Deep-Learned Approximate Message Passing for Asynchronous Massive Connectivity

@article{Zhu2021DeepLearnedAM,
  title={Deep-Learned Approximate Message Passing for Asynchronous Massive Connectivity},
  author={Weifeng Zhu and Meixia Tao and Xiaojun Yuan and Yunfeng Guan},
  journal={IEEE Transactions on Wireless Communications},
  year={2021},
  volume={20},
  pages={5434-5448}
}
This paper considers the massive connectivity problem in an asynchronous grant-free random access system, where a huge number of devices sporadically transmit data to a base station (BS) with imperfect synchronization. The goal is to design algorithms for joint user activity detection, delay detection, and channel estimation. By exploiting the sparsity on both user activity and delays, we formulate a hierarchical sparse signal recovery problem in both the single-antenna and the multiple-antenna… 
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