Spatial and wavelength division multiplexing for high-speed VLC systems: An overview

White light emitting diodes (LEDs) are becoming the primary source of illumination for the home and office environment. These LEDs can be intensity modulated to transmit high-speed data via an optical carrier. As a result, there is a paradigm shift in indoor wireless communication as the illumination infrastructure can be reused for data communications. It is widely expected that visible light communication (VLC) system will play a significant role in realizing the high-speed data communication envisaged for 5G connectivity. The goal of VLC systems is to provide a reliable and ubiquitous communication link that is an order of magnitude faster than current radio frequency (RF) links. In order to support the high data rates required for the current and future generations of communication systems, a number of techniques were explored for VLC by a number of research groups worldwide. This paper provides an overview of spatial and wavelength division multiplexing that has enabled multi-Gb/s transmission speeds in VLC using low bandwidth LEDs

A study of discrete wavelet transform based denoising to reduce the effect of artificial light interferences for indoor optical wireless communication

The optical power penalty (OPP) due to the artificial light interferences (ALIs) can be significantly high in an indoor optical wireless communication (OWC) channel making such link practically infeasible. A discrete wavelet transform (DWT) is an effective technique in reducing the ALI effects. The DWT has the advantage over the high pass filtering (HPF) to reduce ALI in terms of complexity and performance. In this paper, a comprehensive study of the DWT based denoising for the on-off keying (OOK), pulse position modulation (PPM) and digital pulse interval modulation (DPIM) is provided. The OPPs due to ALIs and DWT based denoising for these modulation techniques are presented

Application of wavelets and artificial neural network for indoor optical wireless communication systems

Abstract This study investigates the use of error control code, discrete wavelet transform (DWT) and artificial neural network (ANN) to improve the link performance of an indoor optical wireless communication in a physical channel. The key constraints that barricade the realization of unlimited bandwidth in optical wavelengths are the eye-safety issue, the ambient light interference and the multipath induced intersymbol interference (ISI). Eye-safety limits the maximum average transmitted optical power. The rational solution is to use power efficient modulation techniques. Further reduction in transmitted power can be achieved using error control coding. A mathematical analysis of retransmission scheme is investigated for variable length modulation techniques and verified using computer simulations. Though the retransmission scheme is simple to implement, the shortfall in terms of reduced throughput will limit higher code gain. Due to practical limitation, the block code cannot be applied to the variable length modulation techniques and hence the convolutional code is the only possible option. The upper bound for slot error probability of the convolutional coded dual header pulse interval modulation (DH-PIM) and digital pulse interval modulation (DPIM) schemes are calculated and verified using simulations. The power penalty due to fluorescent light interference (FL I) is very high in indoor optical channel making the optical link practically infeasible. A denoising method based on a DWT to remove the FLI from the received signal is devised. The received signal is first decomposed into different DWT levels; the FLI is then removed from the signal before reconstructing the signal. A significant reduction in the power penalty is observed using DWT. Comparative study of DWT based denoising scheme with that of the high pass filter (HPF) show that DWT not only can match the best performance obtain using a HPF, but also offers a reduced complexity and design simplicity. The high power penalty due to multipath induced ISI makes a diffuse optical link practically infeasible at higher data rates. An ANN based linear and DF architectures are investigated to compensation the ISI. Unlike the unequalized cases, the equalized schemes don‘t show infinite power penalty and a significant performance improvement is observed for all modulation schemes. The comparative studies substantiate that ANN based equalizers match the performance of the traditional equalizers for all channel conditions with a reduced training data sequence. The study of the combined effect of the FLI and ISI shows that DWT-ANN based receiver perform equally well in the present of both interference. Adaptive decoding of error control code can offer flexibility of selecting the best possible encoder in a given environment. A suboptimal ?soft‘ sliding block convolutional decoder based on the ANN and a 1/2 rate convolutional code with a constraint length is investigated. Results show that the ANN decoder can match the performance of optimal Viterbi decoder for hard decision decoding but with slightly inferior performance compared to soft decision decoding. This provides a foundation for further investigation of the ANN decoder for convolutional code with higher constraint length values. Finally, the proposed DWT-ANN receiver is practically realized in digital signal processing (DSP) board. The output from the DSP board is compared with the computer simulations and found that the difference is marginal. However, the difference in results doesn‘t affect the overall error probability and identical error probability is obtained for DSP output and computer simulations

