# Modeling and Spatial Diversity-Based Receiving Improvement of In-Flight UAV FSO Communication Links
## 4 In-Flight UAV FSO Communication Improvement Based on Spatial Diversity  
The spatial diversity technology can effectively reduce the influence of the phase distortion and light intensity fluctuation, so as to achieve the signal gain [13]. In the UAV FSO link, the spatial diversity with single-in and multiple-out (SIMO) is suitable to be adopted, as shown in Figure 8, in which each optical antenna in the receiving array independently receives the optical signals. After coupling to the fiber, the signal will be compensated and reconstructed by their corresponding receiver, and the equal gain merge (EGC) algorithm will be used to merge each signal [21].  
Figure 6: Normalized distribution of the channel coefficient with different wind resistances in yaw motion.  
Figure 7: FSO communication performance with different wind resistances of the UAV in yaw motion at the same horizontal plane. (**a**) Outage probability; (**b**) average BER.  
The linear combining process for the diversity technology can be expressed as:  
\[y=\sum_{i=1}^{M}\widetilde{w}_{i}(t)x_{i}(t) \tag{24}\]  
where \(x_{i}(t)\) is the signal of each path, which can be expressed as:  
\[x_{i}(t)=a_{i}(t)+n_{i}(t) \tag{25}\]  
where \(a_{i}(t)\) denotes the signal, and \(n_{i}(t)\) is the noise. \(\widetilde{w}_{i}(t)\) represents the weight coefficient of each signal in the process of merging, which can be expressed as:  
\[\widetilde{w}_{i}(t)=w_{i}(t)exp[j\theta_{i}(t)] \tag{26}\]  
where the real part \(w_{i}(t)\) represents the proportion of signals in each path, and the imaginary part \(e^{i\theta_{i}(t)}\) represents the phase alignment of signals in each path to achieve coherent combining effect. Equal-gain combining (EGC) algorithm simplifies all the weighting coefficients to 1 and only performs phase alignment. It can both effectively improve the SNR of the combined signal and avoid the contingency of results.  
In this simulation, two and four receivers are considered respectively for comparison. The parameters are shown as follows: the field angle \(\theta_{FOV}=40\) mrad, the variance of transceiver end position deviation \(\sigma_{rp}^{2}=\sigma_{rp}^{2}=1\) cm, the variances of the angular deviation \(\sigma_{ro}^{2}=\sigma_{lo}^{2}=1\) mrad, the fuselage of the tilt angle \(\varphi=5\) mrad, and the random angle deflection variance around the \(y\) axis \(\sigma_{\pi}^{2}=1\) mrad. The number of receivers in the receiving array is 1, 2, and 4, respectively. Figure 9 shows the BER performance against the SNR, which represents the quality of the FSO communication link.  
Figure 8: Schematic diagram of the spatial diversity receiving structure for SIMO FSO communications.  
Figure 9: FSO communication performance of the UAV with single-, double- and four-receiver arrays.  
As shown in Figure 9, the average BER is significantly reduced compared to that without the diversity receiving technology, and the transmission performance of the UAV FSO system is effectively improved. Without the diversity receiving technology, the average BER of the received signal is still higher than \(10^{-4}\) under the SNR higher than 20 dB, and the FSO communication link of the UAV is unstable. When the receiving array composed of two receivers is used, the average BER is less than \(10^{-4}\) when the SNR is higher than 15 dB. When the receiving array composed of four receivers is used, the average BER is less than \(10^{-4}\) when the SNR is higher than 10 dB. When the SNR is around 13 dB, the average BER drops to \(10^{-5}\). Therefore, it can be seen that the application of diversity receiving technology can effectively improve the quality of communication and enhance the stability of the link.