The recent works on a deep learning (DL)-based joint design of preamble set for the transmitters and data-aided active user detection (AUD) in the receiver has demonstrated a significant performance improvement for grant-free sparse code multiple access (GF-SCMA) system. The autoencoder for the joint design can be trained only in a given environment, but in an actual situation where the operating environment is constantly changing, it is difficult to optimize the preamble set for every possible environment. Therefore, a conventional, yet general approach may implement the data-aided AUD while relying on the preamble set that is designed independently rather than the joint design. In this paper, the activity detection error rate (ADER) performance of the data-aided AUD subject to the two preamble designs, i.e., independently designed preamble and jointly designed preamble, were directly compared. Fortunately, it was found that the performance loss in the data-aided AUD induced by the independent preamble design is limited to only 1dB. Furthermore, such performance characteristics of jointly designed preamble set is interpreted through average cross-correlation among the preambles associated with the same codebook (CB) (average intra-CB cross-correlation) and average cross-correlation among preambles associated with the different CBs (average inter-CB cross-correlation).
翻译:最近为接收器中发报机和数据辅助积极用户探测(AUD)设计的基于深度学习(DL)的联合序言设计工作表明,对无赠款的稀有代码多重访问(GF-SCMA)系统而言,该联合设计自动编码器的性能有显著改进,只有在特定环境中才能对联合设计自动编码师进行培训,但在操作环境不断变化的实际情况下,很难优化为每一种可能的环境设定的数据辅助自动编码的序言。因此,一种常规但一般的办法可能执行数据辅助自动编码的自动编码,同时依靠独立设计的序言而不是联合设计的共同设计。在本文中,对数据辅助自动编码的自动编码自动编码系统的活动识别误差率(ADER)的性能进行了两次直接比较,即独立设计的序言和共同设计的序言。幸运的是,发现独立序言设计引起的数据辅助自动编码自动编码的性能损失仅限于1 dB。此外,联合设计的序言集的这种性能特征通过序言与同一平均(CB)序言和不同平均的相互关系(CB)的跨序言(CB)的跨级/CB(CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CR/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/C/C/C/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CB/CBBB/CB/CB/CB/CB/CB/CB/CB/C/C/CB/C/C/CB/C/C/CB/CB/CB/CB/CB/C/CB/CB/C/CB/C/C/C/C/C/C/C