Wavelet transform - artificial neural network receiver with adaptive equalisation for a diffuse indoor optical wireless OOK link

This paper presents an alternative approach for signal detection and equalization using the continuous wavelet transform (CWT) and the artificial neural network (ANN) in diffuse indoor optical wireless links (OWL). The wavelet analysis is used for signal preprocessing (feature extraction) and the ANN for signal detection. Traditional receiver architectures based on matched filter (MF) experience significant performance degradation in the presence of artificial light interference (ALI) and multipath induced intersymbol interference (ISI). The proposed receiver structure reduces the effect of ALI and ISI by selecting a particular scale of CWT that corresponds to the desired signal and classifying the signal into binary 1 and 0 based on an observation vector. By selecting particular scales corresponding to the signal, the effect of ALI is reduced. We show that there is little variation when using 30 and 5 neurons in the first layer, with one layer ANN model showing a consistently worse BER performance than other models, whilst the 15 neuron model show some behaviour anomalies from a BER of approximately 10-3. The simulation results show that the Wavelet-ANN architecture outperforms the traditional MF based receiver even with the filter is matched to the ISI affected pulse shape. The Wavelet-ANN receiver is also capable of providing a bit error rate (BER) performance comparable to the equalized forms of traditional receiver structure

Effective denoising and adaptive equalization of indoor optical wireless channel with artificial light using the discrete wavelet transform and artificial neural network

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

Bit error performance of diffuse indoor optical wireless channel pulse position modulation system employing artificial neural networks for channel equalisation

The bit-error rate (BER) performance of a pulse position modulation (PPM) scheme for non-line-of-sight indoor optical links employing channel equalisation based on the artificial neural network (ANN) is reported. Channel equalisation is achieved by training a multilayer perceptrons ANN. A comparative study of the unequalised `soft' decision decoding and the `hard' decision decoding along with the neural equalised `soft' decision decoding is presented for different bit resolutions for optical channels with different delay spread. We show that the unequalised `hard' decision decoding performs the worst for all values of normalised delayed spread, becoming impractical beyond a normalised delayed spread of 0.6. However, `soft' decision decoding with/without equalisation displays relatively improved performance for all values of the delay spread. The study shows that for a highly diffuse channel, the signal-to-noise ratio requirement to achieve a BER of 10−5 for the ANN-based equaliser is ~10 dB lower compared with the unequalised `soft' decoding for 16-PPM at a data rate of 155 Mbps. Our results indicate that for all range of delay spread, neural network equalisation is an effective tool of mitigating the inter-symbol interference

Wavelet—Artificial Neural Network Receiver for Indoor Optical Wireless Communications

The multipath induced intersymbol interference (ISI) and fluorescent light interference (FLI) are the two most important system impairments that affect the performance of indoor optical wireless communication (OWC) systems. The presence of either incurs a high optical power penalty (OPP) and hence the interferences should be mitigated with suitable techniques to ensure optimum system performance. The discrete wavelet transform (DWT) and the artificial neural network (ANN) based receiver to mitigate the effect of FLI and ISI has been proposed in the previous study for the one-off keying (OOK) modulation scheme. It offers performance improvement compared to the traditional methods of employing a high pass filter (HPF) and a finite impulse response (FIR) equalizer. In this paper, the investigation of the DWT-ANN based receiver for baseband modulation techniques including OOK, pulse position modulation (PPM) and digital pulse interval modulation (DPIM) are reported. The proposed system is implemented using digital signal processing (DSP) board and results are verified by comparison with simulation data