Jinli Zhang, Jie Li, Mingjiao Cai, Dining Li, Qiang Wang
{"title":"基于多目标进化算法的5G NOMA网络规划","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":"{\"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}","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}
The 5G NOMA networks planning based on the multi-objective evolutionary algorithm
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.