Abstract
Indoor diffuse optical wireless (OW) communication systems performance
is limited due to a number of effects; interference from natural and artificial
light sources and multipath induced intersymbol interference (ISI). Artificial
light interference (ALI) is a periodic signal with a spectrum profile extending
up to the MHz range. It is the dominant source of performance degradation
at low data rates, which can be removed using a high-pass filter (HPF). On
the other hand, ISI is more severe at high data rates and an equalizing filter
is incorporated at the receiver to compensate for the ISI. This paper provides
the simulation results for a discrete wavelet transform (DWT)—artificial
neural network (ANN)-based receiver architecture for on-and-off keying (OOK)
non-return-to-zero (NRZ) scheme for a diffuse indoor OW link in the presence
of ALI and ISI. ANN is adopted for classification acting as an efficient equalizer
compared to the traditional equalizers. The ALI is effectively reduced by
proper selection of the DWT coefficients resulting in improved receiver performance
compared to the digital HPF. The simulated bit error rate (BER) performance
of proposed DWT-ANN receiver structure for a diffuse indoor OW link operating
at a data range of 10-200 Mbps is presented and discussed. The results are
compared with performance of a diffuse link with an HPF-equalizer, ALI with/without
filtering, and a line-of-sight (LOS) without filtering. We show that the DWT-ANN
display a lower power requirement when compared to the receiver with an HPF-equalizer
over a full range of delay spread in presence of ALI. However, as expected
compared to the ideal LOS link the power penalty is higher reaching to 6 dB
at 200 Mbps data rate.
© 2009 IEEE
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