This paper proposes a cell-free massive multiple-input multiple-output (CF-mMIMO) architecture with joint list-based detection with soft interference cancelation (soft-IC) and access points (APs) selection. In particular, we derive a new closed-form expression for the minimum mean-square error receive filter while taking the uplink transmit powers and APs selection into account. This is achieved by optimizing the receive combining vector by minimizing the mean square error between the detected symbol estimate and transmitted symbol, after canceling the multi-user interference (MUI). By using low-density parity check (LDPC) codes, an iterative detection and decoding (IDD) scheme based on a message passing is devised. In order to perform joint detection at the central processing unit (CPU), the access points locally estimate the channel and send their received sample data to the CPU via the front haul links. In order to enhance the system's bit error rate performance, the detected symbols are iteratively exchanged between the joint detector and the LDPC decoder in log likelihood ratio form. Furthermore, we draw insights into the derived detector as the number of IDD iterations increase. Finally, the proposed list detector is compared with existing detection techniques.

翻译：本文提出一种联合基于列表的软干扰消除（soft-IC）检测与接入点（APs）选择的去蜂窝大规模多输入多输出（CF-mMIMO）架构。具体而言，我们推导出考虑上行发射功率和AP选择时的最小均方误差接收滤波器的新闭式表达式。这是通过优化接收合并向量，在消除多用户干扰（MUI）后最小化检测符号估计值与传输符号之间的均方误差来实现的。采用低密度奇偶校验（LDPC）码，设计了一种基于消息传递的迭代检测与译码（IDD）方案。为实现中央处理单元（CPU）的联合检测，各接入点本地估计信道并通过前传链路将接收样本数据发送至CPU。为提升系统误比特率性能，检测符号以对数似然比形式在联合检测器与LDPC译码器之间迭代交换。此外，我们深入分析了随IDD迭代次数增加时推导所得检测器的特性。最后，将所提列表检测器与现有检测技术进行了对比。