University of Oulu

Y. Takano, H. Su, M. Juntti and T. Matsumoto, "A Conditional ℓ1 Regularized MMSE Channel Estimation Technique for IBI Channels," in IEEE Transactions on Wireless Communications, vol. 17, no. 10, pp. 6720-6734, Oct. 2018. doi: 10.1109/TWC.2018.2863295

A conditional ℓ1 regularized MMSE channel estimation technique for IBI channels

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Author: Takano, Yasuhiro1; Su, Hsuan-Jung2; Juntti, Markku3;
Organizations: 1Department of Electrical and Electronic Engineering, Kobe University
2Department of Electrical Engineering, National Taiwan University
3Centre for Wireless Communications, University of Oulu
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 1.9 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2018110147054
Language: English
Published: Institute of Electrical and Electronics Engineers, 2018
Publish Date: 2018-11-01
Description:

Abstract

Inter-block-interference (IBI) caused in the pursuit of spectral efficiency can deteriorate channel estimation performance. For this problem, previously-proposed chained turbo estimation performs IBI cancelation by using the soft replica of the transmitted signal. The IBI cancelation technique can, however, suffer from a mean squared error (MSE) floor problem, since the soft replica is unavailable at the first turbo iteration. The IBI problem can be avoided by using channel impulse response length constraint. Nevertheless, as shown in this paper, the IBI avoidance approach is difficult to perform independently since it requires unbiased second-order statistics. This paper proposes, therefore, a new conditional ℓ1 regularized minimum mean square error channel estimation algorithm by jointly utilizing the IBI avoidance/cancelation and subspace techniques. Simulation results verify that the proposed algorithm solves the MSE floor problem, and, hence, improves the bit error rate convergence performance in realistic IBI channels including the effect of pulse shaping filters.

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Series: IEEE transactions on wireless communications
ISSN: 1536-1276
ISSN-E: 1558-2248
ISSN-L: 1536-1276
Volume: 17
Issue: 10
Pages: 6720 - 6734
DOI: 10.1109/TWC.2018.2863295
OADOI: https://oadoi.org/10.1109/TWC.2018.2863295
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
Subjects:
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