Pilot beamforming for massive machine type communication systems

Hyoungju Ji, Jun Won Choi, Byonghyo Shim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we propose a novel pilot beamforming and CSI acquisition strategy for machine-Type-communication systems to achieve reduction in pilot overhead and improve the channel estimation performance. Key idea of the proposed beam-forming technique is to sparsify the time-domain channel vector using the beamforming. To be specific, using the deliberately designed beamforming weight, we minimize nonzero taps and thus sparsify the (beamformed) channel vector. Due to this, only a few samples are required to perform the channel estimation of beamformed pilots so that whole CSI can be acquired with partial pilot symbols in time and frequency. From the numerical evaluations, we show that the proposed scheme outperforms conventional channel estimation schemes, and achieves NT-fold reduction in the pilot overhead. Also, the proposed scheme can be applied for beamforming weight of energy harvesting.

Original languageEnglish
Title of host publication2017 IEEE/CIC International Conference on Communications in China, ICCC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-5
Number of pages5
ISBN (Electronic)9781538645024
DOIs
Publication statusPublished - 2017 Jul 2
Event2017 IEEE/CIC International Conference on Communications in China, ICCC 2017 - Qingdao, China
Duration: 2017 Oct 222017 Oct 24

Publication series

Name2017 IEEE/CIC International Conference on Communications in China, ICCC 2017
Volume2018-January

Other

Other2017 IEEE/CIC International Conference on Communications in China, ICCC 2017
Country/TerritoryChina
CityQingdao
Period17/10/2217/10/24

Bibliographical note

Funding Information:
This work was sponsored by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIP) (2016R1A2B3015576) and (2014R1A5A1011478).

Publisher Copyright:
© 2017 IEEE.

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Signal Processing

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