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Decomposition-based learning in drone-assisted wireless-powered mobile edge computing networks

Digital communications and networks 2024年第6期10卷 1769-1781页

作者： Xiaoyi Zhou Liang Huang Tong Ye Weiqiang Sun State Key Laboratory of Advanced Optical Communication Systems and Networks Shanghai Jiao Tong UniversityShanghai 200240China College of Computer Science and Technology Zhejiang University of TechnologyHangzhou 310058China

This paper investigates the multi-Unmanned Aerial Vehicle(UAV)-assisted wireless-powered Mobile Edge Computing(MEC)system,where UAVs provide computation and powering services to mobile *** aim to maximize the number of completed computation tasks by jointly optimizing the offloading decisions of all terminals and the trajectory planning of all *** action space of the system is extremely large and grows exponentially with the number of *** this case,single-agent learning will require an overlarge neural network,resulting in insufficient ***,the offloading decisions and trajectory planning are two subproblems performed by different executants,providing an opportunity for *** thus adopt the idea of decomposition and propose a 2-Tiered Multi-agent Soft Actor-Critic(2T-MSAC)algorithm,decomposing a single neural network into multiple small-scale *** the first tier,a single agent is used for offloading decisions,and an online pretrained model based on imitation learning is specially designed to accelerate the training process of this *** the second tier,UAVs utilize multiple agents to plan their *** agent exerts its influence on the parameter update of other agents through actions and rewards,thereby achieving joint *** results demonstrate that the proposed algorithm can be applied to scenarios with various location distributions of terminals,outperforming existing benchmarks that perform well only in specific *** particular,2T-MSAC increases the number of completed tasks by 45.5%in the scenario with uneven terminal ***,the pretrained model based on imitation learning reduces the convergence time of 2T-MSAC by 58.2%.

关键词： Mobile-edge computing Multi-agent reinforcement learning Offloading decision Trajectory planning Unmanned aerial vehicle Wireless power transfer

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Combined QoS Analysis of Smart Distribution Grids with Constraint Satisfaction Problem and Network Calculus 14

Combined QoS Analysis of Smart Distribution Grids with Const...

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14th IEEE International Conference on communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2023

作者： Alshra'a, Abdullah S. Vietz, Matthias Hielscher, Kai-Steffen Oest, Frauke Lehnhoff, Sebastian German, Reinhard Friedrich-Alexander-University Computers Networks and Communication Systems Germany University of Oldenburg Department of Computer Science Germany

ISBN: (纸本)9781665455541

The expansion of renewable energies requires implementing Smart Grid Services (SGSs) in the distribution grid. Analytical verification of the SGSs' Quality of Service (QoS) requirements is crucial for reliable operation. This paper proposes a two-step approach: a constraint satisfaction problem (CSP) considers network infrastructure and resource allocations to find candidates' solutions. Then, the solutions are evaluated using Network Calculus (NC) to calculate delay bounds at the worst-case and compare them to the requirements. If necessary, alternative solutions are generated. The NC framework is adjustable and considers different service priorities by implementing scheduling policies such as strict priority, weighted fair queuing, weighted round robin, and deficit round robin. In the end, the best-performing parameters are derived for a sample network and the results manifest that the NC framework can be used to analyze random communication networks. © 2023 IEEE.

关键词： Quality of service

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Intelligent indoor metasurface robotics

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National science Review 2023年第8期10卷 20-32页

作者： Hanting Zhao Shengguo Hu Hongrui Zhang Zhuo Wang Hao Dong Philipp del Hougne Tie Jun Cui Lianlin Li State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Center on Frontiers of Computing Studies School of Computer Science Peking University The French National Centre for Scientific Research(CNRS) University of Rennes State Key Laboratory of Millimeter Waves Southeast University

