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Pilot-based estimation for SC-FDMA LTE in high altitude platforms (HAPS) channel
Hidayat D.a, Iskandara
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]© 2015 IEEE.This paper aims at evaluating pilot-based estimation technique for SC-FDMA LTE deployed via high altitude platforms (HAPS) channel. HAPS is a novel wireless infrastructure in which one of its applications is to carry cellular system such as 4G LTE. The problem of SC-FDMA LTE signal transmission over HAPS channel is due to multipath from objects nearby the mobile user. Signal at the receiver, which in this case receiver is an eNB onboard the platform, will be suffering from fluctuation due to fading. Since the channel conditions fluctuate, immediate channel state information (CSI) needs to be estimated in a short time. Pilot signal or a so-called training sequence is a popular approach to estimate CSI. HAPS channel is known to follow Ricean fading distribution. In our work, pilot-based estimation is evaluated under HAPS Ricean channel. The channel variation is governed by user’s elevation angle. Modulation type and LTE channel bandwidth are also investigated.[/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]Estimation techniques,HAPS,High altitude platform (HAPs),Ricean fading channel,SC-FDMA,Signal transmission,Training sequences,Wireless infrastructures[/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]HAPS,LTE,Pilot-based channel estimation,Ricean fading channel,SC-FDMA[/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.2015.7440421[/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]