Role of Interference Alignment in Wireless Cellular Network Optimization

TL;DR

This paper investigates how interference alignment can enhance network optimization in multi-cell MIMO systems by combining IA with traditional algorithms, showing benefits depend on interference conditions and utility functions.

Contribution

It introduces a two-stage optimization framework integrating interference alignment with conventional methods and provides new feasibility results for partial IA.

Findings

IA improves minimum rate optimization without out-of-cluster interference

Marginal gains in sum-rate optimization with IA

Out-of-cluster interference reduces IA benefits

Abstract

The emergence of interference alignment (IA) as a degrees-of-freedom optimal strategy motivates the need to investigate whether IA can be leveraged to aid conventional network optimization algorithms that are only capable of finding locally optimal solutions. To test the usefulness of IA in this context, this paper proposes a two-stage optimization framework for the downlink of a $G$-cell multi-antenna network with $K$ users/cell. The first stage of the proposed framework focuses on nulling interference from a set of dominant interferers using IA, while the second stage optimizes transmit and receive beamformers to maximize a network-wide utility using the IA solution as the initial condition. Further, this paper establishes a set of new feasibility results for partial IA that can be used to guide the number of dominant interferers to be nulled in the first stage. Through simulations on specific topologies of a cluster of base-stations, it is observed that the impact of IA depends on the choice of the utility function and the presence of out-of-cluster interference. In the absence of out-of-cluster interference, the proposed framework outperforms straightforward optimization when maximizing the minimum rate, while providing marginal gains when maximizing sum-rate. However, the benefit of IA is greatly diminished in the presence of significant out-of-cluster interference.