Intelligent indoor robotics is expected to rapidly gain importance in crucial areas of our modern society such as at-home health care and factories. Yet, existing mobile robots are limited in their ability to perceive and respond to dynamically evolving complex indoor environments because of their inherently limited sensing and computing resources that are, moreover, traded off against their cruise time and payload. To address these formidable challenges, here we propose intelligent indoor metasurface robotics(I2MR),where all sensing and computing are relegated to a centralized robotic brain endowed with microwave perception; and I2MR's limbs(motorized vehicles, airborne drones, etc.) merely execute the wirelessly received instructions from the brain. The key aspect of our concept is the centralized use of a computation-enabled programmable metasurface that can flexibly mold microwave propagation in the indoor wireless environment, including a sensing and localization modality based on configurational diversity and a communication modality to establish a preferential high-capacity wireless link between the I2MR's brain and limbs. The metasurface-enhanced microwave perception is capable of realizing low-latency and high-resolution three-dimensional imaging of humans, even around corners and behind thick concrete walls, which is the basis for action decisions of the I2MR's brain. I2MR is thus endowed with real-time and full-context awareness of its operating indoor environment. We implement, experimentally, a proof-of-principle demonstration at ～2.4 GHz, in which I2MR provides health-care assistance to a human inhabitant. The presented strategy opens a new avenue for the conception of smart and wirelessly networked indoor robotics.

关键词： intelligent metasurfaces intelligent robotics edge devices IoT 6G

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A low-fabrication-temperature, high-gain chip-scale waveguide amplifier

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science China(Information sciences) 2022年第6期65卷 247-255页

作者： Bo WANG Peiqi ZHOU Xingjun WANG Yandong HE State Key Laboratory of Advanced Optical Communication Systems and Networks Department of ElectronicsSchool of Electronics Engineering and Computer Science Peking University Institute of Microelectronics School of Electronics Engineering and Computer Science Peking University Frontier Science Center for Nano-optoelectronics Peking University Peking University Yangtze Delta Institute of Optoelectronics Peng Cheng Laboratory

The increasing prevalence of integrated on-chip optoelectronic devices has identified serious issues regarding inter-device transmission and coupling losses, highlighting an urgent need for on-chip waveguide amplifiers to compensate for these losses. Compared with other Er-based optical materials, erbium silicate is ideally suited to high-efficiency on-chip amplifiers and lasers because of its extremely high Er3+concentration(1022cm-3). Nevertheless, erbium silicate must be annealed above 1000℃ to crystallize and activate the Er3+, which damages other on-chip optoelectronic components and is not conducive to device ***, we report a low-fabrication-temperature, high-luminescence-efficiency gain material by adding Bi2O3to an erbium-ytterbium silicate mixed film. Our experiments demonstrate that the proposed film crystallizes at 600℃ while the activation of Er3+is also achieved, which is the lowest activation temperature of on-chip waveguide amplifier to our knowledge. This material forms the basis for a new chip-scale waveguide amplifier design, with a theoretical multi-energy-level model of Bi-Er-Yb in the mixed thin films used to analyze its signal enhancement properties. We achieve a peak on-chip gain of 23 dB in a 3.3-mm-long waveguide under the pump and signal powers of 300 mW and 1 μW, respectively. These results highlight the potential of the proposed material for realizing on-chip amplifiers and lasers for large-scale nanophotonic integrated circuits.

关键词： photonic circuit integration low fabrication temperature high gain rare earth material waveguide amplifier

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Traffic-aware Dedicated Path Protection in Elastic Optical networks 12

Traffic-aware Dedicated Path Protection in Elastic Optical N...

