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Performance degradation due to target deviation by, for example, drift orjitter, presents a significant issue to inter-satellite laser communications.In particular, with periodic acquisition for positioning the satellitereceiver, deviation may arise in the time period between two consecutiveacquisition operations. One solution to mitigate the issue is to use adivergence angle at the transmitter being wider than that if the receiverposition is perfectly known. However, as how the deviation would vary over timeis generally very hard to predict or model, there is no clear clue for settingthe divergence angle. We propose a robust optimization approach to the problem,with the advantage that no distribution of the deviation need to be modelled.Instead, a so-called uncertainty set (often defined in form of a convex setsuch as a polytope) is used, where each element represents a possible scenario,i.e., a sequence of deviation values over time. Robust optimization seeks thesolution that maximizes the performance (e.g., sum rate) that can beguaranteed, no matter which scenario in the uncertainty set materializes. Tosolve the robust optimization problem, we deploy a process of alternatelysolving a decision maker's problem and an adversarial problem. The formeroptimizes the divergence angle for a subset of the uncertainty set, whereas thelatter is used to explore if the subset needs to be augmented. Simulationresults show the approach leads to significantly more robust performance thanusing the divergence angle as if there is no deviation, or other ad-hocschemes.

Robust Divergence Angle for Inter-satellite Laser Communications under Target Deviation Uncertainty