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An intelligent resource management scheme for SDF-based cooperative spectrum sensing in the presence of primary user emulation attack

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COMPUTERS & ELECTRICAL ENGINEERING 2018年 69卷 555-571页

作者： Das, Deepa Das, Susmita NIT Dept Elect Engn Rourkela India

This paper focuses on designing an energy-efficient cognitive radio network (CRN) in the presence of a primary user emulation attacker. The approach requires suitable resource management schemes that help in maximizing energy efficiency (EE) of the secondary network while providing sufficient protection to the primary network. Hence, we propose a secondary users (SUs) selection algorithm for maximizing system throughput while ensuring spectrum sensing accuracy. Then the sensing time is evaluated for obtaining maximum throughput, minimum delay and minimum false alarm probability. Further, the non-linear EE maximization problem associated with the non-convex constraints is solved by our proposed novel iterative resource allocation (nira) algorithm to jointly optimize both sensing time and transmission power of the secondary network within which the fractional EE is transferred to convex programming by employing the Dinkelbach method in the outer layer and the constraints are addressed by dual decomposition and Difference of convex (DC) programming method. Simulation results validate the effectiveness of our proposed approaches, and the impact of different system parameters is also studied. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Cognitive radio network Energy efficiency PUEA nira algorithm DC programming

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A Novel Resource Allocation for Energy-Efficient Cognitive Radio 12

A Novel Resource Allocation for Energy-Efficient Cognitive R...

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12 IEEE Int C Elect Energy Env Communications Computer Control

作者： Das, Deepa Das, Susmita NIT Dept Elect Engn Rourkela India

ISBN: (纸本)9781467365406

This paper investigates the energy efficiency (EE) maximization problem in soft decision fusion (SDF) based cooperative spectrum sensing (CSS) system framework. Specifically, we emphasize in optimizing the sensing time and power allocation to the secondary users (SUs) with optimally selected users for both single threshold and double threshold based sensing scheme under the constraint of transmit power, interference to the primary user (PU), outage of SUs and probability of false alarm. To this end, we first propose an efficient algorithm for selecting optimal number of SUs and suitable users that take part in spectrum sensing and data transmission. Then, we formulate the EE maximization problem by using a novel iterative resource allocation (nira) algorithm which is based on parametric transformation method. The aid of Lagrangian duality theorem with this novel iterative process jointly helps in optimizing the sensing time and transmit power allocation to the SUs. Extensive simulation results are carried out to validate our proposed algorithm and demonstrate the effectiveness by comparing its performance with the other existing scheme.

关键词： energy efficiency cooperative spectrum sensing SDF single and double threshold nira algorithm Lagrangian duality theorem

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Simulation Interventions for Depressive Symptoms in Chinese Adolescents: Insights from NodeIdentifyR algorithm 24

Simulation Interventions for Depressive Symptoms in Chinese ...

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2nd International Conference on Educational Knowledge and Informatization, EKI 2024

作者： Huang, Ningning Fang, Yuan Chen, Zhiyan CAS Key Laboratory of Mental Health Institute of Psychology Chinese Academy of Sciences China Department of Psychology University of Chinese Academy of Sciences China

ISBN: (纸本)9798400710230

Using the NodeIdentifyR algorithm (nira) in R programming language, this study aimed to identify potential intervention targets by simulating interventions. It examined how alleviating or aggravating specific symptoms impacts the activation of the overall depressive symptom network in Chinese adolescents. A total of 3347 valid participants aged 10 to 18 years were recruited from China (Mage = 13.79, SD = 2.56;52.94% female). "Feel lonely", "sad mood", and "low spirit" were identified as central symptoms. "Feel happy" emerged as a potential treatment target for alleviating overall depressive symptoms, and "feel lonely" was identified as potential prevention target for addressing depressive symptoms in adolescents. These findings emphasize the significance of computational modeling in enhancing the understanding of psychopathology, offering insights and cost-effective recommendations for future interventions aimed at addressing depressive symptoms in adolescents. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Chinese adolescents Depressive symptoms Network analysis nira algorithm

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