Layered asymmetrical clipped optical-orthogonal frequency division multiplexing (LACO-OFDM) enhances spectral efficiency by mandating the use of a K-means algorithm in LACO-OFDM (KLACO-OFDM), which enables efficiency gains to nearly double by modulating odd and even subcarriers. The traditional receiver is not sufficiently sophisticated enough to exploit the full potential of LACO-OFDM, thereby restricting its performance. In this paper, a K-means algorithm was used to increase the spectral efficiency of LACO-OFDM by integrating machine learning to cluster the inward signal such that the original locations of the received constellations can be retrieved.
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