Experimental Study on Chromaticity Control in Visible Light Communication Systems

Abstract

To apply visible light communication systems in different scenarios, this article utilizes an excellent temperature-adjustable light source mixed with RGB LEDs and applies it in a visible light communication system. It uses color division multiplexing technology to achieve three-channel communication, thereby improving the communication bandwidth of the system. The communication system adopts three constant current driving circuits to control the duty cycle of Pulse Width Modulation (PWM) of each channel, thereby changing the proportion of RGB LEDs, and obtaining different color temperatures to achieve the purpose of color control for mixed-color LEDs. The experimental results show that when adjusting the color temperature, the change in luminous flux is very small, with fluctuations of less than 2.24%. When adjusting the brightness, the color temperature fluctuation is within 40 K, which is less than the 50 K color temperature limit that the human eye can distinguish, and the average color temperature error is 0.609%. Color tolerance less than 5.5 × 10⁻³ indicates good dimming effect, and the communication performance of the system is better in the high color temperature range, which is significantly superior to the low color temperature range. When the error rate is below 3.8 × 10⁻³, the total modulation bandwidth of the three channels reaches 11.7 MHz.

1. Introduction

As a dual-function white LED for lighting and communication, it is important to consider the influence of the light source’s color on the human eye in addition to its communication performance. Creating a lighting environment with a positive psychological, physiological, and visual impact on individuals is crucial [1,2]. The color temperature of the light source has a significant impact on the human nervous system [3]. Cold-colored light sources can potentially stimulate the nervous system, and in high color-temperature environments, a person’s heart rate and pulse accelerate, blood pressure increases, and mental excitement occurs. On the contrary, warm-colored light sources have effects such as soothing emotions, reducing stress, and lowering heart rhythm and pulse [4]. In terms of psychological perception, low color temperature light sources (warm color light) make people feel warm, while high color temperature white light (cold color light) makes people feel cold [5]. To achieve dynamic changes in LED color temperature, it is necessary to quantitatively control the chromaticity of the light source. Studying LED light sources with adjustable color temperature in visible light communication systems has a certain significance. Adjusting the color temperature of LEDs according to different environments can make people feel comfortable with the light environment and create a healthy lighting environment. Generally, the color temperature range of indoor lighting is 3000 K~6500 K [6]. Using light sources with different color temperatures in different situations can meet people’s psychological and physiological needs. So, making the color temperature of the light source in visible light communication systems adjustable and controlling the chromaticity is currently a topic of great interest in research.

There have been studies on the use of multi-color LEDs for transmitting information in visible light communication systems. In 2015, Ke X Z et al. constructed an RGB LED visible light communication video transmission system and completed an experiment on video data stream transmission at a transmission rate of 1.5 Mbps [7]. In 2018, Zhu et al. conducted an experiment on an indoor visible light communication system using RGBCY LEDs and the wavelength division multiplexing (WDM) technique. The experiment attained a communication rate of 10.72 Gb/s and a communication distance of 1 m [8]. In 2018, Bian R et al. achieved a 10.2 Gbps three-channel visible light communication experiment using RGB LEDs and the WDM technique [9]. In the next year, the team used four different colored LEDs as light sources and the OFDM modulation method to complete an experiment on 15.73 Gbps VLC reliable transmission on a 1.6 m link [10]. In 2020, Hu et al. accomplished a transmission experiment via multi-color LEDs over a 1.2 m underwater link using DMT modulation and WDM techniques, achieving a communication rate of 20.09 Gbit/s [11]. In 2022, Qiu et al. used three LEDs and five micro-LEDs, alongside wavelength division multiplexing technology to successfully achieve a visible light communication experiment with a total communication rate of 25.20 Gbps when the communication distance is 25 cm [12]. In 2022, Zhang developed an LED visible light communication control system capable of achieving lighting effects and transmitting signals up to 3 m away with a transmission speed of 56,000 bit/s and low BER [13]. In the field of visible light communication, multi-channel visible light communication systems using multiple monochrome LEDs have achieved high communication rates, but there is no color control mechanism. The color of the light emitted by multiple LEDs poses a certain threat to human eyes [14,15]. Research shows that the color and brightness of the light source have an impact on the adjustment ability of the ciliary muscle of the human eye [16], which can cause visual fatigue and discomfort and easily lead to myopia.

