Comparative Analysis of Ray Tracing and Rayleigh Fading Models for Distributed MIMO Systems in Industrial Environments

TL;DR

The paper addresses D-MIMO performance in industrial private networks by comparing realistic ray-tracing (RT) channel models with Rayleigh fading in a factory setting at $3.7$ GHz. It develops a centralized, multi-AP MIMO-OFDM framework with UL pilot training and DL precoding (ZF and SVD) to assess UL cooperative detection and DL cooperative beamforming under network densification (up to $15$ AP serving $679$ UEs on a $20$ MHz bandwidth). Results show that densification improves LoS coverage, AP overlap, and MIMO rank, while RT captures spatial correlations that Rayleigh fading can miss, making Rayleigh optimistic in some scenarios. The findings inform private factory network design, highlighting the value of RT-based propagation modeling and the importance of clustering strategies and limited cooperation to realize D-MIMO gains in industrial environments.

Abstract

This paper presents a detailed analysis of coverage in a factory environment using realistic 3D map data to evaluate the benefits of Distributed MIMO (D-MIMO) over colocalized approach. Our study emphasizes the importance of network densification in enhancing D-MIMO performance, ensuring that User Equipment (UE) remains within range of multiple Access Points (APs). To assess MIMO capacity, we compare two propagation channel models: ray tracing and stochastic. While ray tracing provides accurate predictions by considering environmental details and consistent correlations within the MIMO response, stochastic models offer a more generalized and efficient approach. The analysis outlines the strengths and limitations of each model when applied to the simulation of the downlink (DL) and uplink (UL) single-user capacity in various D-MIMO deployment scenarios.

Figures (9)

• Figure 1: Study area with the $15$AP and $679$ possible UE.
• Figure 2: CDF of the number of LoS AP per UE.
• Figure 3: CDF of the best-server RSRP, for constant AP Tx power (left), or constant network Tx power (right).
• Figure 4: CDF of the number of detected AP, for constant AP Tx power (left), or constant network Tx power (right).
• Figure 5: Distribution of the relative RSRP for second and third best-serving AP.