Daanish Md Shariff, K. Kumari, Lakshmi Shree, S. Neethu
{"title":"使用自适应算法的基站波束形成","authors":"Daanish Md Shariff, K. Kumari, Lakshmi Shree, S. Neethu","doi":"10.1109/RTEICT.2017.8256829","DOIUrl":null,"url":null,"abstract":"With the increase in demand for better quality of service (QoS) requirements and data rates, various software based approaches have been adapted to improve the performance of antennas used in the base stations. Initially, mechanical methods were used for electronic tilt of antenna arrays in the base station. But with the increase in number of users, these methods proved to be less efficient. In order to overcome these limitations, various adaptive algorithms have been worked upon. Adaptive algorithms are mostly used in the base stations rather than at the user equipment end due to space constraints. For adaptive beamforming two types of algorithms are a basic requirement; they are adaptive beamforming and direction of arrival (DOA) estimation. DOA algorithms estimate the direction of the desired signal and this estimated signal direction is given as an input parameter to the adaptive beamforming algorithm. This algorithm forms the beam using suitable number of array elements based on the user location and other practical requirements. There are various DOA estimation algorithms such as MUSIC, MVDR, and ESPIRIT. Examples for adaptive beamforming algorithms include LMS, RLS and many more. In the proposed work, MUSIC algorithm has been used for DOA estimation and LMS algorithm is used for beamforming. Variation of beamwidth with variation in active array elements and error in DOA estimation of MUSIC algorithm has been estimated using MATLAB tool. Further interference mitigation has been achieved by forming side lobes in the direction of the interference signals.","PeriodicalId":342831,"journal":{"name":"2017 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT)","volume":"139 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Beamforming at base stations using adaptive algorithms\",\"authors\":\"Daanish Md Shariff, K. Kumari, Lakshmi Shree, S. Neethu\",\"doi\":\"10.1109/RTEICT.2017.8256829\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the increase in demand for better quality of service (QoS) requirements and data rates, various software based approaches have been adapted to improve the performance of antennas used in the base stations. Initially, mechanical methods were used for electronic tilt of antenna arrays in the base station. But with the increase in number of users, these methods proved to be less efficient. In order to overcome these limitations, various adaptive algorithms have been worked upon. Adaptive algorithms are mostly used in the base stations rather than at the user equipment end due to space constraints. For adaptive beamforming two types of algorithms are a basic requirement; they are adaptive beamforming and direction of arrival (DOA) estimation. DOA algorithms estimate the direction of the desired signal and this estimated signal direction is given as an input parameter to the adaptive beamforming algorithm. This algorithm forms the beam using suitable number of array elements based on the user location and other practical requirements. There are various DOA estimation algorithms such as MUSIC, MVDR, and ESPIRIT. Examples for adaptive beamforming algorithms include LMS, RLS and many more. In the proposed work, MUSIC algorithm has been used for DOA estimation and LMS algorithm is used for beamforming. Variation of beamwidth with variation in active array elements and error in DOA estimation of MUSIC algorithm has been estimated using MATLAB tool. Further interference mitigation has been achieved by forming side lobes in the direction of the interference signals.\",\"PeriodicalId\":342831,\"journal\":{\"name\":\"2017 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT)\",\"volume\":\"139 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RTEICT.2017.8256829\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RTEICT.2017.8256829","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Beamforming at base stations using adaptive algorithms
With the increase in demand for better quality of service (QoS) requirements and data rates, various software based approaches have been adapted to improve the performance of antennas used in the base stations. Initially, mechanical methods were used for electronic tilt of antenna arrays in the base station. But with the increase in number of users, these methods proved to be less efficient. In order to overcome these limitations, various adaptive algorithms have been worked upon. Adaptive algorithms are mostly used in the base stations rather than at the user equipment end due to space constraints. For adaptive beamforming two types of algorithms are a basic requirement; they are adaptive beamforming and direction of arrival (DOA) estimation. DOA algorithms estimate the direction of the desired signal and this estimated signal direction is given as an input parameter to the adaptive beamforming algorithm. This algorithm forms the beam using suitable number of array elements based on the user location and other practical requirements. There are various DOA estimation algorithms such as MUSIC, MVDR, and ESPIRIT. Examples for adaptive beamforming algorithms include LMS, RLS and many more. In the proposed work, MUSIC algorithm has been used for DOA estimation and LMS algorithm is used for beamforming. Variation of beamwidth with variation in active array elements and error in DOA estimation of MUSIC algorithm has been estimated using MATLAB tool. Further interference mitigation has been achieved by forming side lobes in the direction of the interference signals.