Jinli Zhang, Jie Li, Mingjiao Cai, Dining Li, Qiang Wang
{"title":"The 5G NOMA networks planning based on the multi-objective evolutionary algorithm","authors":"Jinli Zhang, Jie Li, Mingjiao Cai, Dining Li, Qiang Wang","doi":"10.1109/CIS52066.2020.00021","DOIUrl":null,"url":null,"abstract":"This paper studies the base station (BS) planning problem of 5G non-orthogonal multiple access (NOMA) heterogeneous network, and considers the goal of maximizing network throughput and minimizing the construction cost. Due to the conflict between the two objectives, the BS planning problem of 5G NOMA heterogeneous network is modeled as a multiobjective integer optimization problem. It is very difficult to solve the multi-objective integer optimization problem by using traditional optimization methods. Therefore, we adopt the multiobjective evolutionary algorithm to solve the problem. Simulation results show that the proposed multi-objective optimization scheme for 5G heterogeneous network planning can effectively improve the network transmission performance and reduce the network construction cost.","PeriodicalId":106959,"journal":{"name":"2020 16th International Conference on Computational Intelligence and Security (CIS)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 16th International Conference on Computational Intelligence and Security (CIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIS52066.2020.00021","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
This paper studies the base station (BS) planning problem of 5G non-orthogonal multiple access (NOMA) heterogeneous network, and considers the goal of maximizing network throughput and minimizing the construction cost. Due to the conflict between the two objectives, the BS planning problem of 5G NOMA heterogeneous network is modeled as a multiobjective integer optimization problem. It is very difficult to solve the multi-objective integer optimization problem by using traditional optimization methods. Therefore, we adopt the multiobjective evolutionary algorithm to solve the problem. Simulation results show that the proposed multi-objective optimization scheme for 5G heterogeneous network planning can effectively improve the network transmission performance and reduce the network construction cost.