Network access and spectrum allocation in next-generation multi-heterogeneous networks

In a multi-heterogeneous network with dense deployment and convergence environment, how to efficiently and reasonably allocate idle spectrum resources of the primary network to meet the diversified business demands of secondary users is a difficult problem. In this article, with the goal of maximizi...

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Main Authors: Xiaoqing Dong, Lianglun Cheng, Gengzhong Zheng, Tao Wang
Format: Article
Language:English
Published: SAGE Publishing 2019-08-01
Series:International Journal of Distributed Sensor Networks
Online Access:https://doi.org/10.1177/1550147719866140
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spelling doaj-84f44a25f63b4e23b1a0ddd4bb79e0b32020-11-25T03:51:43ZengSAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772019-08-011510.1177/1550147719866140Network access and spectrum allocation in next-generation multi-heterogeneous networksXiaoqing Dong0Lianglun Cheng1Gengzhong Zheng2Tao Wang3School of Computers, Guangdong University of Technology, Guangzhou, ChinaSchool of Computers, Guangdong University of Technology, Guangzhou, ChinaSchool of Physics and Electronic Engineering, Hanshan Normal University, Chaozhou, ChinaSchool of Automation, Guangdong University of Technology, Guangzhou, ChinaIn a multi-heterogeneous network with dense deployment and convergence environment, how to efficiently and reasonably allocate idle spectrum resources of the primary network to meet the diversified business demands of secondary users is a difficult problem. In this article, with the goal of maximizing the total transmission rate and minimizing the total cost, a dual-objective optimization mathematical model for network selection and idle spectrum allocation is established in the context of comprehensive consideration of the diversity of spectrum resource attributes and the diversification of secondary users’ business needs. Based on this, two kinds of technical paths to solve the complex network selection and spectrum allocation problem are applied in this article. The first is the simplification method. By preprocessing of objective function, constraint simplification, and standardization, the complex spectrum allocation problem is transformed into a standard form of the 01 programming problem, and the solution is obtained by an improved Hungarian algorithm. Second, an intelligent optimization algorithm named improved non-dominated sorting genetic algorithm II is proposed, which combines the interference constraints of the primary network and the service quality requirements of the secondary users into the objective value evaluation of non-dominated sorting, and corrects the chromosomes that do not meet the constraints. And then makes a decision selection on the optimal solution set to select a compromise solution. Finally, methods proposed in this article are compared with the multi-objective artificial bee colony algorithm through experiments. Experimental results show that the simplified method has higher efficiency, and the improved non-dominated sorting genetic algorithm II can get higher transmission rate, especially the transmission rate–priority strategy.https://doi.org/10.1177/1550147719866140
collection DOAJ
language English
format Article
sources DOAJ
author Xiaoqing Dong
Lianglun Cheng
Gengzhong Zheng
Tao Wang
spellingShingle Xiaoqing Dong
Lianglun Cheng
Gengzhong Zheng
Tao Wang
Network access and spectrum allocation in next-generation multi-heterogeneous networks
International Journal of Distributed Sensor Networks
author_facet Xiaoqing Dong
Lianglun Cheng
Gengzhong Zheng
Tao Wang
author_sort Xiaoqing Dong
title Network access and spectrum allocation in next-generation multi-heterogeneous networks
title_short Network access and spectrum allocation in next-generation multi-heterogeneous networks
title_full Network access and spectrum allocation in next-generation multi-heterogeneous networks
title_fullStr Network access and spectrum allocation in next-generation multi-heterogeneous networks
title_full_unstemmed Network access and spectrum allocation in next-generation multi-heterogeneous networks
title_sort network access and spectrum allocation in next-generation multi-heterogeneous networks
publisher SAGE Publishing
series International Journal of Distributed Sensor Networks
issn 1550-1477
publishDate 2019-08-01
description In a multi-heterogeneous network with dense deployment and convergence environment, how to efficiently and reasonably allocate idle spectrum resources of the primary network to meet the diversified business demands of secondary users is a difficult problem. In this article, with the goal of maximizing the total transmission rate and minimizing the total cost, a dual-objective optimization mathematical model for network selection and idle spectrum allocation is established in the context of comprehensive consideration of the diversity of spectrum resource attributes and the diversification of secondary users’ business needs. Based on this, two kinds of technical paths to solve the complex network selection and spectrum allocation problem are applied in this article. The first is the simplification method. By preprocessing of objective function, constraint simplification, and standardization, the complex spectrum allocation problem is transformed into a standard form of the 01 programming problem, and the solution is obtained by an improved Hungarian algorithm. Second, an intelligent optimization algorithm named improved non-dominated sorting genetic algorithm II is proposed, which combines the interference constraints of the primary network and the service quality requirements of the secondary users into the objective value evaluation of non-dominated sorting, and corrects the chromosomes that do not meet the constraints. And then makes a decision selection on the optimal solution set to select a compromise solution. Finally, methods proposed in this article are compared with the multi-objective artificial bee colony algorithm through experiments. Experimental results show that the simplified method has higher efficiency, and the improved non-dominated sorting genetic algorithm II can get higher transmission rate, especially the transmission rate–priority strategy.
url https://doi.org/10.1177/1550147719866140
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