Decentralized Algorithms for Out-of-System Interference Suppression in Distributed MIMO

TL;DR

This paper introduces a decentralized algorithm for mitigating out-of-system interference in distributed MIMO networks, effectively estimating and suppressing interference with low communication overhead.

Contribution

It proposes a novel distributed interference estimation and suppression algorithm that approaches centralized performance with reduced fronthaul load.

Findings

Performance comparable to centralized algorithms

Lower fronthaul load requirements

Effective interference suppression in uplink and downlink

Abstract

Out-of-system (OoS) interference is a potential limitation for distributed networks that operate in unlicensed spectrum or in a spectrum sharing scenario. The OoS interference differs from the in-system interference in that OoS signals and their associated channels (or even their statistics) are completely unknown. In this paper, we propose a novel distributed algorithm that can mitigate OoS interference in the uplink and suppress the signal transmission in the OoS direction in the downlink. To estimate the OoS interference, each access point (AP), upon receiving an estimate of OoS interference from a previous AP, computes a better estimate of OoS interference by rotate-and-average using Procrustes method and forwards the estimates to the next AP. This process continues until the central processing unit (CPU) receives the final estimate. Our method has comparable performance to that of a fully centralized interference rejection combining algorithm and has much lower fronthaul load requirements.