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Extreme Learning Machine-Based Receiver for MIMO LED Communications
This work concerns receiver design for light-emitting diode (LED) multiple
input multiple output (MIMO) communications where the LED nonlinearity can
severely degrade the performance of communications. In this paper, we propose
an extreme learning machine (ELM) based receiver to jointly handle the LED
nonlinearity and cross-LED interference, and a circulant input weight matrix is
employed, which significantly reduces the complexity of the receiver with the
fast Fourier transform (FFT). It is demonstrated that the proposed receiver can
efficiently handle the LED nonlinearity and cross-LED interference
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