Pilot Contamination Mitigation with Reduced RF Chains

TL;DR

This paper proposes a joint pilot sequence design and analog combiner approach to mitigate pilot contamination and reduce hardware complexity in massive MIMO systems, demonstrating improved channel estimation accuracy through simulations.

Contribution

It introduces a novel framework for joint pilot and analog combiner design that is independent, with closed-form solutions and a greedy method for partially-separable correlation models.

Findings

Achieves lower mean squared error than existing pilot allocation methods

Provides closed-form optimal pilot sequences for fully-separable models

Demonstrates effectiveness of the proposed framework via simulations

Abstract

Massive multiple-input multiple-output (MIMO) communication is a promising technology for increasing spectral efficiency in wireless networks. Two of the main challenges massive MIMO systems face are degraded channel estimation accuracy due to pilot contamination and increase in computational load and hardware complexity due to the massive amount of antennas. In this paper, we focus on the problem of channel estimation in massive MIMO systems, while addressing these two challenges: We jointly design the pilot sequences to mitigate the effect of pilot contamination and propose an analog combiner which maps the high number of sensors to a low number of RF chains, thus reducing the computational and hardware cost. We consider a statistical model in which the channel covariance obeys a Kronecker structure. In particular, we treat two such cases, corresponding to fully- and partially-separable correlations. We prove that with these models, the analog combiner design can be done independently of the pilot sequences. Given the resulting combiner, we derive a closed-form expression for the optimal pilot sequences in the fully-separable case and suggest a greedy sum of ratio traces maximization (GSRTM) method for designing sub-optimal pilots in the partially-separable scenario. We demonstrate via simulations that our pilot design framework achieves lower mean squared error than the common pilot allocation framework previously considered for pilot contamination mitigation.