Abstract

In this paper, we investigate methods to optimise the bias point of an LED to benefit from increasing bandwidth at higher driving current while minimising the resulting signal distortion. The approaches are based on allowing for some nonlinear distortion or to reduce signal swing/signal-to-noise ratio while benefiting from higher bandwidth at higher driving currents. A framework is presented to estimate the attainable capacity under both conditions. We also experimentally validate the optimisation with a PAM-4 based VLC system. The experimental results show that for a 40 mA dynamic range VLMB1500 LED used, the optimum bias point is not in the middle of the dynamic range but at 31 mA.

Highlights

  • T HE continued rapid growth of data traffic is demanding high-capacity communication systems

  • In [12], a numerical method based on minimising mean squared error (MMSE) criterion is proposed to optimise the DC bias that improves the bit error rate (BER) performance

  • It has been shown that the modulation bandwidth of an light-emitting diodes (LEDs) increases at the DC bias from the mid-point of its linear region

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Summary

INTRODUCTION

T HE continued rapid growth of data traffic is demanding high-capacity communication systems. This is driving the radio frequency (RF) based wireless communication towards spectrum shortage [1]. In the optical domain, large and unlicensed spectrum, free from electromagnetic interference, and with inherent security is available This makes optical wireless communication (OWC) a plausible technology to supplement developments in the RF-based networks [2]. Significant research effort has been put towards the development of high-speed VLC Such a system needs to address the challenges associated with the relatively low modulation bandwidth of commercial LEDs [4]. In [12], a numerical method based on minimising mean squared error (MMSE) criterion is proposed to optimise the DC bias that improves the bit error rate (BER) performance

SYSTEM DESIGN
VLC Model and Link Capacity
Bias Point Optimisation
Simulation Results
Experimental Validation
Findings
CONCLUSION
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