Blind Estimation of Sparse Multi-User Massive MIMO Channels

Conference: WSA 2017 - 21th International ITG Workshop on Smart Antennas
03/15/2017 - 03/17/2017 at Berlin, Deutschland

Proceedings: WSA 2017

Pages: 5Language: englishTyp: PDF

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Authors:
Mezghani, Amine; Swindlehurst, Lee (Center for Pervasive Communications and Computing (CPCC), Department of EECS, University of California, Irvine, CA 92697, USA)

Abstract:
We provide a maximum likelihood formulation for the blind estimation of massive mmWave MIMO channels while taking into account their underlying sparse structure. The main advantage of this approach is the fact that the overhead due to pilot sequences can be reduced dramatically especially when operating at low SNR per antenna. Thereby, the sparsity in the angular domain is exploited as a key property to enable the unambiguous blind separation between user's channels. On the other hand, as only the sparsity is assumed, the proposed method is robust with respect to the statistical properties of the channel and data and allows the estimation in rapidly time-varying scenarios and eventually the separation of interfering users from adjacent base stations. Additionally, a performance limit is derived based on the clairvoyant Cramer Rao lower bound. Simulation results demonstrate that this maximum likelihood formulation yields superior estimation accuracy with reasonable computational complexity and limited model assumptions.