University of Oulu

J. Kaleva, A. Tölli, M. Juntti, R. A. Berry and M. L. Honig, "Decentralized Joint Precoding With Pilot-Aided Beamformer Estimation," in IEEE Transactions on Signal Processing, vol. 66, no. 9, pp. 2330-2341, 1 May1, 2018. doi: 10.1109/TSP.2018.2812750

Decentralized joint precoding with pilot-aided beamformer estimation

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Author: Kaleva, Jarkko1; Tölli, Antti1; Juntti, Markku1;
Organizations: 1Centre for Wireless Communications, University of Oulu, Oulu 90014, Finland
2Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL 60208 USA
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 1.7 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2019040511235
Language: English
Published: Institute of Electrical and Electronics Engineers, 2018
Publish Date: 2019-04-05
Description:

Abstract

Downlink beamforming techniques with low beamformer training overhead are proposed for joint processing (JP) coordinated multipoint transmission (CoMP). The objective is to maximize the weighted sum rate within joint transmission clusters without centralized beamformer processing, while accounting for uncertainty in the underlying channels. The proposed methods use time-division duplexing and pilot-based training with, possibly, nonorthogonal pilot sequences. The beamformer training is done without the explicit channel state information estimation, which greatly improves the robustness to pilot contamination. Best response and gradient-based decentralized algorithms are proposed and provide a tradeoff between computational complexity and fast convergence rate. The impact of feedback/backhaul quantization is also considered. The results show that JP CoMP is feasible with slow fading conditions and limited backhaul capacity by employing decentralized beamformer processing.

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Series: IEEE transactions on signal processing
ISSN: 1053-587X
ISSN-E: 1941-0476
ISSN-L: 1053-587X
Volume: 66
Issue: 9
Pages: 2330 - 2341
DOI: 10.1109/TSP.2018.2812750
OADOI: https://oadoi.org/10.1109/TSP.2018.2812750
Type of Publication: A1 Journal article – refereed
Field of Science: 113 Computer and information sciences
Subjects:
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