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981
Optimal QoM in Multichannel Wireless Networks Based on MQICA
Published 2013-06-01“…In this paper, a Multiple-Quantum-Immune-Clone-Algorithm- (MQICA-) based solution was proposed to achieve the optimal channel allocation. …”
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982
Security-driven service caching and computation offloading strategy in air-ground collaborative edge computing networks
Published 2025-07-01“…Considering dual secrecy rate constraints and resource limitations suffered by a UAV server, UAV service caching, computation offloading decisions of ground devices, resource allocation, and UAV deployment were jointly optimized to minimize the task completion delay of ground devices. …”
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983
Joint Caching and Computation in UAV-Assisted Vehicle Networks via Multi-Agent Deep Reinforcement Learning
Published 2025-06-01“…This requires balancing system energy consumption and resource allocation fairness while maximizing cache hit rate and minimizing task latency. …”
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984
Machine Learning Based Flexible Transmission Time Interval Scheduling for eMBB and uRLLC Coexistence Scenario
Published 2019-01-01“…When multi-scenario services coexist in the 5G networks, exploring optimized resource scheduling and allocation strategies become a critical issue. …”
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985
Gemini: A Cascaded Dual-Agent DRL Framework for Task Chain Planning in UAV-UGV Collaborative Disaster Rescue
Published 2025-07-01“…Specifically, this framework comprises a chain selection agent and a resource allocation agent: The chain selection agent plans paths for task chains, and the resource allocation agent distributes platform loads along generated paths. …”
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986
Security performance analysis for cell-free massive multiple-input multiple-output system with multi-antenna access points deployment in presence of active eavesdropping
Published 2022-08-01“…Compared to equal power allocation, the proposed power control algorithm can further boost the network security performance.…”
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987
Optimization, Design, and Implementation of Biodiversity-Focused Fisheries Survey Stations: A Case Study of the Coastal Waters of Maoming
Published 2024-12-01“…This package, based on a genetic algorithm, can determine the optimal stratification, sample size, and sample allocation to meet precision constraints in the presence of multiple stratification variables and multiple target variables. …”
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988
Content-based dynamic superframe adaptation for Internet of Medical Things
Published 2020-02-01“…This article presents a content-based dynamic superframe adaptation algorithm for the low-powered Internet of Medical Things devices to address the resource utilization challenges. …”
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989
NOMA-based secure computation offloading in marine Internet of things
Published 2024-09-01“…Considering the requirements such as energy constraints and security transmission, the offloading ratio, transmitting power, computation resource allocation and NOMA cluster selection were jointly optimized with the objective of minimizing the maximum task processing latency. …”
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990
Constrained Restless Bandits for Dynamic Scheduling in Cyber-Physical Systems
Published 2024-01-01“…CRMABs can be applied to resource allocation problems in cyber-physical systems, including sensor/relay scheduling. …”
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991
Optimizing sum rates in IoT networks: A novel IRS-NOMA cooperative system
Published 2025-06-01“…By leveraging our optimization algorithm, the proposed system ensures efficient resource allocation, achieving superior spectral efficiency and fairness among users compared to traditional models. …”
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992
Cluster channel equalization using adaptive sensing and reinforcement learning for UAV communication
Published 2024-12-01“…Simulation results demonstrate that the U-FRQL-EA algorithm effectively reduces the system’s bit error rate, enhances communication quality, and optimizes network resource utilization, offering a novel solution for improving the performance of uncrewed aerial vehicle communication systems.…”
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993
Deep Reinforcement Learning-Based Two-Phase Hybrid Optimization for Scheduling Agile Earth Observation Satellites
Published 2025-06-01“…To mitigate problem complexity, the action space is decomposed into two interdependent decision layers: task sequencing and resource allocation. Given the resource occupation constraints during action execution, a novel reward function is designed by integrating resource occupation utility into the immediate reward mechanism. …”
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994
Deep Learning-Driven Geospatial Modeling of Elderly Care Accessibility: Disparities Across the Urban-Rural Continuum in Central China
