A predistortion method using the adaptive normalised least mean square (NLMS) algorithm is proposed for the estimation of light-emitting diode distortion. The light emission characteristic could change nonlinearly depending on conditions of the physical environment, such as temperature variation, which cannot be ignored, especially in the case of high-power emissions. Instead of using the fixed values of the conventional memory look-up-table (LUT) for nonlinearity compensation, the proposed adaptive NLMS-based predistorter immediately estimates the distortion change according to environmental changes. The simulation results show that the proposed method has better performance than the conventional predistorter employing an LUT.Introduction: The visual light-emitting diode (LED) has a wavelength range of ∼380-780 nm at a very high-frequency band of 385-789 THz. If this band is used for communication, we can avoid electromagnetic interference from man-made signals, including conventional radio communication, which cannot reach this frequency range. An LED is a digitally controllable element with on/off switching control that is represented as a digital pulse. Human eyes cannot recognise LED blinking; rather, they sense that the LED is continuously turned on if it blinks at a sufficiently high speed. Because of this characteristic, the LED can be utilised simultaneously as lighting and as a communication link. Recent research for visible-light communications (VLCs) has focused on low-speed communications based on the on/off switching scheme [1].In order to apply VLC for wideband data transmission, we need to consider the linear variation of the luminance for high-order modulated signals with M-ary modulation, since the LED switching scheme has limitations in enhancing the transmit data rate. However, M-ary modulations have a critical disadvantage in a VLC system, especially for nonconstant envelope-modulated signals, because of the nonlinear response of the LED. Therefore, this drawback not only reduces the power efficiency of the system, but also degrades the bit error rate (BER) performance [1]. If we distort the bias signal intentionally to compensate for the nonlinearity of the LED luminance, the system performance could be improved [2]. The amount of distortion corresponding to the bias signal is calculated after measuring the characteristic of the LED luminance and storing it in a look-up-table (LUT). Using this LUT, we can constitute a predistorter. However, the performance is degraded in the conventional LUT-based predistorter when the physical characteristic is changed due to abnormal temperatures, LED ageing or similar physical changes.In this Letter, we propose a predistorter that can estimate the LED characteristics due to environmental changes using the adaptive normalised least mean square (NLMS) algorithm.
A simple and general bit log‐likelihood ratio (LLR) expression is provided for Gray‐coded rectangular quadrature amplitude modulation (R‐QAM) signals. The characteristics of Gray code mapping such as symmetries and repeated formats of the bit assignment in a symbol among bit groups are applied effectively for the simplification of the LLR expression. In order to reduce the complexity of the max‐log‐MAP algorithm for LLR calculation, we replace the mathematical max or min function of the conventional LLR expression with simple arithmetic functions. In addition, we propose an implementation algorithm of this expression. Because the proposed expression is very simple and constructive with some parameters reflecting the characteristic of the Gray code mapping result, it can easily be implemented, providing an efficient symbol de‐mapping structure for various wireless applications.
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