- Article
35 Pages
Spatial dimming in multi-user, multiple-input, multiple-output visible light communication (MIMO-VLC) systems changes the LED activation pattern and effective channel structure, thereby affecting inter-user interference and posing additional challenges to multi-user detection. To address this issue, this paper develops a spatial-dimming- and inter-user-interference-aware DeepSIC detection framework. First, a physically based MIMO-VLC model is established using the Lambertian line-of-sight channel, and a channel-aware LED selection strategy is employed to preserve effective channel separability under the spatial-dimming constraint. Spatial dimming attention (SDA) and inter-user interference attention (IIA) are then introduced to characterize LED-dependent spatial features and target-dependent heterogeneous interference relationships, respectively. An adaptive fusion gate (AFG) is further employed to dynamically integrate the two feature branches. In addition, a BER-oriented optimization strategy is adopted to train the unfolded DeepSIC detector toward the final binary detection objective. Numerical simulations demonstrate that the proposed framework effectively characterizes multi-user interference under spatial dimming and provides favorable detection performance in the low-to-moderate SNR regime. More importantly, measured module-level ablation experiments identify IIA as the primary contributor to the detection improvement. Compared with the original DeepSIC, introducing IIA alone reduces the BER by 9.88% at 15 dB and 34.92% at 25 dB. Attention visualization further shows that IIA learns differentiated interference weights for different target users. Meanwhile, the combined SDA, IIA, and AFG results reveal a nontrivial coupling between spatial-dimming- and interference-aware representations, with adaptive fusion exhibiting SNR-dependent behavior. These results highlight the importance of jointly considering spatial-dimming-induced channel variations and heterogeneous inter-user interference in learning-based multi-user detection for MIMO-VLC systems and provide insights into the development of physically constrained spatial attention and adaptive interference-fusion mechanisms.
Photonics
22 October 2026









