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Sum rate capacity of multiuser MISO designed for HAPS high speed train application
Zakia I.a, Tjondronegoro S.a, Iskandara, 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]The capacity gain proportional to the number of transmit or receive antenna promised by MIMO, has attracted many interests to implement MIMO on existing terrestrial and satellite system. A complementary to those existing systems is known as HAPS, and is situated in the stratosphere around 17-22 km. One of the interesting applications of HAPS is broadband transmission to high speed trains. The requirements of simultaneously transmitting high data rate in the order of tens of Mbps to high speed trains has brought the idea of implementing multiuser MISO on HAPS. The downlink channel where HAPS is equipped with more than one antenna transmitting to more than one single-antenna trains simultaneously, is known as the Gaussian MISO broadcast channel. The capacity region for this channel is achieved by DPC, but is difficult to implement in practical systems. In this paper, a suboptimal lower complexity scheme such as ZF beamforming is utilized as the precoding strategy. A simulation is conducted to calculate the sum rate capacity for different SNRs. The channel is i.i.d. Rayleigh and Ricean distributed and is assumed to be known perfectly both by the transmitter and receiver. The receiver is assumed to have compensated for the Doppler perfectly. The result is compared to the theoretically optimal DPC strategy and also to the DOA technique proposed by one of the HAPS project in Europe (CAPANINA). © 2011 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]DOA,Gaussian broadcast channel,HAPS,Multi-user,Sum-rate capacity,Zero-forcing[/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]DOA,Gaussian broadcast channel,HAPS,multiuser MISO,sum rate capacity,zero forcing[/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/ICEEI.2011.6021781[/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]