Fuzzy logic control based modulation optimisation for the indoor optical wireless channel

The optical wireless (OW) channel has attracted recent interests from researchers as a complement to the already crowded RF spectrum. The OW offers many advantages over RF, such as unregulated bandwidth and improved security and less interference with existing systems, for example. The modulation schemes developed for OW are limited by the combined power and bandwidth requirements, since the communication link is often exposed to intense background noise and channel dynamics. In order to improve the link quality and immunity, rule-based fuzzy logic (FL) control and adaptive neuro-fuzzy inference system (ANFIS) are applied to modulation optimisation under different channel variation. It has been demonstrated that the FL control model can be used to realise real time parameter optimisation, with preset instructions or a learned control pattern. The obtained control model has shown the ability to learn from the desired parameter optimisation, and training results agree well with preset instructions. Since the control model is rule based, it can be easily migrated into different scenarios. This is certainly helpful for high speed applications where link quality is vital.