In an indoor environment, visible light communication not only realizes the communication function but also meets the lighting requirements. It is also suitable for some special occasions, such as bars and studios, where the light source is not only white light but also requires adjustable color and chroma. As a result, the multi-color transmission system should also consider the light mixing and chroma control of the light source. This article conducts experiments and analysis on the chromaticity control of light sources in RGB LED visible light communication systems. By controlling the duty cycle of PWM in each channel and changing the proportions of red, green, and blue LEDs, respectively, different color temperatures can be obtained to achieve the purpose of controlling the chromaticity of mixed-color LEDs.

2. Theoretical Basis

To analyze the color rendering of LEDs, the Gaussian mathematical model (Y-model) proposed by Yoshi Ohno et al. agrees well with the actual spectral distribution of LEDs and was widely accepted. This model can be represented as follows [17]:

$$S_{LED}(\lambda ,{\lambda }_0,\Delta {\lambda }_{0.5})=Y_c\frac{g(\lambda ,{\lambda }_0,\Delta {\lambda }_{0.5})+2g^5(\lambda ,{\lambda }_0,\Delta {\lambda }_{0.5})}{3},$$

(1)

where $g(\lambda ,{\lambda }_0,\Delta {\lambda }_{0.5})=\exp [-{((\lambda -{\lambda }_0)/\Delta {\lambda }_{0.5})}^2]$; $\lambda$ is the wavelength; $Y_c$ is the spectral power at peak wavelength ${\lambda }_0$; and $\Delta {\lambda }_{0.5}$ is the half peak width.

The tristimulus value of a light source refers to the basic optical characteristics of the light source and is usually used to describe and measure the color of the light source. According to the spectral mathematical model of LED, the tristimulus values of $X$, $Y$, and $Z$ of the light source to be tested can be calculated, and the calculation formula is [18] as follows:

$$\{\begin{array}{l}X=K_m{\displaystyle {\int }_{380}^{780}S(\lambda )}\overline{x}(\lambda )d\lambda \\ Y=K_m{\displaystyle {\int }_{380}^{780}S(\lambda )}\overline{y}(\lambda )d\lambda \\ Z=K_m{\displaystyle {\int }_{380}^{780}S(\lambda )}\overline{z}(\lambda )d\lambda \end{array},$$

(2)

where $K_m=683lm/W$ as the constant; $S(\lambda )$ is the relative spectral power distribution; and $\overline{x}(\lambda )$, $\overline{y}(\lambda )$ and $\overline{z}(\lambda )$ are the color matching function, which is the average data of the CIE 1931 standard observer, also known as the spectrum triple stimulation function [18].

In the actual calculation, the CIE 1931 standard chromaticity tristimulus value of the light source to be tested is obtained by using the method of discrete summation and approximate integration calculation. The expression can be expressed as follows:

$$\{\begin{array}{l}X=K_m{\displaystyle \sum _{380}^{780}S(\lambda )}\overline{x}(\lambda )\Delta \lambda \\ Y=K_m{\displaystyle \sum _{380}^{780}S(\lambda )}\overline{y}(\lambda )\Delta \lambda \\ Z=K_m{\displaystyle \sum _{380}^{780}S(\lambda )}\overline{z}(\lambda )\Delta \lambda \end{array},$$

(3)

where $\overline{x}(\lambda )$, $\overline{y}(\lambda )$, and $\overline{z}(\lambda )$ can be determined by looking up tables, and the spectral sampling interval of $\Delta \lambda$= 1 is often taken.

According to the obtained light source three stimulus values, the corresponding color coordinates can be found. After the normalization of $X$, $Y$, and $Z$, the color coordinates $x$, $y$, and $z$ of the light source to be measured can be obtained:

$$\{\begin{array}{l}x=\frac{X}{X+Y+Z}\\ y=\frac{Y}{X+Y+Z}\\ z=\frac{Z}{X+Y+Z}\end{array},$$

(4)

In lighting systems, color temperature is a physical quantity used to define the chromaticity of a light source, which can measure the lighting quality of the light source. The relevant color temperature of the light source can be calculated from the chromaticity coordinates, and the formula for calculating the color temperature is as follows [19]:

$$T=-437n^3+3601n^2-6861n+5514,$$

(5)

where $n=\frac{x-0.3320}{y-0.1858}$; and $x$, $y$ is the color coordinate.

