This paper considers massive access in massive multiple-input multiple-output (MIMO) systems and proposes an adaptive active user detection and channel estimation scheme based on compressive sensing. By exploiting the sporadic traffic of massive connected user equipments and the virtual angular domain sparsity of massive MIMO channels, the proposed scheme can support massive access with dramatically reduced access latency. Specifically, we design non-orthogonal pseudo-random pilots for uplink broadband massive access, and formulate the active user detection and channel estimation as a generalized multiple measurement vector compressive sensing problem. Furthermore, by leveraging the structured sparsity of the uplink channel matrix, we propose an efficient generalized multiple measurement vector approximate message passing (GMMV-AMP) algorithm to realize joint active user detection and channel estimation based on a spatial domain or an angular domain channel model. To jointly exploit the channel sparsity present in both the spatial and the angular domains for enhanced performance, a Turbo-GMMV-AMP algorithm is developed for detecting the active users and estimating their channels in an alternating manner. Finally, an adaptive access scheme is proposed, which adapts the access latency to guarantee reliable massive access for practical systems with unknown channel sparsity level. Additionally, the state evolution of the proposed GMMV-AMP algorithm is derived to predict its performance. Simulation results demonstrate the superiority of the proposed active user detection and channel estimation schemes compared to several baseline schemes.

中文翻译：

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基于压缩感知的自适应主动用户检测和信道估计：大规模接入满足大规模 MIMO

本文考虑了大规模多输入多输出（MIMO）系统中的大规模接入，并提出了一种基于压缩感知的自适应主动用户检测和信道估计方案。通过利用海量连接用户设备的零星流量和海量 MIMO 信道的虚拟角域稀疏性，所提出的方案可以支持海量接入，并显着降低接入延迟。具体而言，我们为上行宽带大规模接入设计了非正交伪随机导频，并将活动用户检测和信道估计表述为广义多测量向量压缩感知问题。此外，通过利用上行信道矩阵的结构化稀疏性，我们提出了一种高效的广义多测量向量近似消息传递（GMMV-AMP）算法，以实现基于空间域或角域信道模型的联合主动用户检测和信道估计。为了联合利用空间域和角域中存在的信道稀疏性以提高性能，开发了 Turbo-GMMV-AMP 算法来检测活跃用户并以交替方式估计他们的信道。最后，提出了一种自适应接入方案，该方案通过调整接入延迟来保证信道稀疏度未知的实际系统的可靠大规模接入。此外，还导出了所提出的 GMMV-AMP 算法的状态演变以预测其性能。