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Performance comparisons of adaptive MVDR and received LS beamforming on the downlink time varying channel of HAP system

Zakia I.a, Tjondronegoro S.a, Iskandar I.a, Kurniawan A.a

a School of Electrical Engineering and Informatics, Institut Teknologi Bandung, 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]We consider the performance comparisons of adaptive Minimum Variance Distortionless Response (MVDR) and received Least Squares (LS) beamforming on the downlink channel from High Altitude Platform (HAP) to high speed train. The channel, as modeled in CAPANINA project, is considered as time varying rician and flat fading process. Since the rician factor is moderate to high, adaptive MVDR beamforming is attractive in compensating for the rician fading channel. Due to the constraint in the cost function, MVDR beamforming neglects useful received signal particularly in the lower rician factors, hence, mismatch occurs. By implementing the LS beamforming, the receiver is able to adapt better to a more rayleigh fading channel case. The comparisons of the considered beamforming algorithms are given in terms of Mean Square Error (MSE) of beamforming weight tracking and Bit Error Rate (BER). © 2013 IEEE.[/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]HAP,Least Square,MVDR,Rician fading,Time varying channel[/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]beamforming,HAP,least squares,MVDR,rician fading,time varying channel[/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/APCC.2013.6766041[/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]