I. Valavanis, D. Zarbouti, G. Athanasiadou, G. Tsoulos
{"title":"最小发射电网规划的基站天线方向图重构","authors":"I. Valavanis, D. Zarbouti, G. Athanasiadou, G. Tsoulos","doi":"10.1109/OnlineGreenCom.2015.7387381","DOIUrl":null,"url":null,"abstract":"Optimization of basestation antenna patterns and transmitted powers in heterogeneous 4g networks with geographically inhomogeneous throughput requirements is not an easy problem to tackle, and hence, frequently omitted. Moreover, the initial phase of network dimensioning and planning often fails to meet growing throughput demands, and hence, network operation becomes problematic, especially around hotspots. This paper formulates the coverage and capacity optimization problem in the context of 4g systems and uses a multi-objective genetic algorithm in order to optimize the basestation antenna patterns with respect to their pointing direction, 3dB beamwidth and transmitted power. The proposed optimization algorithm is then applied to provide the most energy efficient network setup in a test scenario with varying area capacity requirements. It is shown that the reconfigured network setups featured neatly adjusted radiation patterns, increase capacity capabilities while reducing network cost and energy consumption and, most importantly, improve safety with regards to reduced power emissions.","PeriodicalId":171886,"journal":{"name":"2015 IEEE Online Conference on Green Communications (OnlineGreenComm)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Basestation antenna pattern reconfiguration for minimum transmit power network planning\",\"authors\":\"I. Valavanis, D. Zarbouti, G. Athanasiadou, G. Tsoulos\",\"doi\":\"10.1109/OnlineGreenCom.2015.7387381\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Optimization of basestation antenna patterns and transmitted powers in heterogeneous 4g networks with geographically inhomogeneous throughput requirements is not an easy problem to tackle, and hence, frequently omitted. Moreover, the initial phase of network dimensioning and planning often fails to meet growing throughput demands, and hence, network operation becomes problematic, especially around hotspots. This paper formulates the coverage and capacity optimization problem in the context of 4g systems and uses a multi-objective genetic algorithm in order to optimize the basestation antenna patterns with respect to their pointing direction, 3dB beamwidth and transmitted power. The proposed optimization algorithm is then applied to provide the most energy efficient network setup in a test scenario with varying area capacity requirements. It is shown that the reconfigured network setups featured neatly adjusted radiation patterns, increase capacity capabilities while reducing network cost and energy consumption and, most importantly, improve safety with regards to reduced power emissions.\",\"PeriodicalId\":171886,\"journal\":{\"name\":\"2015 IEEE Online Conference on Green Communications (OnlineGreenComm)\",\"volume\":\"36 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE Online Conference on Green Communications (OnlineGreenComm)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/OnlineGreenCom.2015.7387381\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE Online Conference on Green Communications (OnlineGreenComm)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/OnlineGreenCom.2015.7387381","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Basestation antenna pattern reconfiguration for minimum transmit power network planning
Optimization of basestation antenna patterns and transmitted powers in heterogeneous 4g networks with geographically inhomogeneous throughput requirements is not an easy problem to tackle, and hence, frequently omitted. Moreover, the initial phase of network dimensioning and planning often fails to meet growing throughput demands, and hence, network operation becomes problematic, especially around hotspots. This paper formulates the coverage and capacity optimization problem in the context of 4g systems and uses a multi-objective genetic algorithm in order to optimize the basestation antenna patterns with respect to their pointing direction, 3dB beamwidth and transmitted power. The proposed optimization algorithm is then applied to provide the most energy efficient network setup in a test scenario with varying area capacity requirements. It is shown that the reconfigured network setups featured neatly adjusted radiation patterns, increase capacity capabilities while reducing network cost and energy consumption and, most importantly, improve safety with regards to reduced power emissions.