, Shihao Yang, Zhen Yang, Nan Yuan, Jinhong Key Lab. of Ministry of Education in Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Nanjing210003 College of Physics and Electronic Information Engineering Anhui Normal University Wuhu241000 China Research School of Engineering Australian National University CanberraACT Australia School of Engineering Macquarie University NSW2109 Australia Research School of Engineering Australian National University CanberraACT2600 Australia School of Electrical Engineering and Telecommunications University of New South Wales SydneyNSW2052 Australia

In this work, we propose a novel beamforming design to enhance physical layer security of a non-orthogonal multiple access (NOMA) system with the aid of artificial noise (AN). The proposed design uses two scalars to balance the useful signal strength and interference at the strong and weak users, which is a generalized version of the existing beamforming designs in the context of physical layer security for NOMA. We determine the optimal power allocation among useful signals and AN together with the two optimal beamforming scalars in order to maximize the secrecy sum rate (SSR). Our asymptotic analysis in the high signal-to-noise ratio regime provides an efficient and near-optimal solution to optimizing the beamforming scalars and power allocation coefficients. Our analysis indicates that it is not optimal to form a beam towards either the strong user or the weak user in NOMA systems for security enhancement. In addition, the asymptotically optimal power allocation informs that, as the transmit power increases, more power should be allocated to the weak user or AN signals, while the power allocated to the strong user keeps constant. Our examination shows that the proposed novel beamforming design can significantly outperform two benchmark schemes. Copyright © 2018, The Authors. All rights reserved.

关键词： Beamforming

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A Smart Content Caching and Replacement Scheme for UAV-Assisted Fog Computing network

A Smart Content Caching and Replacement Scheme for UAV-Assis...

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International Conference on wireless communications and Signal Processing (WCSP)

作者： Xujie Li Jichang Shen Ying Sun Ziya Wang Xuedong Zheng College of Computer and Information Engineering Hohai University Nanjing China National Mobile Communications Research Laboratory Southeast University Nanjing China Key Lab for Wireless Sensor network and Communication Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China Nanjing China-Spacenet Satellite Telecom Co.Ltd China

ISBN: (数字)9781728172361

ISBN: (纸本)9781728172378

For unmanned aerial vehicle (UAV)-assisted fog computing system, content caching is an effective way to reduce network delay. How to smartly sense the future requirement of the user equipment and cache the contents in advance is a big challenge. Meanwhile, the impact of cache content size and other related factors on cache performance are often overlooked, which results in low cache hit ratio. Therefore, this paper proposes a smart caching and caching replacement scheme based on valuation function of content caching for UAV-assisted fog computing network. Firstly, the effect of the content popularity, content size and availab.e cache storage space on system performance is analysed. Then the valuation function combing these factors is defined. Based on the presented valuation function, a smart content caching and caching replacement scheme for UAV-assisted fog computing network is proposed. Finally, the simulation results validate the effectiveness of the proposed scheme. The scheme can be applied into the design the deployment of the UVA-assisted fog computing network.

关键词： Edge computing Cost accounting Unmanned aerial vehicles Performance evaluation Delays Indexes Quality of service

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Traffic Matrix Prediction in SDN based on Spatial-Temporal Residual Graph Convolutional network

Traffic Matrix Prediction in SDN based on Spatial-Temporal R...

