Optimal receiver design improves satellite to UAV communication rates
Optimal Receive Design on the Observation Axis for RSMA Satellite-UAV Downlinks
Information Theory
Summary
Sending data from satellites to drones can be tricky because of signal direction and noise. The authors show how adjusting the way the receiving antenna listens can make the signal clearer and faster. They developed methods to choose the best antenna settings even when the drone's exact position isn't perfectly known. Their work leads to better minimum data rates and more accurate tracking of drone movement.
What this means in practice
- •For satellite communication engineers: Design receiver antennas that maximize data rates and reliability in satellite-to-UAV links under direction uncertainty.
- •For unmanned aerial vehicle operators: Improve UAV signal reception quality by applying advanced receive beamforming techniques for more stable satellite connections.
Authors
Xianwei Meng
Abstract
A receiver can change its observation state while the physical signal remains the same. In rate-splitting multiple access (RSMA) downlinks, this distinction separates receive-beam design and phase-reference transport from the motion of the satellite--UAV line of sight. We formulate receive optimization within the physical--observation dual-axis (PODA) structure and obtain three complementary results. For a known line-of-sight response and positive-definite receiver-noise covariance, a noise-weighted matched combiner simultaneously maximizes every decoding SINR and the minimum user rate. Under directional uncertainty, the principal eigenvector of the conditional response covariance globally maximizes mean array gain; for a Gaussian directional model, an equal-amplitude receiver is optimized by steering towards the conditional mean. Mean rate requires a different objective. We prove that the RSMA common-rate water level is jointly concave in the users' receive gains and derive a semidefinite relaxation with a computable global upper bound. A feasible rank-one beam can therefore be compared directly with the optimum of the finite-scenario problem. We also derive a precision-weighted linear predictor that suppresses uncertain physical-velocity estimates after observation-frame transport. Paired dynamic simulations reduce direction-cosine RMSE by 51.29\% relative to unrestricted nine-point extrapolation. In a separate uncertainty experiment, direct rate optimization increases mean minimum spectral efficiency from 0.32425 to 0.41712 bit/s/Hz, an improvement of 28.64\%; the corresponding design objective is within $2.28\times10^{-4}$ bit/s/Hz of a global upper bound. The phase-transport equation fixes a coherent representative of each optimal beam without changing its gain.