On the Flow-Level Delay of a Spatial Multiplexing MIMO Wireless Channel

TL;DR

This paper analyzes the delay performance of a MIMO wireless channel in spatial multiplexing mode using stochastic network calculus and Markov models, providing probabilistic delay bounds and insights on antenna configurations.

Contribution

It introduces a novel MGF-based stochastic analysis of MIMO channels with Markov models, quantifying spatial multiplexing gains for QoS performance.

Findings

Delay bounds improve with more antennas under certain conditions

Channel burstiness and fading speed significantly impact delay performance

Multi-hop scenarios are analyzed under statistical independence

Abstract

The MIMO wireless channel offers a rich ground for quality of service analysis. In this work, we present a stochastic network calculus analysis of a MIMO system, operating in spatial multiplexing mode, using moment generating functions (MGF). We quantify the spatial multiplexing gain, achieved through multiple antennas, for flow level quality of service (QoS) performance. Specifically we use Gilbert-Elliot model to describe individual spatial paths between the antenna pairs and model the whole channel by an N-State Markov Chain, where N depends upon the degrees of freedom available in the MIMO system. We derive probabilistic delay bounds for the system and show the impact of increasing the number of antennas on the delay bounds under various conditions, such as channel burstiness, signal strength and fading speed. Further we present results for multi-hop scenarios under statistical independence.