论文标题
数据辅助主动用户检测具有虚假警报校正的无拨款传输
Data-aided Active User Detection with False Alarm Correction in Grant-Free Transmission
论文作者
论文摘要
在大多数现有的赠款（GF）研究中，分别处理这两个关键任务，即主动用户检测（AUD）和有效载荷数据解码。在本文中，提出了两步数据援助的AUD方案，即初始AUD步骤和错误警报校正步骤。为了实现初始的AUD步骤，构建了基于嵌入式的低密度签名（LDS）的前序池。此外，开发了两个传递算法（MPA）初始估计器的消息。在错误的警报校正步骤中，根据初始活动用户集构建了冗余因子图，该集合将MPA用于数据解码。剩下的错误检测到的非活性用户将通过解码数据符号进一步识别错误警报纠正器。仿真结果表明，与基于传统的压缩感（CS）相比，数据解码性能和AUD性能在目标准确性上显着增强了1：5 dB。
In most existing grant-free (GF) studies, the two key tasks, namely active user detection (AUD) and payload data decoding, are handled separately. In this paper, a two-step dataaided AUD scheme is proposed, namely the initial AUD step and the false alarm correction step respectively. To implement the initial AUD step, an embedded low-density-signature (LDS) based preamble pool is constructed. In addition, two message passing algorithm (MPA) based initial estimators are developed. In the false alarm correction step, a redundant factor graph is constructed based on the initial active user set, on which MPA is employed for data decoding. The remaining false detected inactive users will be further recognized by the false alarm corrector with the aid of decoded data symbols. Simulation results reveal that both the data decoding performance and the AUD performance are significantly enhanced by more than 1:5 dB at the target accuracy of 10^3 compared with the traditional compressed sensing (CS) based counterparts
