# Post-Flood UAV-Based Free Space Optics Recovery Communications with Spatial Mode Diversity
## 5 Results and Discussion
Top panel (**a–e**) shows the power coupling coefficients at low-refractive-index structure values, and bottom panel shows (**f–j**) those at high-refractive-index structure values. Color legend of normalized power coupling coefficients for all plots is on the bottom right corner. Overall, 25% to 44% of power was leaked to other modes during rainfall, prior to mode diversity. The power leakage was more significant for adjacent modes to the dominant modes and gradually decreased for modes further away from the dominant modes. With increased turbulence strength, the crosstalk was more prevalent and the power distribution of the modes was more dispersed. After mode diversity reception, an increase of 10% to 19% in the dominant mode power was observed. A larger amount of power was successfully  
Figure 8: Variation in normalized power coupling coefficients on _LP01_ mode after spatial mode diversity reception: (**a,f**) clear night, (**b,g**) clear day, (**c,h**) light rain, (**d,i**) medium rain, (**e,j**) heavy rain. Top panel (**a–e**) shows the power coupling coefficients for primary channel at low-refractive-index structure values, and the bottom panel shows (**f–j**) those for backup channel at high-refractive-index structure values. Color legend of normalized power coupling coefficients for all plots is on the bottom right corner. Figure 9: Variation in normalized power coupling coefficients on _LP11_ mode after spatial mode diversity: (**a,f**) clear night, (**b,g**) clear day, (**c,h**) light rain, (**d,i**) medium rain, (**e,j**) heavy rain. Top panel (**a–e**) shows the power coupling coefficients for primary channel at low-refractive-index structure values, and the bottom panel shows (**f–j**) those for backup channel at high-refractive-index structure values. Color legend of normalized power coupling coefficients for all plots is on the bottom right corner. maintained in the dominant modes through the switch to the backup channels during SINR dips. The inter-modal crosstalk matrices for the primary channel, secondary channel, and composite channel after mode diversity is shown Figure 10. The power in the dominant mode of each channel was improved under all weather conditions. Without the mode diversity scheme, there were interruptions in the data transmission from sensors. By incorporating mode diversity, uninterrupted data transmission from sensors was observed, even under heavy rain due to the backup channels on different LG modes experiencing different channel degradations from the primary channels. The average diversity gain from spatial mode diversity was 0.97 dB. The average bit error rate (BER) versus SINR for all channels under various weather conditions was measured and compared, without and with spatial mode diversity, as shown in Figure 4:0 It was observed that spatial mode diversity successfully enhanced the BER by 38% to 55% from the original BER. After spatial mode diversity, a satisfactory BER below the 7% forward error correction (FEC) limit of \(3.8\times 10^{-3}\) was attained, at SINRs higher than 20 dB, under all levels of rain. An FEC of 7% was used to provide a 0.3 dB coding gain to better mitigate atmospheric turbulence. Figure 4:1 Inter-modal crosstalk matrices for primary channel and secondary channel before mode diversity, and composite channel after mode diversity. The transmitted mode number and received mode number, i, are given in Figure 4:2 The color legend shows the normalized power coupling coefficient. Through UAV-FSO spatial diversity, despite mobility restrictions due to floods, vital health statistics from injured flood victims could be forwarded to a patient cloud-based health monitoring system accurately and timely, for hospitals to make critical preparations for relevant medical treatment upon the victims' arrival. To verify the experimental measurements, the average values of \(C_{n}^{2}\) were computed using [67]:  
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