Massive Access in Cell-Free Massive MIMO-Based Internet of Things: Cloud Computing and Edge Computing Paradigms

This article studies massive access in cell-free multi-input multi-output (MIMO)-based Internet of Things and solves the challenging active user detection (AUD) channel estimation (CE) problems. For uplink transmission, we propose an advanced frame structure design to reduce latency. Moreover, by considering cooperation all points (APs), investigate two processing paradigms at receiver for access: cloud computing edge computing. computing, APs are connected a centralized unit (CPU), signals received centrally processed CPU. While central is offloaded part equipped with distributed units, so that AUD CE can be performed strategy. Furthermore, leveraging structured sparsity matrix, develop sparsity-based generalized approximated message passing (SS-GAMP) algorithm reliable joint CE, where quantization accuracy taken into account. Based on SS-GAMP algorithm, successive interference cancellation-based scheme further developed under reduced Simulation results validate superiority proposed approach over state-of-the-art baseline schemes. Besides, reveal achieve similar performance as capable alleviating burden CPU, having faster response, supporting more flexible AP cooperation.