The color index is a parameter to evaluate the degree to which the light source restores the true color of an object. It is generally believed that the color presented by objects under natural light is the most authentic, with a color index of 100. The color index of the light source for a standard sample can be expressed as follows [20]:

$$R_i=100-4.6\Delta E_i,$$

(6)

where $\Delta E_i$ is the color difference of the sample under the reference light source and the light source to be tested, which can be obtained from the chromaticity coordinates.

The average color index of the light source for color samples 1 to 8 is called the general color index $R_a$:

$$R_a=\frac{1}{8}{\displaystyle \sum _{i=1}^8{R}_i},$$

(7)

3. Research on RGB LEDs Dimming

3.1. Dimming Method and Calculation Method

Dimming technology has become an important aspect of LED driver technology, and there are three commonly used LED dimming methods: DC dimming, PWM dimming, and thyristor dimming [21]. When the current is too small, the thyristor will turn off, making the dimming effect unstable and unsuitable for use in visible light communication systems [21]. Meanwhile, DC dimming is achieved by changing the driving peak current of the LED to change the luminous flux. This dimming method can affect the chromaticity shift and color temperature change in the LED [22]. The PWM dimming method is achieved by changing the duty cycle of the LED light source, thereby changing the average luminous flux. The dimming performance is flexible and can accurately control the luminous flux, thereby accurately controlling the brightness change in the LED and reducing the impact of current changes during amplitude modulation on the stability of the light source [23]. In engineering practice, the color difference caused by PWM dimming is often not considered [24].

In the PWM dimming method, the peak value of the driving current remains unchanged, and the LED is dimmed by adjusting the duty cycle of the PWM. The expression is as follows:

$$I_{avg}=I_{peak}\cdot D,$$

(8)

where $I_{avg}$ represents the effective value of the driving current, $I_{peak}$ represents the magnitude of the driving peak current, and $D$ represents the duty cycle of PWM.

For the convenience of calculation, it is usually assumed that the PWM duty cycle of the input driver module is directly proportional to the luminous flux output by the light source [25], which satisfies the following:

$$\Phi =D{\Phi }_{\mathrm{Max}},$$

(9)

where $D$ is the duty cycle of the input PWM signal, $D<1$; ${\Phi }_{\mathrm{Max}}$ is the maximum output luminous flux; and $\Phi$ is the luminous flux of the output signal.

According to Glassman’s law of color mixing, there is a formula for the luminous flux output of a three-color mixture [26]:

$$\Phi =D_r{\Phi }_r+D_g{\Phi }_g+D_b{\Phi }_b,$$

(10)

where $D_r$, $D_g$, and $D_b$ are the input duty cycle of PWM; ${\Phi }_r$, ${\Phi }_g$, and ${\Phi }_b$ are the maximum output luminous flux of each light source; and $\Phi$ is the output luminous flux of the mixed light.

In the CIE-1931 standard colorimetric system, it is specified that the stimulus value of $Y$ is equal to the luminous flux, so in the following text, it can be changed to $Y$. According to the principle of color mixing and the CIE 1931 color coordinate calculation method, the color coordinates after mixing with three light sources should meet the following [27]:

$$x=\frac{R_r{D}_r{x}_r+R_g{D}_g{x}_g+R_b{D}_b{x}_b}{R_r{D}_r+R_g{D}_g+R_b{D}_b},$$

(11)

$$y=\frac{R_r{D}_r{y}_r+R_g{D}_g{y}_g+R_b{D}_b{y}_b}{R_r{D}_r+R_g{D}_g+R_b{D}_b},$$

(12)

where $x$ and $y$ represent the color coordinates of a mixed light source consisting of three types of light sources; $(x_r,y_r)$, $(x_g,y_g)$, and $(x_b,y_b)$ represent the color coordinates of red, green, and blue LEDs, respectively; $R_r=\frac{Y_r}{y_r}$, $R_g=\frac{Y_g}{y_g}$, and $R_b=\frac{Y_b}{y_b}$ represents the sum of the three stimulus values of the light source under full current operation; $D_r$, $D_g$, and $D_b$, respectively, represent the PWM input duty cycle of red, green, and blue LEDs.

