A Novel OTFS-Based Massive Random Access Scheme in Cell-Free Massive MIMO Systems for High-Speed Mobility

In the research of next-generation wireless communication technologies, orthogonal time frequency space (OTFS) modulation is emerging as a promising technique for highspeed mobile environments due to its superior efficiency and robustness in doubly-selective channels. Additionally, the cellfree architecture, which eliminates the issues associated with cell boundaries, offers broader coverage for radio access networks. Integrating cell-free architecture with OTFS modulation enables support for massive random access in high-mobility machinetype communication scenarios. This paper explores a massive random access scheme based on OTFS modulation within a cellfree architecture. A transceiver model for uplink OTFS signals involving multiple access points (APs) is developed, where channel estimation with fractional channel parameters is approximated as a two-dimensional block sparse matrix recovery problem. Building on existing superimposed and embedded preamble schemes, a hybrid preamble strategy intended for massive random access is proposed. This scheme leverages superimposed and embedded preambles to respectively achieve rough and accurate active user equipment (UE) detection (AUD), as well as precise channel estimation. Moreover, this study introduces a generalized approximate message passing and pattern-coupled sparse Bayesian learning with Laplacian prior (GAMP-PCSBL-La) algorithm, which effectively captures block sparse features after discrete cosine transform (DCT), delivering precise estimation results with reduced computational complexity. Simulation results demonstrate that the proposed scheme is effective and provides superior performance compared to other existing schemes.