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  • 标题:PERFORMANCE OF SEPARATED RANDOM USER SCHEDULING (SRUS) AND JOUNT USER SCHEDULING (JUS) IN THE LONG - TERM EVOLUTION - ADVANCED
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  • 作者:AHMED A ALI ; Ir. Dr. ROSDIADEE NORDIN ; Assoc. Prof. Dr. HUD BINTI ABDULLAH
  • 期刊名称:Journal of Theoretical and Applied Information Technology
  • 印刷版ISSN:1992-8645
  • 电子版ISSN:1817-3195
  • 出版年度:2014
  • 卷号:59
  • 期号:1
  • 出版社:Journal of Theoretical and Applied
  • 摘要:Carrier aggregation (CA) is one of the main features in Long Term Evolution� Advanced (LTE-A). CA will allow the target peak data rates in excess of 1 Gbps in the downlink and 500 Mbps in the uplink to be achieved, And the users can have access to the total bandwidth of up to 100 MHz . The system bandwidth may be continuous or system consisting of several parts non continuous bandwidth are aggregated. This paper provides a summary of the supported CA scenarios as well as an overview of the advanced functionality of CA-LTE with particular emphasis on the basic concept, control mechanisms, and the performance aspects of (CA). This paper also demonstrates how CA can be used as an enabler for simple yet effective frequency domain interference management schemes. In particular, the interference management is to provide the intervention made significant gains in heterogeneous networks, envisioning intrinsically uncoordinated deployments from the home base stations. then, we compared the quality of service (QoS) performances of two different multi-user scheduling schemes in CA based LTE-A systems, separated random user scheduling (SRUS) and joint user scheduling (JUS). The former is simpler but less efficient whereas the latter is optimal but with higher overhead signaling. Moreover, only one single component carrier (CC) is required to access for user equipment (UE) in the case of SRUS while all the CCs must be connected in the case of JUS. Some technical challenges for implementing carrier scheduling schemes technique in LTE-A systems, are discussed and highlighted.
  • 关键词:Long Term Evolution� Advanced ;Carrier aggregation ; separated random user scheduling; joint user scheduling.
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