{"title":"基于遗传算法的基站布局优化","authors":"O. M. Amine, A. Khireddine","doi":"10.1504/IJCAET.2020.10006440","DOIUrl":null,"url":null,"abstract":"The base station (BS) placement, or planning cell problem, involves choosing the position and infrastructure configuration for cellular networks. This problem is considered to be a mathematical optimisation problem and will be optimised in our study using genetic algorithms. The various parameters such as site coordinates (x, y), transmitting power, height and tilt are taken as design parameters for BS placement. This paper takes signal coverage, interference and cost as objective functions and handover, traffic demand and overlap as a very important constraint. Receiving field strength testing services for all items is calculated using simulations and path loss is calculated using Hata model. Assuming that a flat area is considered, the performance of the proposed algorithm was evaluated with 97% of the users in the network being covered with a good quality signal.","PeriodicalId":346646,"journal":{"name":"Int. J. Comput. Aided Eng. Technol.","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Base station placement optimisation using genetic algorithms approach\",\"authors\":\"O. M. Amine, A. Khireddine\",\"doi\":\"10.1504/IJCAET.2020.10006440\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The base station (BS) placement, or planning cell problem, involves choosing the position and infrastructure configuration for cellular networks. This problem is considered to be a mathematical optimisation problem and will be optimised in our study using genetic algorithms. The various parameters such as site coordinates (x, y), transmitting power, height and tilt are taken as design parameters for BS placement. This paper takes signal coverage, interference and cost as objective functions and handover, traffic demand and overlap as a very important constraint. Receiving field strength testing services for all items is calculated using simulations and path loss is calculated using Hata model. Assuming that a flat area is considered, the performance of the proposed algorithm was evaluated with 97% of the users in the network being covered with a good quality signal.\",\"PeriodicalId\":346646,\"journal\":{\"name\":\"Int. J. Comput. Aided Eng. Technol.\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Comput. Aided Eng. Technol.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJCAET.2020.10006440\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Comput. Aided Eng. Technol.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJCAET.2020.10006440","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Base station placement optimisation using genetic algorithms approach
The base station (BS) placement, or planning cell problem, involves choosing the position and infrastructure configuration for cellular networks. This problem is considered to be a mathematical optimisation problem and will be optimised in our study using genetic algorithms. The various parameters such as site coordinates (x, y), transmitting power, height and tilt are taken as design parameters for BS placement. This paper takes signal coverage, interference and cost as objective functions and handover, traffic demand and overlap as a very important constraint. Receiving field strength testing services for all items is calculated using simulations and path loss is calculated using Hata model. Assuming that a flat area is considered, the performance of the proposed algorithm was evaluated with 97% of the users in the network being covered with a good quality signal.