From Equations (10) to (12), the duty cycles of the three channels can be obtained as follows:

$$D_r=\frac{(y_g-y_b)(x_b-x)+(y-y_b)(x_g-x_b)}{(y_g-y_b)(x_b-x_r)+(y_r-y_b)(x_g-x_b)}\cdot \frac{y_{r}Y}{y{Y}_r},$$

(13)

$$D_g=\frac{(y_b-y_r)(x_r-x)+(y-y_r)(x_b-x_r)}{(y_b-y_r)(x_r-x_g)+(y_g-y_r)(x_b-x_r)}\cdot \frac{y_{g}Y}{y{Y}_g},$$

(14)

$$D_b=\frac{(y_g-y_r)(x_r-x)+(y-y_r)(x_g-x_r)}{(y_g-y_r)(x_r-x_b)+(y_b-y_r)(x_g-x_r)}\cdot \frac{y_{b}Y}{y{Y}_b},$$

(15)

where $Y_r$, $Y_g$, and $Y_b$ are the maximum output luminous flux when the input duty cycle of the red, green, and blue light sources is 100%; $Y$ is the output luminous flux of a hybrid light source; $(x_r,y_r)$, $(x_g,y_g)$ and $(x_b,y_b)$ are the color coordinates of red, green and blue, respectively; and $(x,y)$ is the color coordinate of the mixed light source.

3.2. Simulation Analysis of Dimming

The duty cycle is proportional to the luminous flux, and the luminous flux determines the LED luminance. The larger the luminous flux, the brighter the LED luminance. Therefore, the duty cycle is also directly proportional to the luminous brightness of the LED. Calculate and simulate the ratio of different brightness of RGB LEDs controlled by the circuit, change the ratio of brightness of a single LED, and observe the changes in color temperature and color coordinates of the RGB LEDs hybrid light source via simulation. The arrangement of the three types of LEDs is shown in Figure 1, with an observation area of 500 mm × 500 mm and a distance of 100 cm from the emitter. In the simulation, the distance remains unchanged; only the brightness ratio of the LED is changed, and the total luminous flux of the set LED is 100 lm.

(1) When the control circuit adjusts the luminous flux ratio of RGB LEDs, different color temperatures can be obtained. Simulate the changes in different color temperatures and the corresponding color coordinates based on the ratio calculated from Equations (15) to (16). As shown in Figure 2, the color coordinate $x$ shows a decreasing trend with the increase in color temperature, while the color coordinate $y$ fluctuates up and down with the increase in color temperature. The fluctuation is greater in the low color temperature stage and smaller in the high color temperature stage.

When the duty cycle ratios of the RGB LEDs are set to 0.6:0.28:0.12, 0.5:0.32:0.19, 0.47:0.33:0.2, and 0.45:0.34:0.21, the mixed light source on the observation surface is shown in Figure 3. At this time, the color temperature of the mixed light source is 3470 K, 5677 K, 6528 K, and 7265 K. The color coordinates are (0.4044, 0.3847), (0.3286, 0.3334), (0.3116, 0.3336), and (0.3038, 0.3099), and the total amount of light is around 88 lm. From the simulation, it can be seen that the proportion of RGB LEDs has a significant impact on the color coordinates and color temperature of the synthesized white light, with a relatively small impact on luminous flux. By changing the duty cycle of the red, green, and blue LEDs, the hybrid white light source can change from warm white to cold white.

(2) Maintain a constant distance of 100 cm between the receiving surface and the light source, and simulate the changes in the average light intensity of the receiving surface under different color temperatures. As shown in Figure 4a, the average light intensity of the receiving surface under different color temperatures is around 1872 lx, with an error of less than 5 lx between the maximum and minimum values. When the color temperature is 3500 K, 5500 K, 6500 K, and 7300 K, it can be seen from the average light intensity distribution of the receiving surface simulated in Figure 4b–e that there is almost no difference. In summary, as the color temperature of the light source changes, the change in the illuminance intensity of the receiving surface is very small and can be ignored.

