# Extreme Learning Machine-Based Receiver for MIMO LED Communications

arXiv: https://arxiv.org/abs/1903.01551 · HTML: https://mlsanity.com/paper/1903.01551/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Feb 2019.

## Built on by (most cited first, 1 of 1)

- [Signal Detection in MIMO Systems with Hardware Imperfections: Message Passing on Neural Networks](https://mlsanity.com/paper/2210.03911/) (2022)

## Abstract (arXiv)

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.