基于集群的大规模 MIMO 系统大规模接入

Shiyu Liang, Wei Chen, Zhongwen Sun, Ao Chen, Bo Ai
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引用次数: 1

摘要

海量机器类型通信旨在支持海量设备的连接,这仍然是 6G 的重要应用场景。本文针对海量多输入多输出系统提出了一种新颖的基于集群的海量接入方法。通过利用角域特征,利用学习到的特定集群字典将设备分成多个集群,从而提高了对活动设备的识别能力。对于检测到的数据恢复失败的有源设备,采用功率域非正交多址和连续干扰消除技术,通过重新传输恢复其数据。仿真结果表明,所提出的方案和算法提高了主动用户检测和数据恢复的性能。
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Cluster-based massive access for massive MIMO systems
Massive machine type communication aims to support the connection of massive devices, which is still an important scenario in 6G. In this paper, a novel cluster-based massive access method is proposed for massive multiple input multiple output systems. By exploiting the angular domain characteristics, devices are separated into multiple clusters with a learned cluster-specific dictionary, which enhances the identification of active devices. For detected active devices whose data recovery fails, power domain nonorthogonal multiple access with successive interference cancellation is employed to recover their data via re-transmission. Simulation results show that the proposed scheme and algorithm achieve improved performance on active user detection and data recovery.
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