Low-Complexity Vector-by-Vector Detector for AFDM-IM Systems by Reconstructing Sparse Channel Matrix

作者：Xiaoshan Wang, Lixia Xiao, Qu Luo, Jiaxi Zhou, Miaowen Wen, Tao Jiang · 发表于：IEEE Communications Letters · 年份：2025 · DOI：10.1109/lcomm.2025.3577262 · 被引用次数：8 · 研究领域：Blind Source Separation Techniques、Sparse and Compressive Sensing Techniques、Optical Network Technologies

In this letter, a low-complexity vector-by-vector aided expectation propagation (VV-EP) detector is proposed for affine frequency division multiplexing (AFDM) with index modulation (IM) through reconstructing the sparse effective channel matrix. Specifically, the low-correlation elements of the effective channel matrix are set to zero by a preset threshold. Based on the reconstructed sparse matrix, approximate inverse operation can be implemented by Cholesky decomposition to reduce computational complexity. Moreover, the lower triangular matrix is constructed iteratively to improve detection performance. Simulation results indicate that the designed VV-EP algorithm is capable of reducing complexity by about 90% with a negligible performance loss compared to the orthogonal approximate message passing (OAMP) detector.