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12th International Workshop on Resilient networks Design and Modeling, RNDM 2022

作者： Goscien, Roza Wroclaw University of Science and Technology Faculty of Information and Communication Technology Department of Systems and Computer Networks Wroclaw Poland

ISBN: (数字)9781665486774

ISBN: (纸本)9781665486774

The increasing popularity of telecommunication networks and their ubiquitous support for our every-day activities impose their high performance and uninterrupted operation. It might be achieved for instance by implementing highly efficient and survivable routing algorithms. In this paper, we study the problem of allocating dynamic traffic requests (representing four transmission types - city-city, city-data center, data center-city, data center-data center) in elastic optical network and providing their protection against a single link failure. To this end, we propose a dedicated traffic-aware approach, which combines dedicated path protection scheme and a traffic forecasting model. Then, we perform simulations to: (i) tune the proposed approach and (ii) evaluate its performance based on the comparison with reference methods. The results show a high efficiency of the proposed allocation scheme, which outperforms the reference algorithms. Particularly, it allowed to reduce the bandwidth blocking probability by up to 1.49% and serve up to 15.321 Tbps more traffic. © 2022 IEEE.

关键词： Blocking probability

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A Non-deep Approach to Classifying Movie Genres Based on Multimodal Data 13th

A Non-deep Approach to Classifying Movie Genres Based on M...

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13th International Conference on Image Processing and communications, IP and C 2023, 13th International Conference on computer Recognition systems, CORES 2023

作者： Niedziólka, Pawel Zyblewski, Pawel Department of Systems and Computer Networks Faculty of Information and Communication Technology Wroclaw University of Science and Technology Wybrzeże Wyspiańskiego 27 Wroclaw50-370 Poland

ISBN: (纸本)9783031416293

Multimodal data processing has recently become popular due to technological advances and easier access to real video, audio, images, or text data. This data type is often processed using deep neural networks associated with high time and computational complexity. The present work addresses the problem of classifying a multimodal MM-IMDb dataset, representing the problem of recognizing a movie genre based on a poster and a brief description of the plot. For experiments, 20 binary subsets were separated, from which features were then extracted. Features from the text were obtained using the tf-idf method, while the posters were reduced to a single color. computer experiments on the resulting tabular data were conducted separately on both modalities, as in the concatenated feature space. The results confirmed that classical approaches to feature extraction could allow satisfactory quality classification of multimodal data to be obtained even when using relatively simple pattern recognition algorithms. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Classification (of information)

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Multidimensional Voronoi Constellations vs. Short Blocklength Probabilistic Shaping: A Comparison for Multilevel Coding Approach

Multidimensional Voronoi Constellations vs. Short Blocklengt...

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2024 Asia communications and Photonics Conference, ACP 2024 and International Conference on Information Photonics and Optical communications, IPOC 2024

作者： Sheng, Yajie Chen, Bin Lei, Yi Deng, Jingxin Xu, Jiwei Fu, Mengfan Zhuge, Qunbi Li, Shen Department of Computer Science and Information Engineering Hefei University of Technology Hefei China State Key Laboratory of Advanced Optical Communication Systems and Networks Department of Electronic Engineering Shanghai Jiao Tong University Shanghai China Department of Electrical and Computer Engineering Université Laval Québec Canada

Performance of concatenated multilevel coding with probabilistic shaping (PS) and Voronoi constellations (VCs) is analysed over AWGN channel. Numerical results show that VCs provide up to 1.3 dB SNR gains over PS-QAM ... 详细信息

ISBN: (纸本)9798350379266

关键词： Probability distributions

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Extending the Reach of Optical Interconnects with Advanced Coded Modulation

Extending the Reach of Optical Interconnects with Advanced C...

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2023 Opto-Electronics and communications Conference, OECC 2023

作者： Lei, Yi Wang, Xiang Lu, Qi Chen, Bin Hefei University of Technology School of Computer Science and Information Engineering Hefei China Shanghai Jiao Tong University State Key Laboratory of Advanced Optical Communication Systems and Networks China

An advanced coded modulation is proposed based on improved staircase codes using marked bits and geometrically-shaped constellations. Up to 0.95 dB SNR gain and 8.6% reach increase are achieved for beyond 800G data ce... 详细信息

ISBN: (纸本)9781665462136

关键词： Stairs

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LLM4CP:Adapting Large Language Models for Channel Prediction

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Journal of communications and Information networks 2024年第2期9卷 113-125页