Published 2025-04-01“…Taking Changsha as a case study, this research constructs an accessibility evaluation system based on the 15-min life circle theory, utilizing multi-source data. Spatial weighting characteristics of elderly care facility locations were analyzed through machine learning algorithms, and service coverage disparities between urban districts and suburban towns were assessed under 5-, 10-, and 15-min walking thresholds. …”
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995
Integrating Machine Learning for Enhanced Agricultural Productivity: A Focus on Bananas and Arecanut in the Context of India’s Economic Growth
Published 2024-10-01“…Assist yield projections may provide governments and policymakers with valuable information to make well-informed choices about food security, import–export policies, and resource allocation. It facilitates national- and regional-level food supply planning. …”
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996
Bit Rate Optimization with MMSE Detector for Multicast LP-OFDM Systems
Published 2012-01-01“…We propose a new resource allocation algorithm with minimum mean square error (MMSE) detector for multicast linear precoded orthogonal frequency division multiplexing (LP-OFDM) systems. …”
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997
Study on multi-satellite cooperative spectrum cognitive method integrating Stackelberg game and federated learning
Published 2024-02-01“…To solve the problem of the weak spectrum-cognitive ability caused by monitoring angle, direction resolution, limited processing ability and peak power for a low-earth-orbit (LEO) satellite, a multi-satellite cooperative spectrum cognitive method integrating Stackelberg game and federated learning was proposed.Firstly, considering the available computing resource, cognitive performance, processing and transmission delay of each spectrum cognitive satellite, a cooperative-satellite selection and computing-resource allocation algorithm was built for multiple spectrum-cognitive tasks.Secondly, based on the selected satellites and the allocated computing resources, a low-complexity multi-satellite cooperative spectrum cognitive strategy was further designed, which could automatically sense the spectrum holes, and detect interference as well as identify the modulation mode.Simulation results demonstrate that compared to the single-node cognitive method, the designed multi-satellite cooperative spectrum cognitive strategy can obtain a better cognitive performance.Moreover, comparing with the existing model, the model utilized in the designed strategy can effectively achieve 96.69% and 93.32% lower number of parameters and required floating point operations per second, whilst maintaining the performance.…”
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998
Using random subcarrier weighting for multi-carrier systems physical layer security
Published 2012-10-01“…An OFDM security model and a physical layer security transmission scheme were proposed for multi-carrier systems to achieve low probability of interception.In contrast to the resource allocation algorithm which would be disabled at the low SNR,this method designed the subcarrier transmission weighting vectors to randomize the eavesdropper’s signals but not the authorized receiver’s signals.The channel state information was the only character to distinguish authorized receivers and eavesdroppers,which was conducted to guide the weighting vectors design.Simulation results show that the proposed method guarantees that authorized receiver performs transmitted reference demodulation successfully,while the eavesdroppers can not detect the transmitted symbols.…”
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999
Joint optimization of edge computing and caching in NDN
Published 2022-08-01“…Named data networking (NDN) is architecturally easier to integrate with edge computing as its routing is based on content names and its nodes have caching capabilities.Firstly, an integrated framework was proposed for implementing dynamic coordination of networking, computing and caching in NDN.Then, considering the variability of content popularity in different regions, a matrix factorization-based algorithm was proposed to predict local content popularity, and deep reinforcement learning was used to solve the the problem of joint optimization for computing and caching resource allocation and cache placement policy with the goal of maximizing system operating profit.Finally, the simulation environment was built in ndnSIM.The simulation results show that the proposed scheme has significant advantages in improving cache hit rate, reducing the average delay and the load on the remote servers.…”
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Article -
1000
Using random subcarrier weighting for multi-carrier systems physical layer security
Published 2012-10-01“…An OFDM security model and a physical layer security transmission scheme were proposed for multi-carrier systems to achieve low probability of interception.In contrast to the resource allocation algorithm which would be disabled at the low SNR,this method designed the subcarrier transmission weighting vectors to randomize the eavesdropper’s signals but not the authorized receiver’s signals.The channel state information was the only character to distinguish authorized receivers and eavesdroppers,which was conducted to guide the weighting vectors design.Simulation results show that the proposed method guarantees that authorized receiver performs transmitted reference demodulation successfully,while the eavesdroppers can not detect the transmitted symbols.…”
Get full text
Article