Mobility Information Capacity in the Sky: A Gaussian Channel Perspective
Abstract
Existing airspace capacity metrics mainly quantify occupancy or flow, although the same number of aerial vehicles may result in different motion alternatives. This letter establishes \emph{mobility information capacity} as an information-theoretic measure for low-altitude wireless networks. It quantifies the maximum information that trajectory observations reveal about intentional maneuver inputs under a given maneuver-resource budget and environmental uncertainty. For a common fixed feedback architecture, we formulate a lifted linear-Gaussian mobility channel and derive its finite-horizon log-determinant capacity. Cost and uncertainty whitening gives the spatiotemporal mobility eigenmodes, whose optimal maneuver-resource allocation follows water-filling. When the number of nondegenerate modes grows linearly with time and their efficiencies become asymptotically symmetric, we arrive at the Shannon-like law RMG=BM/2log2(1+MNR), where MNR is the mobility-to-noise ratio. The proposed measure opens a motion-centric capacity perspective for the sky, while remaining a distinguishability baseline rather than a collision- or geometry-constrained airspace capacity.
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BibTeX
@misc{yuan2026mobility,
title = {{Mobility Information Capacity in the Sky: A Gaussian Channel Perspective}},
author = {Weijie Yuan and Fan Liu and Shuangyang Li and Lin Zhou and Pingzhi Fan},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.10436},
eprint = {2609.10436},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.10436},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Mobility Information Capacity in the Sky: A Gaussian Channel Perspective
AU - Weijie Yuan
AU - Fan Liu
AU - Shuangyang Li
AU - Lin Zhou
AU - Pingzhi Fan
PY - 2026
DA - 2026/09/09
PB - arXiv
DO - 10.48550/arxiv.2609.10436
UR - https://arxiv.org/abs/2609.10436
AB - Existing airspace capacity metrics mainly quantify occupancy or flow, although the same number of aerial vehicles may result in different motion alternatives. This letter establishes \emph{mobility information capacity} as an information-theoretic measure for low-altitude wireless networks. It quantifies the maximum information that trajectory observations reveal about intentional maneuver inputs under a given maneuver-resource budget and environmental uncertainty. For a common fixed feedback architecture, we formulate a lifted linear-Gaussian mobility channel and derive its finite-horizon log-determinant capacity. Cost and uncertainty whitening gives the spatiotemporal mobility eigenmodes, whose optimal maneuver-resource allocation follows water-filling. When the number of nondegenerate modes grows linearly with time and their efficiencies become asymptotically symmetric, we arrive at the Shannon-like law R_M^G=B_M/2log_2(1+MNR), where MNR is the mobility-to-noise ratio. The proposed measure opens a motion-centric capacity perspective for the sky, while remaining a distinguishability baseline rather than a collision- or geometry-constrained airspace capacity.
ER -