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Comparative analysis of scheduling methods developed in case of LTE network planning

Iskandara, Hakim R.R.a, Ernawan M.E.b

a School of Electrical Engineering and Informatics, Bandung Institute of Technology, Bandung, 40132, Indonesia
b Graduate School of Global Information and Telecommunication Studies, Waseda University, Japan

[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]© 2017 IEEE.In this paper, we conducted a comparative analysis of the scheduling methods taking a case study in urban, sub urban, and rural environment. The rapid changing of data and information has encouraged the growth of LTE technology which has capable of meeting the needs of data transfer. With scheduling analysis we can determine the best schemes in each type of radio environment such as urban, suburban and rural which produce maximum throughput and the most efficient planning. From this research, proportional fair scheduling algorithms in general is the best algorithm with greatest throughput output for each area, which is urban (max 1154 kbps), suburban (max 2291kbps) and rural (max 3888 kbps). In urban areas proportional fair had better throughput up to 113% in low PDSCH level (<20 dB) compared to Round robin and Maximum C/I scenario.[/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]Comparative analysis,Data and information,Efficient planning,Maximum through-put,Proportional fair scheduling algorithms,Radio environment,Scheduling analysis,Scheduling methods[/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]LTE,PRB,QoS,Scheduling,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/10.1109/TSSA.2017.8272901[/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]