Truncated Polynomial Expansion-Based Detection in Massive MIMO: A Model-Driven Deep Learning Approach

arXiv:2402.12595v1 Announce Type: cross
Abstract: In this paper, we propose a deep learning (DL)-based approach for efficiently computing the inverse of Hermitian matrices using truncated polynomial expansion (TPE). Our model-driven approach involves optimizing the coefficients of the TPE during an offline training procedure for a given number of TPE terms. We apply this method to signal detection in uplink massive multiple-input multiple-output (MIMO) systems, where the matrix inverse operation required by linear detectors, such as zero-forcing (ZF) and minimum mean …

abstract arxiv computing cs.lg deep learning detection eess.sp expansion massive offline paper polynomial training type