Heuristic, machine learning approach to 8-CSK decision regions in RGB-LED visible light communication

Color-shift keying (CSK) is a modulation scheme in RGB-LED based visible light communication (VLC) where each symbol is mapped into a color of the visible spectrum. According to the IEEE 802.15.7 standard, nine valid combinations of symbols exist to construct 4, 8 or 16-CSK constellations. However, to the best of our knowledge, no formal rules are specified to determine which design performs better among the nine proposed. In this work, we presented a heuristic, machine learning-based approach to determine the best performing 8-CSK constellation and the most suitable algorithm to classify received 8-CSK modulated signals in terms of classification accuracy and bit-error rate (BER). The constellation built on the triangle with vertices at {429, 509, 564} nm scored a BER at 14 dB of 2.3E-3, 3.1E-4, 4.9E-5 and 1.6E-4 for each of the proposed algorithms that are several dBs lower than the worst performing constellations designed on the triangles {429, 564, 753} nm, {429, 564, 703} nm and {429, 564, 656} nm, demonstrating that indeed there exists a difference among the proposed designs independently of the adopted decision strategy and consequently room for improvement for the existing CSK standard.