A Survey of Cognitive Radio Reconfigurable Antenna Design and Proposed Design using Genetic Algorithm

Aizaz, Zainab; Sinha, Poonam

doi:10.5120/ijca2016908659

Cited by 3 publications

(2 citation statements)

References 15 publications

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“…Genetic algorithm is based on the concept of biological gene and chromosome 12 . This algorithm adopts the problem and solution of bit string coding based on chromosome similarity of biological system.…”

Section: Optimization Scheme Of Communication Network Based On Geneti...mentioning

confidence: 99%

Reliability analysis and optimization of computer communication network based on genetic algorithm

Song

2020

Int J Communication

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Summary In this paper, the design of reliable communication network is solved by genetic algorithm. In order to solve this problem, we must first provide the lowest acceptable network reliability. There are many methods to satisfy the network reliability constraints. The penalty function may produce an invalid solution, so it is not suitable to solve the problem. In order to overcome these difficulties, this paper proposes a heuristic repair method, which is based on the number of spanning trees in the graph. Compared with the heuristic maintenance method with lower cost, this method can generate a better solution with less computation. When the population size is 25, the hybridization rate is 0.96, and the mutation rate is 0.07, the best results can be obtained. This paper analyzes the node fault, grasps the influence rule of the fault on the network, and improves the network reliability. This paper summarizes and classifies the failure modes of communication network nodes. Combined with the classic BA network model in the complex network theory, through the simulation design of MATLAB and OPNET, the influence of node function failure and performance failure on network reliability is studied.

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Section: Optimization Scheme Of Communication Network Based On Geneti...mentioning

confidence: 99%

Reliability analysis and optimization of computer communication network based on genetic algorithm

Song

2020

Int J Communication

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“…e genetic algorithm (GA) is used to determine optimized solutions using biologically stimulated techniques, such as natural selection, genetic inheritance, recombination, and crossover [26,27]. e remarkable generality and versatility of the GA make it useful in a variety of settings in the wireless communication to reduce the error probability of the CSS [28,29].…”

Section: Introductionmentioning

confidence: 99%

Robust Spectrum Sensing via Double-Sided Neighbor Distance Based on Genetic Algorithm in Cognitive Radio Networks

Gul

Khan

Kim

et al. 2020

Mobile Information Systems

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In cognitive radio networks (CRNs), secondary users (SUs) can access vacant spectrum licensed to a primary user (PU). Therefore, accurate and timely spectrum sensing is vital for efficient utilization of available spectrum. The sensing result at each SU is unauthentic due to fading, shadowing, and receiver uncertainty problems. Cooperative spectrum sensing (CSS) provides a solution to these problems. In CSS, false sensing reports at the fusion center (FC) received from malicious users (MUs) drastically degrade the performance of cooperation in PU detection. In this paper, we propose a robust spectrum sensing scheme to minimize the effects of false sensing reports by MUs. The proposed scheme focuses on double-sided neighbor distance (DSND) based on genetic algorithm (GA) in order to filter out the MU sensing reports in CSS. The simulation results show that the sensing results are more accurate and reliable for the proposed GA majority-voting hard decision fusion (GAMV-HDF) and GA weighted soft decision fusion (GAW-SDF) compared to conventional equal gain combination soft decision fusion (EGC-SDF), maximum gain combination soft decision fusion (MGC-SDF), and majority-voting hard decision fusion (MV-HDF) schemes in the presence of MUs.

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Topology optimization of computer communication network based on improved genetic algorithm

Ai¹,

Fan²,

Zhang³

et al. 2022

Journal of Intelligent Systems

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The topology optimization of computer communication network is studied based on improved genetic algorithm (GA), a network optimization design model based on the establishment of network reliability maximization under given cost constraints, and the corresponding improved GA is proposed. In this method, the corresponding computer communication network cost model and computer communication network reliability model are established through a specific project, and the genetic intelligence algorithm is used to solve the cost model and computer communication network reliability model, respectively. It has been proved that GA can solve the complex problems of computer working environment better, which is 80% higher than the general algorithm, and can select the optimal scheme pertinently.

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A Survey of Cognitive Radio Reconfigurable Antenna Design and Proposed Design using Genetic Algorithm

Cited by 3 publications

References 15 publications

Reliability analysis and optimization of computer communication network based on genetic algorithm

Reliability analysis and optimization of computer communication network based on genetic algorithm

Robust Spectrum Sensing via Double-Sided Neighbor Distance Based on Genetic Algorithm in Cognitive Radio Networks

Topology optimization of computer communication network based on improved genetic algorithm

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