{"ID":2859845,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.04745","arxiv_id":"2510.04745","title":"Interference Alignment for Multi-cluster Over-the-Air Computation","abstract":"One of the main challenges facing Internet of Things (IoT) networks is managing interference caused by the large number of devices communicating simultaneously, particularly in multi-cluster networks where multiple devices simultaneously transmit to their respective receiver. Over-the-Air Computation (AirComp) has emerged as a promising solution for efficient real-time data aggregation, yet its performance suffers in dense, interference-limited environments. To address this, we propose a novel Interference Alignment (IA) scheme tailored for up-link AirComp systems. Unlike previous approaches, the proposed method scales to an arbitrary number $\\sf K$ of clusters and enables each cluster to exploit half of the available channels, instead of only $\\tfrac{1}{\\sf K}$ as in time-sharing. In addition, we develop schemes tailored to scenarios where users are shared between adjacent clusters.","short_abstract":"One of the main challenges facing Internet of Things (IoT) networks is managing interference caused by the large number of devices communicating simultaneously, particularly in multi-cluster networks where multiple devices simultaneously transmit to their respective receiver. Over-the-Air Computation (AirComp) has emer...","url_abs":"https://arxiv.org/abs/2510.04745","url_pdf":"https://arxiv.org/pdf/2510.04745v1","authors":"[\"Lucas Sempéré\",\"Yue Bi\",\"Yue Wu\",\"Pengwenlong Gu\",\"Selma Boumerdassi\"]","published":"2025-10-06T12:21:14Z","proceeding":"eess.SP","tasks":"[\"eess.SP\"]","methods":"[]","has_code":false}