MIMO Interference Alignment in Random Access Networks

TL;DR

This paper evaluates the performance of MIMO interference alignment in randomly distributed ad hoc networks, considering inter-cluster interference and imperfect channel information, and compares it to spatial multiplexing.

Contribution

It introduces a comprehensive analysis of MIMO interference alignment accounting for inter-cluster interference and imperfect CSI, providing insights into its practical limitations and advantages.

Findings

Inter-cluster interference significantly impacts IA performance.

Spatial multiplexing can outperform IA under certain conditions.

Channel state information quality degrades with node distance.

Abstract

In this paper, we analyze a multiple-input multiple-output (MIMO) interference channel where nodes are randomly distributed on a plane as a spatial Poisson cluster point process. Each cluster uses interference alignment (IA) to suppress intra-cluster interference but unlike most work on IA, we do not neglect inter-cluster interference. We also connect the accuracy of channel state information to the distance between the nodes, i.e. the quality of CSI degrades with increasing distance. Accounting for the training and feedback overhead, we derive the transmission capacity of this MIMO IA ad hoc network and then compare it to open-loop (interference-blind) spatial multiplexing. Finally, we present exemplary system setups where spatial multiplexing outperforms IA due to the imperfect channel state information or the non-aligned inter-cluster interference.