(3) Maintain a color temperature of 6500 K and simulate the analysis of light intensity on the receiving surface at different distances. As shown in Figure 5a, as the distance between the light source and the receiving surface increases, the energy received by the receiving surface becomes less and more dispersed. When the distance between the light source and the observation surface is 50 cm, 100 cm, 200 cm, and 300 cm, it can be seen from the light intensity of the receiving surface simulated in Figure 5b–e that the energy dispersion increases with the increase in distance. In summary, the light intensity on the receiving surface decreases as the distance increases, and distance has a significant impact on the light intensity on the receiving surface.

3.3. Dimming Experiment

This experiment uses hexagonal RGB LEDs beads to form a luminescent light source and uses the HP350 spectral illuminometer manufactured by Hangzhou Double Color Intelligent Testing Instrument Co., Ltd., which is produced in Hangzhou, Zhejiang, China, to measure the light color parameters. When the three-color LED is operated at full current, the light color parameters are shown in

Table 1. Three LED parameters.

LED Type	Chromatic Coordinates	Peak Wavelength (nm)	FWHM (nm)	Luminous Intensity (cd)	Luminous Flux (lm)
Red LED	(0.6894, 0.3099)	630	20	1.8~2.0	67.9
Green LED	(0.1689, 0.7232)	520	20	5.0~6.0	178.1
Blue LED	(0.1434, 0.0416)	460	20	1.0~1.5	29.0

, and the relative spectral power distribution is shown in Figure 6.

Adjust the duty cycle of the LED and measure the brightness of the LED. The variation curve of the measured LED brightness with the duty cycle is shown in Figure 7. The brightness of the green light changes significantly with the duty cycle, while the changes in the red and blue light are relatively close, with relatively small changes compared to the green light.

The dimming device mainly consists of a switching power supply, control system, drive circuit, and red, green, and blue LED light sources. Figure 8 is a block diagram of the dimming device. The control system sends instructions to the driving circuit to drive a three-channel LED, obtaining white light with different color temperatures based on different duty cycles, thereby achieving the effect of LED color temperature adjustment. Figure 9 shows the physical image of the dimming device.

RGB LEDs can be mixed in different proportions to obtain a color temperature range of 2500 K~8500 K. To study the optimal color rendering performance of the light source module during the dimming process, 12 sets of combinations with good color rendering performance were selected in this paper. The mixed light parameters measured using the HP350 spectral illuminometer are shown in

Table 2. Comparison between measured data and calculated data.

RGB Proportion	Measured Color Temperature (K)	Calculate Color Temperature (K)	Color Temperature Difference (K)
0.557:0.301:0.142	2539	2500	39
0.502:0.280:0.218	3030	3000	30
0.476:0.347:0.177	3525	3500	25
0.439:0.304:0.257	4012	4000	12
0.417:0.370:0.213	4532	4500	32
0.405:0.323:0.272	5023	5000	23
0.382:0.361:0.257	5510	5500	10
0.364:0.356:0.281	6032	6000	32
0.347:0.363:0.290	6526	6500	26
0.336:0.355:0.308	7036	7000	36
0.313:0.382:0.305	7540	7500	40
0.302:0.381:0.317	8032	8000	32

. From Table 2, it can be seen that compared with the measured color temperature, the color deviation calculated according to Equation (5) is lower than the 50 K color temperature limit that can be resolved by the human eye. The average color temperature error is 0.609%, and the difference between the measured and calculated values is small. Therefore, the color temperature adjustment in the experiment is relatively stable.

The theoretical color coordinates of the synthesized light source are obtained from Equations (3) to (4), and the actual color coordinates are measured using a spectral illuminometer. Figure 10 shows the variation curve of the measured and calculated color coordinates with color temperature. The error of the calculated excellent coordinate $x$ is less than 0.0007, and the error of the color coordinate $y$ is less than 0.0014. The measured color coordinate is in good agreement with the calculated color coordinate. The color coordinates have a significant impact on low color temperature light sources, while they have a relatively small impact on high color temperature light sources, which is consistent with the simulation results mentioned above.

The duty cycle of RGB LEDs obtained from Equations (13) to (15) can obtain mixed white light with different color temperatures. As shown in Figure 11, the duty cycle of the red, green, and blue LEDs varies with color temperature. It can be seen in Figure 11 that as the color temperature increases, the duty cycle of the red LED decreases, while the duty cycle of the green LED and blue LED increases.

