# Misalignment-Resilient Propagation Model for Underwater Optical Wireless Links +
## 5 Conclusions  
This paper presented a simple yet powerful tool based on the Monte Carlo algorithm for modeling the propagation of photons in the underwater medium. Several novel contributions to the area of underwater optical wireless communications were reported, and new features were added to the already existing simulation algorithms. An accurate model of the beam divergence was described, supported by the analysis of lateral offset and angular misalignment between the transmitter and receiver. A receiver configuration with multiple sensors and lenses laid out on a \"circle packing in a circle\", including a precise treatment of photon refraction at the lens interface, was proposed, which showed increased tolerance to misalignment. The assessment of system performance was conducted based on the maximum  
Figure 17: Comparison between the predicted and expected offset radius for a Tx–Rx distance of 1 m.  
Figure 18: Comparison between the predicted and expected offset angle for a Tx–Rx distance of 1 m.  
lateral offset for different sensor schemes, water types, propagation distances, and angular misalignments, which proved the existence of an optimal divergence in agreement with previous results. Some relevant results were achieved: (1) the ideal divergence of the emitter's beam was shown to be around 15\({}^{\circ}\), independent of the water turbidity for a 1 m Tx-Rx distance and considering a 7-lense scheme; (2) the ideal divergence for clear waters was found to be around 17\({}^{\circ}\) for a distance between the Tx and Rx of 1 m, while for a length of 0.5 m, the optimum divergence was 21\({}^{\circ}\); (3) the architecture of the receiver with multiple sensors arranged in a compact geometry was proven to exhibit an increase in the MALO by approximately a factor of 3; and (4) the analysis of the Tx-Rx rotation revealed that rotating the emitter increased the optimal divergence, whereas turning the plane of the sensors decreased it. Moreover, a supervised learning algorithm successfully predicted the lateral offset and angle of the AUV based on the received light power distribution of each lens in a fixed sensor configuration. There was good agreement between the results predicted by the algorithm and the simulation, with a maximum RMS error of 6 mm and 10\({}^{\circ}\) for the predicted values of the lateral and angle offset parameters, respectively. The assessment of the limitations of the optical wireless underwater communication link under misalignment conditions in application scenarios involving AUVs and the identification of optimum operating conditions might be of interest to the research community and design engineers, particularly those looking to implement wireless sensor networks and the transfer of data between nodes and autonomous underwater vehicles. Future work will include obtaining simulation results for longer distances between the transmitter and receiver and the corresponding MALO results, allowing one to assess the performance of medium-range links as well as the feasibility of the offset prediction algorithm in a real AUV scenario application. Conceptualization, L.M.P. and H.M.S. ; methodology, L.M.P. and H.M.S. ; software, V.M.M. ; validation, V.M.M., L.M.P. and H.M.S. ; formal analysis, J.H.A., J.S.T., H.M.S. ; investigation, V.M.M. ; resources, L.M.P. ; data curation, V.M.M., J.H.A. and J.S.T. ; writing--original draft preparation, V.M.M., J.H.A. and J.S.T. ; writing--review and editing, J.H.A., J.S.T. and H.M.S. ; visualization, V.M.M., J.H.A. and J.S.T. ; supervision, L.M.P. and H.M.S. ; project administration, L.M.P. ; funding acquisition, L.M.P. All authors have read and agreed to the published version of the manuscript. This research was funded by the Portuguese Foundation for Science and Technology, Fundacao para a Ciencia e a Tecnologia (FCT), through the individual research grant 2020.06011.BD, co-financed by the European Social Fund through the North Portugal Regional Operational Programme, Programa Operacional Regional do Norte (NORTE 2020). Not applicable.