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arXiv · 2605.00423

GD4: Graph-based Discrete Denoising Diffusion for MIMO Detection

Qincheng Lu·Sitao Luan·Xiao-Wen Chang
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Abstract

In wireless communications, recovering the optimal solution to the multiple-input multiple-output (MIMO) detection problem is NP-hard. Obtaining high-quality suboptimal solutions with a favorable performance-complexity trade-off is particularly challenging in under-determined systems with $N_t$ transmit antennas and $N_r < N_t$ receive antennas. Recent diffusion-based MIMO detectors have shown promise, but they require extensive sampling iterations at inference time, and their performance degrades in under-determined scenarios. We propose GD4, a graph-based discrete denoising diffusion method for MIMO detection. Unlike existing diffusion-based detectors that operate in a continuous relaxed space, GD4 performs denoising directly in the discrete symbol space and enables fast inference with one or a few denoising evaluations. Numerical results show that, under a similar inference-time compute budget, GD4 produces higher-quality suboptimal solutions than existing diffusion-based detectors and some widely used classical baseline including box-constrained Babai point and the $K$-best box-constrained randomized Klein-Babai point in both under-determined and overdetermined settings.

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Qincheng Lu, Sitao Luan, Xiao-Wen Chang. 2026-05-01. GD4: Graph-based Discrete Denoising Diffusion for MIMO Detection. https://arxiv.org/abs/2605.00423

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