The HP350 spectral illuminometer is used to measure the luminous flux, irradiance, color tolerance, light intensity, and a color index of the mixed light source. In Figure 12, it can be seen that the maximum luminous flux set in the experiment is 100 lm, and the luminous flux of the mixed light varies between 92 lm and 100 lm. The resulting luminous flux of the mixed white light is relatively high, and when adjusting the color temperature, the fluctuation of the luminous flux is very small, with a fluctuation of 2.24%. Therefore, the influence of color temperature on the luminous flux is relatively small, which is consistent with the simulation results. The irradiance range of mixed white light is 3.4 W/m²~4.2 W/m². When the color temperature range is 5000 K~6500 K, the irradiance reaches the maximum, and the lighting effect is the best. The color tolerance Duv is stable at around 0, which is specified to be less than 5.5 × 10⁻³ and can meet the lighting standards [28].

In Figure 13, it can be seen that the illumination value fluctuates less with the change in color temperature, with a difference of only 8.2 lx between the maximum and minimum values. The change in color temperature has a small impact on the illumination intensity, which confirms the conclusion of the simulation. In Figure 13, the comparison between the calculated color index and the measured color index according to Equations (6) and (7) shows that the theoretical value of the color index is in good agreement with the measured value. The color index is greatly affected by the color temperature. When the color temperature is within the range of 5500 K~6500 K, the color index is the best. This color temperature range is the light and color temperature at noon. The effect of restoring the color of the object itself is the best, which also conforms to natural law. The light source with a color index of more than 75 is a high-quality light source [29]. The color index of the mixed white light is more than 76 within the adjustable color temperature range, and the maximum color index is 92, indicating that the experimental mixed white light effect is good.

Using the HP350 spectral illuminometer to measure the light intensity at different color temperatures and distances, as shown in Figure 14, the curve of light intensity with distance at different color temperatures is shown. The curve of light intensity with distance at each color temperature almost overlaps, indicating that the influence of color temperature on light intensity is not significant. However, as the distance increases, the light intensity decreases, indicating that the distance has a significant impact on the light intensity, and verified the conclusions obtained from the simulation.

Maintain a distance of 50 cm, as shown in Figure 15, to measure the light intensity at different positions on the receiving surface. The light intensity at direct light is the largest. At the edge of the receiving surface, the light intensity is the smallest, with a maximum illumination value of up to 1500 lx. The illuminance value on the receiving surface is uniform at 400 lx~1200 lx, which meets the requirements of the 300 lx~1500 lx illuminance value formulated by the International Organization for Standardization, with uniformity and lighting effect.

To verify the accuracy of the simulation results, the proportions of RGB LEDs were adjusted to 0.6:0.28:0.12, 0.5:0.32:0.19, 0.47:0.33:0.2, and 0.45:0.34:0.21 via the driver circuit, which were consistent with the simulation proportions. The color temperatures of the mixed white light measured using the HP350 spectral illuminometer were 3472 K, 5670 K, 6530 K, and 7260 K, which were almost equal to the simulated color temperatures. Figure 16 shows the measured spectrogram, and Figure 17 shows the position information of the mixed white light on the CIE 1931 chromaticity diagram. At this time, the chromaticity coordinates are (0.4043, 0.3846), (0.285, 0.3333), (0.3117, 0.3335), and (0.3038, 0.3098), which are very close to the simulated chromaticity coordinates, indicating that the mixed white light has a good effect.

4. Design and Experiment of RGB LEDs Visible Light Communication System

4.1. System Working Principle and Experimental Device

The visible light communication system consists of three parts: the transmitter, the indoor channel, and the receiver. As shown in Figure 18, the structure diagram of a visible light communication system is shown. The light emitted by three different colored LED chips at the transmitter end can be regarded as three channels, so color division multiplexing can be used for multiplexing transmission, thereby improving the communication performance of the system. Three channels of PWM are generated by the STM32 to drive three kinds of LEDs, and then the three colors are mixed into white light in a certain proportion for output and transmission in the indoor channel. At the receiving end, monochromatic radiation is separated from the white light with corresponding filters to form three channels, and receiving signals using a 905 nm silicon avalanche photodiode detector and displayed on the oscilloscope; Then, measure the received optical power using an OPHIRPD300-UV optical power meter and record the data using a computer; finally, measure the color temperature and light intensity of the mixed white light using a spectral illuminometer. The RGB LEDs visible light communication system designed in this article can achieve high-speed data communication through three parallel signals, and use the PWM dimming method to output white light to achieve chromaticity control. The experimental setup is shown in Figure 19.

