Group Based Interference Alignment

TL;DR

This paper introduces a group-based interference alignment scheme for the K-user SISO interference channel, optimizing multiplexing gain under limited resources through novel algorithms.

Contribution

It proposes a new group-based interference alignment method formulated as a knapsack problem, with algorithms to optimize resource allocation for improved multiplexing gain.

Findings

GIA achieves higher multiplexing gain with limited resources.

Optimal and greedy algorithms effectively find group patterns.

GIA outperforms traditional methods in resource-constrained scenarios.

Abstract

In the $K$-user single-input single-output (SISO) frequency-selective fading interference channel, it is shown that the maximal achievable multiplexing gain is almost surely $K/2$ by using interference alignment (IA). However, when the signaling dimensions are limited, allocating all the resources to all users simultaneously is not optimal. So, a group based interference alignment (GIA) scheme is proposed, and it is formulated as an unbounded knapsack problem. Optimal and greedy search algorithms are proposed to obtain group patterns. Analysis and numerical results show that the GIA scheme can obtain a higher multiplexing gain when the resources are limited.