{"ID":2883319,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2508.09020","arxiv_id":"2508.09020","title":"Improved SINR Approximation for Downlink SDMA-based Networks with Outdated Channel State Information","abstract":"Understanding the performance of multi-user multiple-input multiple-output (MU-MIMO) systems under imperfect channel state information at the transmitter (CSIT) remains a critical challenge in next-generation wireless networks. In this context, accurate statistical modeling of the signal-to-interference-plus-noise ratio (SINR) is essential for enabling tractable performance analysis of multi-user systems. This paper presents an improved statistical approximation of the SINR for downlink (DL) MU-MIMO systems with imperfect CSIT. The proposed model retains the analytical simplicity of existing approaches (e.g., Gamma-based approximations) while overcoming their limitations, particularly the underestimation of SINR variance. We evaluate the proposed approximation in the context of Rate-Splitting Multiple Access (RSMA)-enabled MIMO DL systems with outdated CSIT. The results demonstrate excellent accuracy across a wide range of system configurations, including varying numbers of users, antennas, and degrees of CSIT staleness.","short_abstract":"Understanding the performance of multi-user multiple-input multiple-output (MU-MIMO) systems under imperfect channel state information at the transmitter (CSIT) remains a critical challenge in next-generation wireless networks. In this context, accurate statistical modeling of the signal-to-interference-plus-noise rati...","url_abs":"https://arxiv.org/abs/2508.09020","url_pdf":"https://arxiv.org/pdf/2508.09020v2","authors":"[\"Maria Cecilia Fernández Montefiore\",\"Gustavo González\",\"F. Javier López-Martínez\",\"Fernando Gregorio\"]","published":"2025-08-12T15:35:11Z","proceeding":"eess.SP","tasks":"[\"eess.SP\",\"cs.IT\"]","methods":"[]","has_code":false}