4.2. Analysis of Experimental Results

Due to the integration of lighting and communication in this system, it is necessary to analyze the communication performance of optical communication systems. The light source is vertically illuminated onto the receiving surface, and the color temperature of the light source is adjusted according to the mixing ratios obtained from the dimming experiment, which are 0.6:0.28:0.12, 0.5:0.32:0.19, 0.47:0.33:0.2, and 0.45:0.34:0.21. Ensure that the distance between the transmitter and receiver remains fixed, change the modulation bandwidth, and calculate the error rate under different modulation bandwidths to obtain the maximum modulation bandwidth for reliable transmission of the system. In the experiment, the communication distance was 250 cm and the modulation bandwidth of the three channels was changed. The total modulation bandwidth under different color temperatures was recorded and synthesized, and the error rate was calculated. Figure 20 shows the error rate curve with modulation bandwidth at five color temperatures of 3594 K, 4564 K, 5497 K, 6570 K, and 7550 K is shown. As shown in Figure 20, as the modulation bandwidth increases, the bit error rate also increases. When the error rate is below 10⁻³, the maximum modulation bandwidth for the five color temperatures can reach 9.2 MHz, 10 MHz, 11 MHz, 11.5 MHz, and 11.7 MHz, respectively. The modulation bandwidth for high color temperatures is higher than that for low color temperatures. When the modulation bandwidth is 9 MHz, the error rate at all color temperatures is less than 3.8 × 10⁻³, achieving reliable transmission of visible light communication systems.

When the modulation bandwidth is 8 MHz, Figure 21 shows the error rate curve of the five color temperatures of 3594 K, 4564 K, 5497 K, 6570 K, and 7550 K with the distance shown. As shown in Figure 21, in the actual test, as the distance increases, the error rate of the system also increases, and the speed of change becomes faster and faster. When the transmission distance is 350 cm, the error rate at each color temperature is lower than the limit error rate value of 3.8 × 10⁻³ for forward error correction. The bit error rate of the cold white temperature is significantly lower than that of the warm white temperature. The conclusion is that as the color temperature increases, the communication performance of the system improves. However, when the color temperature exceeds 6500 K, the increase in color temperature has a smaller impact on the communication system performance.

4.3. Discussion

The visible light communication system using RGB LEDs as the light source in this article can conveniently use color division multiplexing technology to improve the transmission performance of the entire system. However, the research on RGB multi-color visible light communication systems was conducted in the laboratory and has not been used in daily life. Moreover, the three-channel system designed in this article has not reached the limit of the number of visible light band channels. In the future, the transmission antenna can be reasonably designed to increase the communication bandwidth while mixing multi-color LEDs with white light, making the information transmission distance longer and achieving lighting standards in indoor applications, thus achieving the goal of universal use in daily life.

5. Conclusions

This article investigates the control chromaticity in light sources for visible light communication systems. LED white light sources with adjustable color temperatures were obtained through simulation and experiments. When the error rate of each color temperature is below 3.8 × 10⁻³, the modulation bandwidth of the system reaches 11.7 MHz, the longest communication distance is 5 m, and the illumination intensity is above 400 lx. Thus, both the communication and illumination functions of visible light are achieved, and the following conclusions are obtained:

(1)

The light source with different color temperatures can be obtained by changing the ratio of red, green, and blue LEDs. The general color index of the light source with a color temperature between 5500 K and 6500 K is the best. The influence of color temperature on the illumination intensity of the receiving surface at the same distance can be ignored; the distance has a significant impact on the illumination of the receiving surface, as the distance increases. The light intensity rapidly decreases.

(2)

The optical power under different color temperatures and distances is measured, and it is found that the color temperature has a small impact on the receiving power value, while the distance has a greater impact. With the increase in distance, the optical power value decreases in the exponential decay trend.

(3)

Based on communication experiments under different color temperatures, it was concluded that the communication performance of the system is better in the high color temperature range and significantly better than in the low color temperature range. As the distance increases, the communication error rate under different color temperatures continues to increase.