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Channel state information (CSI) estimation is a critical issue in the designof modern massive multiple-input multiple-output (mMIMO) networks. With theincreasing number of users, assigning orthogonal pilots to everyone incurs alarge overhead that strongly penalizes the system's spectral efficiency (SE).It becomes thus necessary to reuse pilots, giving rise to pilot contamination,a vital performance bottleneck of mMIMO networks. Reusing pilots among theusers of the same cell is a desirable operation condition from the perspectiveof reducing training overheads; however, the intra-cell pilot contaminationmight worsen due to the users' proximity. Reconfigurable intelligent surfaces(RISs), capable of smartly controlling the wireless channel, can be leveragedfor intra-cell pilot reuse. In this paper, our main contribution is a RIS-aidedapproach for intra-cell pilot reuse and the corresponding channel estimationmethod. Relying upon the knowledge of only statistical CSI, we optimize the RISphase shifts based on a manifold optimization framework and the RIS positioningbased on a deterministic approach. The extensive numerical results highlightthe remarkable performance improvements the proposed scheme achieves (for bothuplink and downlink transmissions) compared to other alternatives.

Reconfigurable Intelligent Surfaces-Enabled Intra-Cell Pilot Reuse in Massive MIMO Systems