Interleaved Block-Sparse Transform
<|reference_start|>Interleaved Block-Sparse Transform: Low-complexity Bayes-optimal memory approximate message passing (MAMP) is an efficient signal estimation algorithm in compressed sensing and multicarrier modulation. However, achieving replica Bayes optimality with MAMP necessitates a large-scale right-unitarily invariant transformation, which is prohibitive in practical systems due to its high computational complexity and hardware costs. To solve this difficulty, this letter proposes a low-complexity interleaved block-sparse (IBS) transform, which consists of interleaved multiple low-dimensional transform matrices, aimed at reducing the hardware implementation scale while mitigating performance loss. Furthermore, an IBS cross-domain memory approximate message passing (IBS-CD-MAMP) estimator is developed, comprising a memory linear estimator in the IBS transform domain and a non-linear estimator in the source domain. Numerical results show that the IBS-CD-MAMP offers a reduced implementation scale and lower complexity with excellent performance in IBS-based compressed sensing and interleave frequency division multiplexing systems.<|reference_end|>
@article{liu2024interleaved,
    title={Interleaved Block-Sparse Transform},
    author={Lei Liu, Ming Wang, Shufeng Li, Yuhao Chi, Ning Wei and ZhaoYang Zhang},
    journal={arXiv preprint arXiv:2407.13255},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.13255},
    primaryClass={cs.IT eess.SP math.IT}
}