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Massive MIMO Channel Estimation Using FastICA Weighted Function for VLC in 5G Networks
https://orcid.org/http://orcid.org/0000-0001-7334-462X
The multiple input multiple output-orthogonal frequency division multiplexing (m-MIMO-OFDM) is a hot research topic as it provides air interface solution for 5G wireless communications. The transmitted signals typically reflect the high-speed scattered signals which are processed using light emitting diodes (LED). The transmitted signals arrive at the receiver from the multiple paths. From both the receivers, objects are scattered and the channels are changed over time in m-MIMO which gives rise to slower convergence. The proposed FastICA algorithm produces improved performance as it uses for separating components for the selection of better parameters. The components from the source are transmitted, after which they are separated and detected based on the receiver channel’s location. The present research proposes a method to estimate the blind channel approach using fast independent component analysis based on the weight function (FICA-WF) for blind interference cancellation. The existing models such as parallel factor analysis, joint parallel factor analysis, STBC-m-MIMO-OFDM, and MMSE-CMA-DFCE obtained SNR ranging from 10 to 20 dB, whereas the proposed model obtained better SNR of 9.02 dB for the FastICA-WF.
Massive MIMO Channel Estimation Using FastICA Weighted Function for VLC in 5G Networks
https://orcid.org/http://orcid.org/0000-0001-7334-462X
The multiple input multiple output-orthogonal frequency division multiplexing (m-MIMO-OFDM) is a hot research topic as it provides air interface solution for 5G wireless communications. The transmitted signals typically reflect the high-speed scattered signals which are processed using light emitting diodes (LED). The transmitted signals arrive at the receiver from the multiple paths. From both the receivers, objects are scattered and the channels are changed over time in m-MIMO which gives rise to slower convergence. The proposed FastICA algorithm produces improved performance as it uses for separating components for the selection of better parameters. The components from the source are transmitted, after which they are separated and detected based on the receiver channel’s location. The present research proposes a method to estimate the blind channel approach using fast independent component analysis based on the weight function (FICA-WF) for blind interference cancellation. The existing models such as parallel factor analysis, joint parallel factor analysis, STBC-m-MIMO-OFDM, and MMSE-CMA-DFCE obtained SNR ranging from 10 to 20 dB, whereas the proposed model obtained better SNR of 9.02 dB for the FastICA-WF.
Massive MIMO Channel Estimation Using FastICA Weighted Function for VLC in 5G Networks
https://orcid.org/http://orcid.org/0000-0001-7334-462X
The multiple input multiple output-orthogonal frequency division multiplexing (m-MIMO-OFDM) is a hot research topic as it provides air interface solution for 5G wireless communications. The transmitted signals typically reflect the high-speed scattered signals which are processed using light emitting diodes (LED). The transmitted signals arrive at the receiver from the multiple paths. From both the receivers, objects are scattered and the channels are changed over time in m-MIMO which gives rise to slower convergence. The proposed FastICA algorithm produces improved performance as it uses for separating components for the selection of better parameters. The components from the source are transmitted, after which they are separated and detected based on the receiver channel’s location. The present research proposes a method to estimate the blind channel approach using fast independent component analysis based on the weight function (FICA-WF) for blind interference cancellation. The existing models such as parallel factor analysis, joint parallel factor analysis, STBC-m-MIMO-OFDM, and MMSE-CMA-DFCE obtained SNR ranging from 10 to 20 dB, whereas the proposed model obtained better SNR of 9.02 dB for the FastICA-WF.
Massive MIMO Channel Estimation Using FastICA Weighted Function for VLC in 5G Networks
J. Inst. Eng. India Ser. B
Sindhuja, R. (Autor:in) / Shankar, Arathi R. (Autor:in)
Journal of The Institution of Engineers (India): Series B ; 104 ; 433-440
01.04.2023
8 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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