Approaching the Capacity of Wireless Networks through Distributed Interference Alignment

TL;DR

This paper explores how distributed interference alignment can approach the Shannon capacity in wireless networks, proposing iterative algorithms that use local channel knowledge to achieve alignment.

Contribution

It introduces iterative algorithms leveraging network reciprocity for interference alignment with only local channel knowledge, advancing practical feasibility.

Findings

Algorithms achieve interference alignment with local knowledge

Numerical insights into interference alignment feasibility

Approaching Shannon capacity at high SNR

Abstract

Recent results establish the optimality of interference alignment to approach the Shannon capacity of interference networks at high SNR. However, the extent to which interference can be aligned over a finite number of signalling dimensions remains unknown. Another important concern for interference alignment schemes is the requirement of global channel knowledge. In this work we provide examples of iterative algorithms that utilize the reciprocity of wireless networks to achieve interference alignment with only local channel knowledge at each node. These algorithms also provide numerical insights into the feasibility of interference alignment that are not yet available in theory.