作者： Boxun Liu Xuanyu Liu Shijian Gao Xiang Cheng Liuqing Yang State Key Laboratory of Advanced Optical Communication Systems and Networks School of ElectronicsPeking UniversityBeijing 100871China Internet of Things Thrust The Hong Kong University of Science and Technology(Guangzhou)Guangzhou 511400China Internet of Things Thrust and Intelligent Transportation Thrust The Hong Kong University of Science and Technology(Guangzhou)Guangzhou 511400China Department of Electronic and Computer Engineering and Department of Civil and Environmental Engineering The Hong Kong University of Science and TechnologyHong KongChina

Channel prediction is an effective approach for reducing the feedback or estimation overhead in massive multi-input multi-output (m-MIMO) systems. However, existing channel prediction methods lack precision due to model mismatch errors or network generalization issues. Large language models (LLMs) have demonstrated powerful modeling and generalization abilities, and have been successfully applied to cross-modal tasks, including the time series analysis. Leveraging the expressive power of LLMs, we propose a pre-trained LLM-empowered channel prediction(LLM4CP)method to predict the future downlink channel state information (CSI) sequence based on the historical uplink CSI sequence. We fine-tune the network while freezing most of the parameters of the pre-trained LLM for better cross-modality knowledge transfer. To bridge the gap between the channel data and the feature space of the LLM,preprocessor, embedding, and output modules are specifically tailored by taking into account unique channel characteristics. Simulations validate that the proposed method achieves state-of-the-art (SOTA) prediction performance on full-sample, few-shot, and generalization tests with low training and inference costs.

关键词： channel prediction massive multi-input multi-output(m-MIMO) large language models(LLMs) fine-tuning time-series

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Analog parallel processor for broadband multifunctional integrated system based on silicon photonic platform

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Light(science & Applications) 2025年第3期14卷 746-756页

作者： Na Qian Defu Zhou Haowen Shu Ming Zhang Xingjun Wang Daoxin Dai Xiao Deng Weiwen Zou State Key Laboratory of Advanced Optical Communication Systems and Networks Intelligent Microwave Lightwave Integration Innovation Center(imLic)Department of Electronic EngineeringShanghai Jiao Tong UniversityShanghaiChina State Key Laboratory of Advanced Optical Communications System and Networks Department of ElectronicsSchool of Electronics Engineering and Computer SciencePeking UniversityBejingChina State Key Laboratory of Extreme Photonics and Instrumentation College of Optical Science and EngineeringInternational Research Center for Advanced PhotonicsZhejiang UniversityHangzhouChina

Sharing the hardware platform between diverse information systems to establish full cooperation among different functionalities has attracted substantial ***,broadband multifunctional integrated systems with large operating frequency ranges are challenging due to the bandwidth and computing speed restrictions of electronic ***,we report an analog parallel processor(APP)based on the silicon photonic platform that directly discretizes and parallelizes the broadband signal in the analog *** APP first discretizes the signal with the optical frequency comb and then adopts optical dynamic phase interference to reassign the analog signal into 2N parallel *** photonic analog parallelism,data rate and data volume in each sequence are simultaneously compressed,which mitigates the requirement on each parallel computing ***,the fusion of the outputs from each computing core is equivalent to directly processing broadband *** the proof-of-concept experiment,two-channel analog parallel processing of broadband radar signals and high-speed communication signals is implemented on the single photonic integrated *** bandwidth of broadband radar signal is 6 GHz and the range resolution of 2.69 cm is *** wireless communication rate of 8 Gbit/s is also *** the bandwidth and speed limitations of the single-computing core along with further exploring the multichannel potential of this architecture,we anticipate that the proposed APP will accelerate the development of powerful optoelectronic processors as critical support for applications such as satellite networks and intelligent driving.

关键词： analog parallel processor sharing hardware platform multifunctional integrated systems establish full cooperation different functionalities analog parallel processor app based silicon photonic platform electronic circuitryherewe broadband signal

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