{"ID":2889811,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2507.21363","arxiv_id":"2507.21363","title":"Distributed Iterative ML and Message Passing for Grant-Free Cell-Free Massive MIMO Systems","abstract":"Cell-Free (CF) Massive Multiple-Input Multiple-Output (MaMIMO) is considered one of the leading candidates for enabling next-generation wireless communication. With the growing interest in the Internet of Things (IoT), the Grant-Free (GF) access scheme has emerged as a promising solution to support massive device connectivity. The integration of GF and CF-MaMIMO introduces significant challenges, particularly in designing distributed algorithms for activity detection and pilot contamination mitigation. In this paper, we propose a distributed algorithm that addresses these challenges. Our method first employs a component-wise iterative distributed Maximum Likelihood (ML) approach for activity detection, which considers both the pilot and data portions of the received signal. This is followed by a Pseudo-Prior Hybrid Variational Bayes and Expectation Propagation (PP-VB-EP) algorithm for joint data detection and channel estimation. Compared to conventional VB-EP, the proposed PP-VB-EP demonstrates improved convergence behavior and reduced sensitivity to initialization, especially when data symbols are drawn from a finite alphabet. The pseudo prior used in PP-VB-EP acts as an approximated posterior and serves as a regularization term that prevents the Message Passing (MP) algorithm from diverging. To compute the pseudo prior in a distributed fashion, we further develop a distributed version of the Variable-Level Expectation Propagation (VL-EP) algorithm.","short_abstract":"Cell-Free (CF) Massive Multiple-Input Multiple-Output (MaMIMO) is considered one of the leading candidates for enabling next-generation wireless communication. With the growing interest in the Internet of Things (IoT), the Grant-Free (GF) access scheme has emerged as a promising solution to support massive device conne...","url_abs":"https://arxiv.org/abs/2507.21363","url_pdf":"https://arxiv.org/pdf/2507.21363v2","authors":"[\"Zilu Zhao\",\"Christian Forsch\",\"Laura Cottatellucci\",\"Dirk Slock\"]","published":"2025-07-28T22:14:44Z","proceeding":"cs.IT","tasks":"[\"cs.IT\",\"eess.SP\",\"stat.AP\"]","methods":"[]","has_code":false}