This is the second part of a two-part paper that focuses on link-adaptation (LA) and physical layer (PHY) abstraction for multi-user MIMO (MU-MIMO) systems with non-linear receivers. The first part proposes a new metric, called bit-metric decoding rate (BMDR) for a detector, as being the equivalent of post-equalization signal-to-interference-noise ratio (SINR) for non-linear receivers. Since this BMDR does not have a closed form expression, a machine-learning based approach to estimate it effectively is presented. In this part, the concepts developed in the first part are utilized to develop novel algorithms for LA, dynamic detector selection from a list of available detectors, and PHY abstraction in MU-MIMO systems with arbitrary receivers. Extensive simulation results that substantiate the efficacy of the proposed algorithms are presented.

翻译：这是一份分为两部分的文件的第二部分,其重点是与非线性接收器的多用户MIMO(MU-MIMO)系统连接的适应和物理层(PHY)抽取,第一部分为检测器提出了一个称为位数解码率(BMDR)的新度量,相当于非线性接收器的衡平后信号-干涉-噪声比(SINR),由于BMDR没有封闭式表达方式,因此介绍了一种基于机器学习的方法来有效估计它,在这一部分中,开发的概念被用来为LA开发新的算法,从现有探测器清单中选择动态探测器,在MU-MIMO系统中使用任意接收器进行PHY抽取。介绍了证实拟议算法有效性的广泛模拟结果。