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A Compressive Sensing Based Multi-user Detection Algorithm for SIMa-NOMA Systems

机译:基于压缩感测的辛巴诺马织马系统的多用户检测算法

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Multi-User Detection (MUD) for uplink grant-free Non-orthogonal Multiple Access (NOMA) has received much attention recently. In this paper, we consider the scenario in which a Base Station (BS) is equipped with multiple antennas, and propose a Compressive Sensing-based Hard Fusion Algorithm (CS-HFA) to realize MUD. More explicitly, we detect the user activity information by a conventional CS algorithm at each antenna, and then amalgamate the detected user activity information to derive an active user set. Finally, we can use the obtained active user set to estimate the active users' data. The proposed CS- HFA with low complexity for uplink grant-free Single-Input Multiple-Output Non-Orthogonal Multiple Access (SIMO-NOMA) systems can achieve better BER performance than traditional CS-based MUD in the NOMA system with single antenna at the BS.
机译:用于上行链路的多用户检测(MUD)自由链路的非正交多次访问(NOMA)最近受到了很多关注。在本文中,我们考虑一种基站(BS)配备有多个天线的场景,并提出了一种基于压缩的基于融合的硬融合算法(CS-HFA)来实现泥浆。更明确地,我们通过在每个天线处通过传统的CS算法检测用户活动信息,然后对检测到的用户活动信息进行合并以导出活动用户集。最后,我们可以使用所获得的活动用户设置来估计活动用户的数据。提出的CS-HFA具有低复杂性对上行链路授权单输入多输出非正交多址(SIMO-NOMA)系统可以实现比NOMA系统中的传统CS系列更好的BER性能,其中单天线BS。

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