Grant-Free Random Access in Uplink LEO Satellite Communications with OFDM

This paper investigates joint device activity detection
and channel estimation for grant-free random access in Lowearth
orbit (LEO) satellite communications. We consider uplink
communications from multiple single-antenna terrestrial users to
a LEO satellite equipped with a uniform planar array of multiple
antennas, where orthogonal frequency division multiplexing
(OFDM) modulation is adopted. To combat the severe Doppler
shift, a transmission scheme is proposed, where the discrete prolate
spheroidal basis expansion model (DPS-BEM) is introduced to reduce
the number of unknown channel parameters. Then the vector
approximate message passing (VAMP) algorithm is employed to
approximate the minimum mean square error estimation of the
channel, and the Markov random field is combined to capture
the channel sparsity. Meanwhile, the expectation-maximization
(EM) approach is integrated to learn the hyperparameters in
priors. Finally, active devices are detected by calculating energy
of the estimated channel. Simulation results demonstrate that the
proposed method outperforms conventional algorithms in terms
of activity error rate and channel estimation precision