{"title":"Efficient resource allocation scheme with grey relational analysis for the uplink scheduling of 3GPP LTE networks","authors":"Ruey-Rong Su, I. Hwang","doi":"10.1109/ICIT.2016.7474817","DOIUrl":null,"url":null,"abstract":"Appropriate bandwidth allocation is an important issue to benefit the long Term Evolution (LTE) networks performance. Single-carrier FDMA (SC-FDMA) multiple access scheme has been chosen for the 3GPP LTE uplink scheduling. However, it requires that all the sub carriers allocated to a single user must be in contiguous frequency band within each time slot. This constraint limits the scheduling flexibility. The resource allocation algorithm in frequency domain must take this constrain into consideration to maximize its scheduling objectives. An Efficient Resource Allocation algorithm with Grey Relational Analysis (ERAGRA) is proposed and compared with the others algorithms based on the throughput and fairness in this research. The ERAGRA algorithm is a channel-aware traffic resource allocation algorithm which aims at enabling uplink traffic delivery on ideal and non-ideal channels. This algorithm is evaluated using 3GPP LTE simulation model. A key performance index (KPI) is defined as the combination of total throughput and fairness. ERAGRA and two other scheduling algorithms: Best CQI and Round Robin has been evaluated through simulation based on this KPI. Simulation results indicate that the proposed ERAGRA algorithm effectively improves the average normalized system throughput of Best CQI by 6.22 % and fairness by 2.74 %, while improves the average normalized system throughput of Round Robin by 38.67 % and fairness by 10.26 %. The proposed scheduling scheme achieves a near optimal solution for maximizing system throughput and fairness of resource utilization.","PeriodicalId":116715,"journal":{"name":"2016 IEEE International Conference on Industrial Technology (ICIT)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Industrial Technology (ICIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIT.2016.7474817","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
Appropriate bandwidth allocation is an important issue to benefit the long Term Evolution (LTE) networks performance. Single-carrier FDMA (SC-FDMA) multiple access scheme has been chosen for the 3GPP LTE uplink scheduling. However, it requires that all the sub carriers allocated to a single user must be in contiguous frequency band within each time slot. This constraint limits the scheduling flexibility. The resource allocation algorithm in frequency domain must take this constrain into consideration to maximize its scheduling objectives. An Efficient Resource Allocation algorithm with Grey Relational Analysis (ERAGRA) is proposed and compared with the others algorithms based on the throughput and fairness in this research. The ERAGRA algorithm is a channel-aware traffic resource allocation algorithm which aims at enabling uplink traffic delivery on ideal and non-ideal channels. This algorithm is evaluated using 3GPP LTE simulation model. A key performance index (KPI) is defined as the combination of total throughput and fairness. ERAGRA and two other scheduling algorithms: Best CQI and Round Robin has been evaluated through simulation based on this KPI. Simulation results indicate that the proposed ERAGRA algorithm effectively improves the average normalized system throughput of Best CQI by 6.22 % and fairness by 2.74 %, while improves the average normalized system throughput of Round Robin by 38.67 % and fairness by 10.26 %. The proposed scheduling scheme achieves a near optimal solution for maximizing system throughput and fairness of resource utilization.