2016/09/02 by Yanlun Wu, Jun Fang, Wu, Yanlun +1
Computer Science · Engineering · Mathematics · #Advanced MIMO Systems Optimization #FOS: Computer and information sciences #Indoor and Outdoor Localization Technologies #Information Theory (cs.IT) #Sparse and Compressive Sensing Techniques #cs.IT #math.IT
paper · pdf · doi:10.48550/arxiv.1609.00452
openalex publication_date 2016/09/02 · arxiv created 2017/01/10 · arxiv updated 2017/01/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Support massive connectivity is an important requirement in 5G wireless communication system. For massive Machine Type Communication (MTC) scenario, since the network is expected to accommodate a massive number of MTC devices with sparse short message, the multiple access scheme like current LTE uplink would not be suitable. In order to reduce the signaling overhead, we consider an grant-free multiple access system, which requires the receiver facilitate activity detection, channel estimation, and data decoding in "one shot" and without the knowledge of active user's pilots. However, most of the "one shot" communication research haven't considered the massive MIMO scenario. In this work we propose a Multiple Measurement Model (MMV) model based Massive MIMO and exploit the covariance matrix of the measurements to confirm a high activity detection rate.