University of Oulu

P. Jayasinghe, A. Tölli, J. Kaleva and M. Latva-aho, "Bi-Directional Beamformer Training for Dynamic TDD Networks," in IEEE Transactions on Signal Processing, vol. 66, no. 23, pp. 6252-6267, 1 Dec.1, 2018. doi: 10.1109/TSP.2018.2875888

Bi-directional beamformer training for dynamic TDD networks

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Author: Jayasinghe, Praneeth1; Tölli, Antti1; Kaleva, Jarkko1;
Organizations: 1Centre for Wireless Communications, University of Oulu P.O. Box 4500, FIN-90014 University of Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 2.8 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2018
Publish Date: 2020-01-08


In dynamic time-division-duplexing networks, the available resources per cell can be freely allocated to either uplink (UL) or downlink (DL) depending on the instantaneous traffic demand. Hence, complicated UL-DL and DL-UL interference scenarios arise due to simultaneous UL and DL data transmission in adjacent cells. In this paper, decentralized iterative beamformer designs are obtained for several traffic aware network optimization objectives such that only minimal information exchange is required among the coordinated base stations (BS) and user equipment (UE). Bi-directional forward-backward training via spatially precoded over-the-air pilot signaling is used to facilitate coordinated beamforming. This allows BSs and UEs to iteratively optimize their respective transmitters/receivers based on only locally measured reverse link pilot measurements. Novel bi-directional beamformer training strategies and methods for direct estimation (DE) of the stream specific beamformers are developed for each intermediate beamformer update in a limited and noisy pilot environment. The proposed signaling and DE schemes allow for non-orthogonal and overlapping pilots, which considerably reduces the resource coordination effort. Also, the decontamination ability of the proposed strategies are analyzed with limited pilot resources. The numerical examples illustrate the superior system performance of the proposed training and estimation framework in comparison to both the traditional stream-specific channel estimation method and an uncoordinated system.

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Series: IEEE transactions on signal processing
ISSN: 1053-587X
ISSN-E: 1941-0476
ISSN-L: 1053-587X
Volume: 66
Issue: 23
Pages: 6252 - 6267
DOI: 10.1109/TSP.2018.2875888
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
Funding: This research was supported by Finnish Funding Agency for Technology and Innovation (TEKES), Nokia Networks, Bittium, Keysight, Kyynel and MediaTek.
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