satellite system designers

Abstract: Ensemble decoding improves decoding reliability by combining component decoders with complementary failure events. Existing approaches typically obtain this diversity from code-specific structure, such as code automorphisms, multiple parity-check representations, or targeted modifications of the message-passing graph. In this work, we instead learn the diversity of an ensemble of weighted belief propagation decoders by jointly optimizing trainable Tanner-graph edge weights. A central design question is how the training objective should distribute gradient among the ensemble members to promote complementary decoding behavior. To this end, we compare four ensemble objectives under direct gradient-based optimization and identify best-member training as the most effective approach. For a (64,32) progressive edge-growth (PEG) low-density parity-check (LDPC) code, the resulting ensemble outperforms the considered trained and untrained belief-propagation-based ensemble baselines. With 10 members, it provides a gain of approximately 0.66 dB over a single belief propagation decoder at a target frame error rate (FER) of $10^{-4}$. Similar behavior is observed for a (128,64) CCSDS LDPC code, indicating that the learned complementarity is not specific to PEG. Although the ensemble performance improves substantially, all trained members show a higher standalone FER. The gain therefore results from learned specialization and complementary failure events rather than uniformly improved component decoders.

Abstract: 3GPP Release 19 supports store-and-forward satel- lite access, where traffic accumulated during feeder-link outages must be forwarded through finite, geometry-limited windows. Static priority levels offer little discrimination among large backlogs and ignore the decay in packet value. We formulate QoS feasibility for status updates, measured by destination freshness, and deadline-constrained event reports over periodic two-hop contacts with finite onboard storage. For general calendars, we derive ordering-sensitive miss, cohort-capacity, delivery-rate, and freshness bounds, including an exact status-only characterization. For single status flow and single event class sharing a contact pair per period, a finite-state program gives exact joint feasibility for arbitrary integer age thresholds. Numerical results quantify tradeoffs among load, capacity, deadline, and freshness tolerance.

Abstract: Faster-than-Nyquist (FTN) signaling can improve spectral efficiency by transmitting symbols closer together than the Nyquist limit, at the cost of additional inter-symbol interference (ISI). In this letter, we study the finite-alphabet symbol-wise achievable information rate (AIR) of FTN signaling for BPSK, QPSK, and 16-QAM under a transmit-power constraint and a common minimum mean square error (MMSE) channel-shortening (CS) detection framework, cross-validated for BPSK against an independent reduced-state Ungerboeck Bahl-Cocke-Jelinek-Raviv (BCJR) benchmark. Our results show a clear trend. Lower-order constellations can benefit from more aggressive time acceleration, while higher-order constellations become less tolerant of acceleration and achieve their best spectral efficiency closer to the Nyquist limit. At a reference signal-to-noise ratio (SNR) of 6 dB the optimum acceleration factor shifts from $τ^\star\approx0.65$ for BPSK to 0.75 for QPSK and 0.90 for 16-QAM. We further show that this trend is preserved in coded systems and remains robust to the detector memory. The impact of FTN operation on the instantaneous-to-average power ratio (IAPR) is also examined. Overall, the results highlight how constellation order should be considered when selecting the operating point for FTN signaling.

Abstract: Low Earth orbit (LEO) satellite networks are increasingly used to provide global connectivity. However, each satellite has limited resources that need to be allocated according to demand, which varies geographically and over time. Beam hopping addresses this challenge by dividing a satellite's service area into geographic cells. Rather than illuminating every cell simultaneously, it dynamically assigns available beams to a selected subset based on demand. This reliance on observed traffic demand as an input to beam-selection decisions creates a new attack surface whose security implications have received little attention. In this paper, we present JANUS, a novel targeted denial-of-service attack against beam-hopping systems in LEO networks. We show that a small botnet of compromised terminals can inject legitimate user traffic into carefully selected non-victim cells to manipulate the beam-hopping scheduler's view of demand. This manipulation alters beam-allocation decisions and redirects service away from the targeted victim area. We evaluate JANUS across different system configurations, schedulers, attack horizons, and attacker-knowledge settings to characterize the attack's effectiveness, required resources, and resulting service disruption over time. Against a rank-based KMAX scheduler, JANUS achieves complete service denial for up to approximately 95% of evaluated victims. Against DRL, JANUS can exclude the victim from approximately 92% of scheduling decisions. Finally, we evaluate mitigation strategies that reduce the attack effectiveness.