# AI-Enabled Intelligent Visible Light Communications: Challenges, Progress, and Future
## 2 Status and Challenges of VLC
### Visible Light Communication E2E Channel
The carrier lifetime \(\tau\), which determines the modulation bandwidth, is given as [18]:  
\[\tau=\frac{n}{R}\approx\frac{n}{An+Bn^{2}+Cn^{3}+an+bn^{2}+cn^{3}+dn^{4}\ldots} \tag{5}\]  
The carrier density is determined by the effective injected current density, which is expressed as [27]:  
\[\frac{\Delta n}{\Delta R}=-R+\frac{\eta_{inj}J}{q_{e}} \tag{6}\]  
\[J=\frac{I}{w_{active}} \tag{7}\]  
where \(\eta_{inj}\) is the injection efficiency, \(J\) is the current density, \(q_{e}\) is the elementary charge, \(I\) is the current intensity, and \(w_{active}\) is the thickness of the effective active region. Then, the optical output power is given by [18]:  
Figure 1.0  
here, \(V_{active}\) is the volume of the active layer, \(E_{phot}\) is the photon energy and \(\eta_{EQE}\) is the external quantum efficiency (EQE). As can be seen here, since the initial transmission signal is in the form of a voltage; it first goes through a nonlinear V-I conversion [21]. Then, the relationship between current and carriers is a dynamic nonlinear relationship. Moreover, at higher currents, there will be an efficiency droop [28]. It is also easy to understand that the effective radiative carriers have only second-order terms and the total number of carriers has higher-order terms. When the current increases, the number of carriers increases, and the effective light-emitting carrier ratio \(P_{ratio}\) will first increase and then decrease. Figure 1.1  
Because of the aforesaid dynamic nonlinear equations, all of the carrier-related publications mentioned above use a tiny signal and low bandwidth assumption in their derivation. The carrier density is minimal enough to ignore the higher-order terms due to the low current density caused by the tiny signal. If the signal has a limited bandwidth, the pulse duration is sufficient to make the left side of Equation (6) equal to zero. Abandoning the higher-order and differential terms would greatly simplify the modeling of visible light channels, but it also poses the problem of not being able to satisfy the modeling of high-speed VLC. In later work based on both the carrier rate equation and an equivalent discrete-time circuit modeling [7; 30], the same assumptions were required, and the experimental verification of the channel modeling was performed with only 2 MHz [30]. In addition to the large signals and high bandwidth that make visible light channel modeling difficult [19; 21], another challenge is transmission channel modeling [31; 32; 33]. Much work has focused on indoor visible light transmission modeling, such as multi-path impulse-response analysis [31], ray-tracing methods based on channel impulse response [32], and photon-based statistical modeling [33]. However, this is only one aspect of visible light communication applications. When transmitting in an outdoor environment, the effects of atmospheric turbulence in visible wavelengths must also be modeled. Water environment modeling is also essential while broadcasting underwater. Furthermore, as illustrated in Figure 1, numerous modules introduce nonlinearities. For example, there are high-power electrical amplifiers at the transmitter side, which can have large nonlinearities at high currents. The linear dynamic range of the receiver PIN is usually smaller than the LED, and too much optical power can cause saturation of the PIN, which is serious especially when using APD detectors. Therefore, the nonlinear modeling of the driver circuit and the receiver based on different detector implementations are also very important. Because of the additional optoelectronic and electro-optical conversion, as well as the rest of the nonlinear modules, the VLC end-to-end channel is extremely complex, as summarized in Figure 1.2 This also presents a significant problem for VLC's high-speed connectivity.