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Inter-cell interference management technique for multi-cell LTE-a network
Iskandara, Setyawan I.a, Nuraini H.a
a School of Electrical Engineering and Informatics, Bandung Institute of Technology, Bandung, 40132, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]Copyright © 2017 Institute of Advanced Engineering and Science. All rights reserved. In modern cellular system such as LTE Advanced (LTE-A), frequency reuse scheme is targeted to be applied to fulfill the requirement of high capacity broadband access and high spectrum efficiency. But this kind of frequency planning may lead to the worse inter-cell interference (ICI) level experienced especially by a user located at the cell edge. Soft Frequency Reuse (SFR) is considered as an effective way to mitigate inter-cell interference and maintain capacity. We propose a power division SFR, known as multi level SFR technique to minimize ICI in a designed LTE-A network for sub-urban environment. Service area of LTE-A network was first developed to deploy particular number of eNB by using LTE network planning tools in the frequency of 1800 MHz with the use of SISO (Single Input Single Output) antennas. Coverage dimensioning and propagation consideration determine LTE-A parameters which were used in the simulation. Monte carlo simulation is executed to examine the performance of SFR for LTE-A downlink transmission to address different power ratio and traffic loads problem. Both performance of cell edge users and overall cell performance are evaluated in terms of CINR, BLER, and throughput. Performance with SFR is also compared with the classical frequency reuse one and three.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]BLER,CIR downlink,Dimensioning,LTE,SINR,Soft frequency reuse (SFR),Throughput[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.11591/ijece.v7i5.pp2696-2705[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]