Variance state propagation for uplink channel estimation in LEO satellite systems

Abstract

Abstract This paper, considers the channel estimation problem of the uplink low Earth orbit (LEO) satellite orthogonal frequency division multiplexing (OFDM) system. By exploiting the channel structured sparsity in the delay‐Doppler‐angle domain, the channel estimation problem is formulated as a block‐sparse signal recovery problem. The variance state propagation (VSP) framework is extended to solve such a problem. Considering that the delay, Doppler shift, and angle of departure (AoD) of each propagation path may not exactly fall on the presumed discrete grid points, an expectation maximization (EM) based parameter learning scheme in VSP to iteratively update the grid parameters is introduced. Simulation results demonstrate that the proposed approach achieves a substantial performance gain over the existing methods.

Keywords

• channel estimation
• compressed sensing
• orthogonal frequency division multiplexing modulation
• satellite communication