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Blind Channel Estimation for Downlink Massive MIMO Systems With Imperfect Channel Reciprocity
Indian Inst Technol, India.
Indian Inst Sci, India.
Univ Peradeniya, Sri Lanka.
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-7599-4367
2020 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 68, p. 3132-3145Article in journal (Refereed) Published
Abstract [en]

We consider the performance of time-division duplex (TDD) massive multiple-input multiple-output (MIMO) with imperfect calibration of the transmit and receive radio frequency chains. By deriving the achievable signal-to-interference-plus-noise ratio & x00A0;(SINR) and the per-user bit error rate & x00A0;(BER) for constant modulus constellations, we establish that, under linear precoding, reciprocity imperfections can result in substantial reduction of the array gain. To mitigate this loss, we propose an algorithm for blind estimation of the effective channel gain at each user. We show that, with sufficiently many downlink data symbols, our blind channel estimation algorithm restores the array gain. In addition, the proposed blind gain estimation algorithm can improve performance compared to standard hardening-based receivers even under perfect reciprocity. Following this, we derive the BERs for non-constant modulus constellations, viz.& x00A0;-PAM and -QAM. We corroborate all our derived results using numerical simulations.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC , 2020. Vol. 68, p. 3132-3145
Keywords [en]
Downlink; Channel estimation; Calibration; MIMO communication; Uplink; Radio frequency; Training; Massive MIMO; channel reciprocity calibration; blind channel estimation; deterministic equivalents
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:liu:diva-167708DOI: 10.1109/TSP.2020.2988570ISI: 000544042900001OAI: oai:DiVA.org:liu-167708DiVA, id: diva2:1454684
Note

Funding Agencies|Swedish Research Council (VR)Swedish Research Council; ELLIIT; Nokia Corporation; Intel CorporationIntel Corporation

Available from: 2020-07-20 Created: 2020-07-20 Last updated: 2020-07-20

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