In this paper, we propose a turbo receiver for joint activity detection and data decoding in grant-free massive random access, which iterates between a detector and a belief propagation (BP)-based channel decoder. Specifically, responsible for user activity detection, channel estimation and soft data symbol detection, the detector is developed based on a bilinear inference problem that exploits the common sparsity pattern in the received pilot and data signals. The bilinear generalized approximate message passing (BiG-AMP) algorithm is adopted to solve the problem using probabilities of the transmitted data symbols estimated by the channel decoder as prior knowledge. In addition, extrinsic information is also derived from the detector to improve the channel decoding accuracy in the decoder. Simulation results show significant improvements achieved by the proposed turbo receiver compared with conventional designs.

翻译：在本文中,我们提议建立一个涡轮接收器,用于在无赠款的大规模随机访问中进行联合活动探测和数据解码,该接收器在探测器和基于信仰的传播(BP)频道解码器之间进行循环,具体地说,负责用户活动探测、频道估计和软数据符号探测,检测器是根据双线推论问题开发的,它利用了所接收的试点和数据信号中常见的弥漫模式。采用了双线通用信息传递(BIG-AMP)算法,利用频道解码器作为先前知识估计的传输数据符号的概率来解决问题。此外,还从探测器中获取了外部信息,以提高解码器的解码准确性。模拟结果表明,拟议的涡轮接收器与常规设计相比取得了显著改进。