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Densification Converses for Walker Constellations
[Submitted on 27 Apr 2026 (v1), last revised 26 Aug 2026 (this v · 2026-04-28 · via cs.IT updates on arXiv.org

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Abstract:We establish densification converses for Walker LEO constellations under nearest-visible association in the full-frequency-reuse setting. Performance is evaluated under the invariant (stationary) measure induced by the constellation/Earth dynamics on the user--constellation ``phase state.'' A key Walker-specific feature, absent from unbounded planar models, is that association is restricted to a bounded visible cap determined by Earth geometry. Under power-law path-loss, a two-level antenna-gain model, i.i.d.\ nonnegative fading with unit mean and finite second moment, and nonzero noise, we prove that increasing the total satellite count $N=N_oN_s$ forces the aggregate interference to grow at least linearly in $N$, while the useful signal remains uniformly bounded above. Consequently, the downlink SINR coverage probability at any fixed threshold and the ergodic spectral efficiency both vanish as $N\to\infty$. These collapse statements concern link-level performance on one shared time--frequency resource block and do not imply that the aggregate capacity of the overall multi-resource network vanishes. The key technical ingredient is a deterministic visibility-annulus block lemma, uniform over all sufficiently large constellations and all ``phase states,'' showing that a fixed fraction of visible satellites lies in a distance annulus strictly inside the horizon; this yields explicit finite-$N$ collapse bounds. In particular, we derive nonasymptotic $O(1/N)$ upper bounds on both coverage and ergodic spectral efficiency. Finally, in the case of frequency reuse through independent thinning, with activity probability $q$, we show that avoiding densification collapse necessarily requires $qN=O(1)$, equivalently a reuse factor $\Omega(N)$, and we obtain a corresponding explicit $O(1/(qN))$ upper bound.

Submission history

From: Ali Khalesi [view email]
[v1] Mon, 27 Apr 2026 16:22:09 UTC (73 KB)
[v2] Wed, 26 Aug 2026 12:44:20 UTC (153 KB)