Gholami R, Cottatellucci L, Slock D (2021)
Publication Type: Conference contribution
Publication year: 2021
Publisher: Institute of Electrical and Electronics Engineers Inc.
Book Volume: 2021-July
Pages Range: 2828-2833
Conference Proceedings Title: IEEE International Symposium on Information Theory - Proceedings
Event location: Virtual, Melbourne, VIC, AUS
ISBN: 9781538682098
DOI: 10.1109/ISIT45174.2021.9517786
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 semiblind 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.
APA:
Gholami, R., Cottatellucci, L., & Slock, D. (2021). Tackling Pilot Contamination in Cell-Free Massive MIMO by Joint Channel Estimation and Linear Multi-User Detection. In IEEE International Symposium on Information Theory - Proceedings (pp. 2828-2833). Virtual, Melbourne, VIC, AUS: Institute of Electrical and Electronics Engineers Inc..
MLA:
Gholami, Roya, Laura Cottatellucci, and Dirk Slock. "Tackling Pilot Contamination in Cell-Free Massive MIMO by Joint Channel Estimation and Linear Multi-User Detection." Proceedings of the 2021 IEEE International Symposium on Information Theory, ISIT 2021, Virtual, Melbourne, VIC, AUS Institute of Electrical and Electronics Engineers Inc., 2021. 2828-2833.
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