Massive MIMO-OTFS-Based Random Access for Cooperative LEO Satellite Constellations

TL;DR

This paper proposes a novel joint device identification, channel estimation, and symbol detection framework for cooperative LEO satellite networks using OTFS modulation, leveraging sparsity and basis expansion models to improve performance and reduce overhead.

Contribution

It introduces a generalized complex exponential basis expansion model for TSLs and develops centralized and distributed algorithms for enhanced random access in satellite constellations.

Findings

Significant performance improvement over conventional algorithms.

Distributed mode achieves near-centralized performance with minimal exchanges.

Efficient implementation via FFT accelerates processing.

Abstract

This paper investigates joint device identification, channel estimation, and symbol detection for cooperative multi-satellite-enhanced random access, where orthogonal time-frequency space modulation with the large antenna array is utilized to combat the dynamics of the terrestrial-satellite links (TSLs). We introduce the generalized complex exponential basis expansion model to parameterize TSLs, thereby reducing the pilot overhead. By exploiting the block sparsity of the TSLs in the angular domain, a message passing algorithm is designed for initial channel estimation. Subsequently, we examine two cooperative modes to leverage the spatial diversity within satellite constellations: the centralized mode, where computations are performed at a high-power central server, and the distributed mode, where computations are offloaded to edge satellites with minimal signaling overhead. Specifically, in the centralized mode, device identification is achieved by aggregating backhaul information from edge satellites, and channel estimation and symbol detection are jointly enhanced through a structured approximate expectation propagation (AEP) algorithm. In the distributed mode, edge satellites share channel information and exchange soft information about data symbols, leading to a distributed version of AEP. The introduced basis expansion model for TSLs enables the efficient implementation of both centralized and distributed algorithms via fast Fourier transform. Simulation results demonstrate that proposed schemes significantly outperform conventional algorithms in terms of the activity error rate, the normalized mean squared error, and the symbol error rate. Notably, the distributed mode achieves performance comparable to the centralized mode with only two exchanges of soft information about data symbols within the constellation.