Robust Pilot Decontamination Based on Joint Angle and Power Domain Discrimination

TL;DR

This paper introduces robust channel estimation algorithms for massive MIMO systems that effectively discriminate interference using joint angle and power domain analysis, improving performance in challenging scenarios.

Contribution

It proposes novel algorithms combining spatial filtering and amplitude projection to mitigate pilot contamination, applicable even when interference overlaps with desired signals.

Findings

Algorithms outperform existing methods in contaminated environments.

Analytical conditions for complete decontamination are established.

Simulations show significant system performance gains.

Abstract

We address the problem of noise and interference corrupted channel estimation in massive MIMO systems. Interference, which originates from pilot reuse (or contamination), can in principle be discriminated on the basis of the distributions of path angles and amplitudes. In this paper we propose novel robust channel estimation algorithms exploiting path diversity in both angle and power domains, relying on a suitable combination of the spatial filtering and amplitude based projection. The proposed approaches are able to cope with a wide range of system and topology scenarios, including those where, unlike in previous works, interference channel may overlap with desired channels in terms of multipath angles of arrival or exceed them in terms of received power. In particular we establish analytically the conditions under which the proposed channel estimator is fully decontaminated. Simulation results confirm the overall system gains when using the new methods.