Extreme Learning Machine-Based Receiver for MIMO LED Communications

Dawei Gao; Qinghua Guo

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arXiv · 1903.01551

Extreme Learning Machine-Based Receiver for MIMO LED Communications

Dawei Gao·Qinghua Guo

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Abstract

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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Dawei Gao, Qinghua Guo. 2019-02-27. Extreme Learning Machine-Based Receiver for MIMO LED Communications. https://arxiv.org/abs/1903.01551

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