Contact Plan Design For Optical Interplanetary Communications

TL;DR

This paper presents a novel contact plan design framework for optical interplanetary communications that accounts for retargeting delays, significantly improving network capacity and scheduling efficiency over previous methods.

Contribution

It introduces the first PAT-aware contact plan framework that models retargeting delays, optimizing optical link schedules for interplanetary networks.

Findings

MILP scheduler achieves 30% higher capacity than greedy algorithms.

Optimal schedules favor fewer, longer links to reduce retargeting delays.

Ignoring retargeting delays overestimates network performance.

Abstract

Space exploration missions generate rapidly increasing volumes of scientific telemetry that far exceed the capacity of today's manually scheduled, RF-based deep-space infrastructure. Free-space optical (FSO) communications promise orders of magnitude higher throughput, but their narrow beams require precise pointing, acquisition, and tracking (PAT) for link establishment and tightly synchronized contact schedules. Critically, no existing contact plan design (CPD) framework accounts for optical head retargeting delay, the time spent during coarse pointing and link acquisition before data transmission begins, which directly reduces usable contact time. Retargeting delay is the dominant impairment unique to optical networks, which induces a seconds-to-minutes-long mechanical pointing process for an optical terminal's laser from its current partner to the next receiver. This paper introduces the first PAT-aware CPD framework for optical interplanetary backhaul networks. The model captures directional temporal flows across both direct-to-Earth optical links and two-hop relay paths using delay/disruption-tolerant networking (DTN) satellites. We also introduce an optical network duty-cycle metric that quantifies the proportion of time spent transmitting to the contact window duration, exposing capacity lost to retargeting delay. Our results show that our MILP scheduler delivers over 30 percent higher network capacity than a greedy algorithm. More importantly, the results uncover a fundamental behavioral shift: when retargeting delays are modeled accurately, optimal schedules favor fewer but longer optical links that maximize throughput while minimizing retargeting overhead. These findings demonstrate that zero-delay assumptions substantially overestimate achievable performance and yield unrealistic contact plans.