In this paper, we show that the adaptive projected subgradient method (APSM) is bounded perturbation resilient. To illustrate a potential application of this result, we propose a set-theoretic framework for MIMO detection, and we devise algorithms based on a superiorized APSM. Various low-complexity MIMO detection algorithms achieve excellent performance on i.i.d. Gaussian channels, but they typically incur high performance loss if realistic channel models (e.g., correlated channels) are considered. Compared to existing low-complexity iterative detectors such as individually optimal large-MIMO approximate message passing (IO-LAMA), the proposed algorithms can achieve considerably lower symbol error ratios over correlated channels. At the same time, the proposed methods do not require matrix inverses, and their complexity is similar to IO-LAMA.

翻译：在本文中,我们显示,适应性预测次梯度方法(APSM)具有受约束性扰动性。为了说明这一结果的潜在应用,我们为MOMO探测提出了一个固定理论框架,我们根据优异的APSM设计了算法。各种低复杂性MIMO检测算法在i.d.高斯海峡上取得了优异的性能,但如果考虑现实的频道模型(例如相关频道),它们通常会发生高性能损失。与现有的低复杂性迭代探测器相比,例如个人最优的大MIMO近似电文传递(IO-LAMA),提议的算法可以在相关频道上实现大大降低符号错误率。与此同时,拟议的方法不需要矩阵反向,其复杂性与IMO-LAMA相似。