Analytic Modeling for Grant-Free Transmission in Cell-Free Massive MIMO: A Stochastic Geometry Approach

Cell-free (CF) massive multiple-input multiple-output (MIMO), as a promising network architecture for beyond the fifth generation (5G), has a great potential to support grant-free (GF) transmission for machine-type communication (MTC). To shed light on this subject, this work aims to model and evaluate the performance of GF transmission in CF massive MIMO under a realistic network deployment scenario, where the spatial locations of both access points (APs) and devices are assumed to be random in nature. In particular, by capitalizing on the distinctive CF network architecture and features, we design a new two-disk based geometric model for GF transmission, which facilitates analysis and understanding in CF massive MIMO. Based on the proposed two-disk model, we derive an approximated closed-form expression for the access success probability by leveraging on techniques from stochastic geometry, and investigate the impact of different key system parameters on the network performance. To highlight the performance superiority of CF massive MIMO, we further provide a comparative analysis by using an analogous single-disk model in an equivalent co-located massive MIMO network. Simulation results verify our analysis and demonstrate that CF massive MIMO is able to significantly outperform its co-located counterpart in terms of access success probability and provide robust performance against increased access density, which well suits to crowd scenarios.