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

Rajbhandari, Sujan, Ghassemlooy, Zabih and Angelova, Maia (2009) Bit error performance of diffuse indoor optical wireless channel pulse position modulation system employing artificial neural networks for channel equalisation. IET Optoelectronics, 3 (4). pp. 169-179. ISSN 1751-8768

[img]
Preview
PDF (Article)
Bit error performance of PPM with ANN equalizer.pdf

Download (353kB) | Preview
Official URL: http://dx.doi.org/10.1049/iet-opt.2007.0081

Abstract

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.

Item Type: Article
Uncontrolled Keywords: neural networks, optical communications
Subjects: H900 Others in Engineering
J900 Others in Technology
Department: Faculties > Engineering and Environment > Mathematics and Information Sciences
Depositing User: EPrint Services
Date Deposited: 31 Jul 2009 14:45
Last Modified: 09 May 2017 13:37
URI: http://nrl.northumbria.ac.uk/id/eprint/3241

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics


Policies: NRL Policies | NRL University Deposit Policy | NRL Deposit Licence