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arXiv · 2407.13255

Interleaved Block-Sparse Transform

Lei Liu·Ming Wang·Shufeng Li·Yuhao Chi·Ning Wei·ZhaoYang Zhang
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Abstract

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.

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Lei Liu, Ming Wang, Shufeng Li, Yuhao Chi, Ning Wei, ZhaoYang Zhang. 2024-07-18. Interleaved Block-Sparse Transform. https://arxiv.org/abs/2407.13255

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