Channel Estimation for Residual Self-Interference in Full-Duplex Amplify-and-Forward Two-Way Relays

Xiaofeng Li, Cihan Tepedelenlioglu, Habib Senol

Research output: Contribution to journalArticle

19 Citations (Scopus)

Abstract

Training schemes for full duplex two-way relays are investigated. We propose a novel one-block training scheme with a maximum likelihood estimator to estimate the channels between the nodes as well as the residual self-interference (RSI) channel simultaneously. A quasi-Newton algorithm is used to solve the estimator. As a baseline, a multi-block training scheme is also considered. The Cramer-Rao bounds of the one-block and multi-block training schemes are derived. By using the Szegö's theorem about Toeplitz matrices, we analyze how the channel parameters and transmit powers affect the Fisher information. We show analytically that exploiting the structure arising from the RSI channel increases its Fisher information. Numerical results show the benefits of estimating the RSI channel.

Original languageEnglish (US)
Article number7931671
Pages (from-to)4970-4983
Number of pages14
JournalIEEE Transactions on Wireless Communications
Volume16
Issue number8
DOIs
StatePublished - Aug 1 2017

Fingerprint

Cramer-Rao bounds
Amplify-and-forward
Channel Estimation
Channel estimation
Maximum likelihood
Relay
Interference Channel
Interference
Multiblock
Fisher Information
Quasi-Newton Algorithm
Cramér-Rao Bound
Toeplitz matrix
Maximum Likelihood Estimator
Baseline
Estimator
Numerical Results
Training
Vertex of a graph
Theorem

Keywords

  • asymptotic Toeplitz matrix
  • Channel estimation
  • full-duplex relay
  • residual self-interference
  • two-way relay

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics

Cite this

Channel Estimation for Residual Self-Interference in Full-Duplex Amplify-and-Forward Two-Way Relays. / Li, Xiaofeng; Tepedelenlioglu, Cihan; Senol, Habib.

In: IEEE Transactions on Wireless Communications, Vol. 16, No. 8, 7931671, 01.08.2017, p. 4970-4983.

Research output: Contribution to journalArticle

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