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Chinese Control and Decision Conference, CCDC

作者： Xintong Wang Yibo Sun Xuan Wang Enliang Wang Zhixin Sun Post Big Data Technology and Application Engineering Research Center of Jiangsu Province Nanjing University of Posts and Telecommunications Nanjing P.R. China Post Industry Technology Research and Development Center of the State Posts Bureau (Internet of Things Technology) Nanjing University of Posts and Telecommunications Nanjing P.R. China Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing University of Posts and Telecommunications Nanjing P.R. China School of Information Technology and Electrical Engineering The University of Queensland Brisbane Brisbane Australia

Traffic prediction is the basis for dynamic network services and resource optimization. Software Defined networking (SDN) provides a global view for network measurement and management, and a reliable way for network information collection and network traffic prediction. Recently, SDN traffic prediction model enabled by deep learning mainly focuses on mining the temporal correlation of traffic data, while the modeling of its spatial correlation remains to be explored. From the perspective of the problem, a novel Spatial-Temporal Residual Graph Convolutional network (STRGCN) model for SDN Traffic Matrix (TM) prediction is proposed. Combined with SDN network topology, TM prediction is defined as time series data prediction in non-Euclidean space. Temporal Gated-Conv Blocks are based on Gated Convolutional Layer, and Spatial Graph-Conv Blocks are based on Graph Convolutional network (GCN). Through identity mapping between Spatial-Temporal Conv Blocks, the deep spatial and temporal features extraction is implemented. Tested by TM data from CERNET and GÉANT datasets, the accuracy and the timely performance of our model are evaluated. Experimental results suggest that the general performance of STRGCN for TM prediction in SDN is superior to the current deep learning models.

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A WOA Based Switching PID Control for Overhead Crane

A WOA Based Switching PID Control for Overhead Crane

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Chinese Control Conference (CCC)

作者： Haoyong Yu Zhe Sun Yuhua Xu Lei Xu Guangfu Gong Xiangpeng Xie Zhixin Sun Post Industry Technology Research and Development Center of the State Posts Bureau (Internet of Things Technology) Nanjing University of Posts and Telecommunications Nanjing P.R. China Post Big Data Technology and Application Engineering Research Center of Jiangsu Province Nanjing University of Posts and Telecommunications Nanjing China Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing University of Posts and Telecommunications Nanjing P.R. China Anhui Yougu Express Intelligent Technology Co. LTD Nanling Anhui P.R. China

Aiming at the problem that the amplitude of load oscillation is not easy to control in the movement process of overhead crane, this paper designs a switching PID control method based on whale optimization algorithm(WOA) to improve the performance of position control and anti-swing control for overhead crane. WOA is used to better adjust the parameters of PID controllers. The switching control is realized by a switching module, which defaults to the output of the Position PID Controller to provide control force for the trolley. When the absolute value of the load swing angle fed back by the crane system exceeds the warning value, the switching module immediately blocks the output of the Position PID Controller, and uses the Angle PID Controller to determine the control force. In addition, through theoretical analysis and simulation experiments under different conditions, the results verify the effectiveness of the WOA based switching control in position control and anti-swing control for overhead crane. Improve the efficiency and safety of overhead crane in practical industrial applications.

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LQR Control Method based on Improved Antlion Algorithm

LQR Control Method based on Improved Antlion Algorithm

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Chinese Control Conference (CCC)

作者： Zhe Sun Zhi Wen Lei Xu Guangfu Gong Xiangpeng Xie Zhixin Sun Post Industry Technology Research and Development Center of the State Posts Bureau (Internet of Things Technology) Nanjing University of Posts and Telecommunications Nanjing P.R. China Post Big Data Technology and Application Engineering Research Center of Jiangsu Province Nanjing University of Posts and Telecommunications Nanjing China Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing University of Posts and Telecommunications Nanjing P.R. China Anhui Yougu Express Intelligent Technology Co. LTD Nanling Anhui P.R. China

In the face of the increasing demand of crane transportation speed and stability, an improved Ant-lion algorithm is proposed in this paper. On the original basis, the quasi-reverse learning method is used to improve the stability of the algorithm and make the initial data distributed evenly. Furthermore, an elite ant-lion growth mechanism is introduced to accelerate the convergence speed of the simulation and improve the simulation accuracy. Finally, the proposed algorithm is verified in the double pendulum system of crane based on LQR controller, and the feasibility and effectiveness of the proposed algorithm are proved by experiments.

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