| Paper ID | D6-S6-T2.2 |
| Paper Title |
Tackling Pilot Contamination in Cell-Free Massive MIMO by Joint Channel Estimation and Linear Multi-User Detection |
| Authors |
Roya Gholami, EURECOM, France; Laura Cottatellucci, Friedrich-Alexander University, Germany; Dirk Slock, EURECOM, France |
| Session |
D6-S6-T2: Massive MIMO Channel Estimation |
| Chaired Session: |
Monday, 19 July, 23:40 - 00:00 |
| Engagement Session: |
Tuesday, 20 July, 00:00 - 00:20 |
| Abstract |
In this paper we consider cell-free (CF) massive MIMO (MaMIMO) systems, which comprise a very large number of geographically distributed access points (APs) serving a much smaller number of users. We exploit channel sparsity to tackle pilot contamination, which originates from the reuse of pilot sequences. Specifically, we consider semi-blind methods for joint channel estimation and data detection. Under the challenging assumption of deterministic parameters, we determine sufficient conditions and necessary conditions for semi-blind identifiability, which guarantee the non-singularity of the Fisher Information Matrix (FIM) and the existence of the Cramer-Rao bound (CRB). We propose a message passing (MP) algorithm which determines the exact channel coefficients in the case of semi-blind identifiability. We show that the system is identifiable if the Karp-Sipser algorithm yields an empty core. Additionally, we propose a Bayesian semi-blind approach which results in an effective algorithm for joint channel estimation and multi-user detection. This algorithm alternates between channel estimation and linear multi-user detection. Numerical simulations verify the analytical derivations.
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