JournalKroSBL

Implementation for algorithms KroSBL and PC-KroSBL in paper

"Bayesian Algorithms for Kronecker-structured Sparse Vector Recovery With Application to IRS-MIMO Channel Estimation"

This paper has been accepted in IEEE Transactions on Signal Processing, June 2024.

In order to reproduce the results, follow the instructions in README in each directory.

KOMP: code for KOMP is modified from here. Implementation of PC-SBL is from Dr. Jun Fang's personal website.

If you turn to the implementation this repository, please cite our paper, and also consider citing the following papers as well: @article{fang2014pattern, title={Pattern-coupled sparse Bayesian learning for recovery of block-sparse signals}, author={Fang, Jun and Shen, Yanning and Li, Hongbin and Wang, Pu}, journal={IEEE Transactions on Signal Processing}, volume={63}, number={2}, pages={360--372}, year={2014}, publisher={IEEE} }

and

@article{caiafa2013computing, title={Computing sparse representations of multidimensional signals using Kronecker bases}, author={Caiafa, Cesar F and Cichocki, Andrzej}, journal={Neural computation}, volume={25}, number={1}, pages={186--220}, year={2013}, publisher={MIT Press} }