Statistical Characterization of Wireless MIMO Channels in Mode-Stirred Enclosures

TL;DR

This paper statistically characterizes 2x2 MIMO wireless channels in mode-stirred enclosures, revealing multipath effects, channel capacity behavior, and the impact of environment conditions on wireless communication in confined, reflective spaces.

Contribution

It provides the first detailed statistical analysis of MIMO channels in mode-stirred enclosures under various loading conditions, highlighting multipath and capacity characteristics.

Findings

Two parallel channels are observed in confined environments.

Channel capacity exhibits a multi-modal distribution.

Absorbers influence the capacity's mean and variance.

Abstract

We present the statistical characterization of a 2x2 Multiple-Input Multiple-Output wireless link operated in a mode-stirred enclosure, with channel state information available only at the receiver (agnostic transmitter). Our wireless channel measurements are conducted in absence of line of sight and varying the inter-element spacing between the two antenna elements in both the transmit and receive array. The mode-stirred cavity is operated: i) at a low number of stirrer positions to create statistical inhomogeneity; ii) at two different loading conditions, empty and with absorbers, in order to mimic a wide range of realistic equipment level enclosures. Our results show that two parallel channels are obtained within the confined space at both the operating conditions. The statistical characterization of the wireless channel is presented in terms of coherence bandwidth, path loss, delay spread and Rician factor, and wideband channel capacity. It is found that the severe multipath fading supported by a highly reflecting environment creates unbalance between the two Multiple-Input Multiple-Output channels, even in presence of substantial losses. Furthermore, the channel capacity has a multi-modal distribution whose average and variance scale monotonically with the number of absorbers. Results are of interest in IoT devices, including wireless chip-to-chip and device-to-device communications, operating in highly reflective environments.