In this paper, we focus on the problem of blind joint calibration of multiband transceivers and time-delay (TD) estimation of multipath channels. We show that this problem can be formulated as a particular case of covariance matching. Although this problem is severely ill-posed, prior information about radio-frequency chain distortions and multipath channel sparsity is used for regularization. This approach leads to a biconvex optimization problem, which is formulated as a rank-constrained linear system and solved by a simple group Lasso algorithm. Numerical experiments show that the proposed algorithm provides better calibration and higher resolution for TD estimation than current state-of-the-art methods.
|Title of host publication||ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)|
|Subtitle of host publication||Proceedings|
|Number of pages||5|
|Publication status||Published - 2020|
|Event||ICASSP 2020: IEEE International Conference on Acoustics, Speech and Signal Processing - Barcelona, Spain|
Duration: 4 May 2020 → 8 May 2020
|Period||4/05/20 → 8/05/20|
Bibliographical noteGreen Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
- blind calibration
- multipath estimation
- sparse covariance matching
- time-of-arrival estimation