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Open AccessArticle

A Novel Spectrum Scheduling Scheme with Ant Colony Optimization Algorithm

by , *,†, and
School of Software, Central South University, Changsha 410075, China
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Algorithms 2018, 11(2), 16;
Received: 28 November 2017 / Revised: 17 January 2018 / Accepted: 26 January 2018 / Published: 29 January 2018
(This article belongs to the Special Issue Evolutionary Computation for Multiobjective Optimization)
Cognitive radio is a promising technology for improving spectrum utilization, which allows cognitive users access to the licensed spectrum while primary users are absent. In this paper, we design a resource allocation framework based on graph theory for spectrum assignment in cognitive radio networks. The framework takes into account the constraints that interference for primary users and possible collision among cognitive users. Based on the proposed model, we formulate a system utility function to maximize the system benefit. Based on the proposed model and objective problem, we design an improved ant colony optimization algorithm (IACO) from two aspects: first, we introduce differential evolution (DE) process to accelerate convergence speed by monitoring mechanism; then we design a variable neighborhood search (VNS) process to avoid the algorithm falling into the local optimal. Simulation results demonstrate that the improved algorithm achieves better performance. View Full-Text
Keywords: spectrum scheduling; ACO; DE; VNS; system utility spectrum scheduling; ACO; DE; VNS; system utility
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Liu, L.; Wang, N.; Chen, Z.; Guo, L. A Novel Spectrum Scheduling Scheme with Ant Colony Optimization Algorithm. Algorithms 2018, 11, 16.

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