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Multi-Tag Backscattering to MIMO Reader: Channel Estimation and Throughput Fairness.

Authors :
Mishra, Deepak
Larsson, Erik G.
Source :
IEEE Transactions on Wireless Communications; Dec2019, Vol. 18 Issue 12, p5584-5599, 16p
Publication Year :
2019

Abstract

Green low power networking with the least requirement of dedicated radio resources is need of the hour which has led to the upsurge of backscatter communication (BSC) technology. However, this inherent potential of BSC is challenged by hardware constraints of the underlying tags. We address this timely concern by investigating the practical efficacy of multiple-input-multiple-output (MIMO) technology in overcoming the fundamental limitations of BSC. Specifically, we first introduce a novel least-squares based channel estimation (CE) protocol for multi-tag BSC settings that takes care of both the unintended ambient reflections and the inability of tags in performing estimation by themselves. Then using it, a nontrivial low-complexity algorithm is proposed to obtain the optimal transceiver designs for the multiantenna reader to maximize the minimum value of the lower-bounded backscattered throughput among the single-antenna semi-passive tags. Additional analytical insights on both individually and jointly-optimal precoding vector and detector matrix at the reader are provided by exploring the asymptotically-optimal transceiver designs. Lastly detailed numerical investigation is carried out to validate the theoretical results and quantify the practically realizable throughput fairness. Specifically, more than seven-fold increase in the common-backscattered-throughput among tags as achieved by the proposed designs over the relevant benchmarks corroborates their practical significance. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15361276
Volume :
18
Issue :
12
Database :
Complementary Index
Journal :
IEEE Transactions on Wireless Communications
Publication Type :
Academic Journal
Accession number :
140335398
Full Text :
https://doi.org/10.1109/TWC.2019.2937763