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Compressive sensing based time-frequency joint non-orthogonal multiple access

机译:基于压缩感知的时频联合非正交多址

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Non-Orthogonal Multiple Access (NOMA) has been considered to be one of the promising key technologies for future wireless communications and broadcasting return channels due to its high spectral efficiency under massive connectivity. The major challenge of NOMA is to realize interference cancellation and detect the optimal transmitted signals among multiple users. The message passing algorithm (MPA) based multi-user detection (MUD) has been developed to approximate optimal signals from multiple users. However, the conventional MPA always suppose that the user-activity is exactly known at the receiver, which is impractical in real systems. Thus, precise user-activity detection is significant in realizing MPA based NOMA system. In this paper, we propose a compressive sensing based time-frequency joint NOMA scheme in the uplink grant-free low density signature orthogonal frequency division multiplexing (LDS-OFDM) systems, where the priori information obtained from the time-domain m-sequence and the frequency-domain training sequence are utilized for user-activity detection under the framework of CS, while the MPA is performed for the successive user-data detection. The proposed method has a superior performance and less complexity compared to the conventional MPA detector in numerical stimulation.
机译:非正交多路访问(NOMA)由于在大规模连接下具有高频谱效率,因此被认为是未来无线通信和广播回传信道的有前途的关键技术之一。 NOMA的主要挑战是实现干扰消除并检测多个用户之间的最佳传输信号。已经开发了基于消息传递算法(MPA)的多用户检测(MUD)来近似估计来自多个用户的最佳信号。但是,常规的MPA始终假定用户活动在接收方是完全已知的,这在实际系统中是不切实际的。因此,精确的用户活动检测对于实现基于MPA的NOMA系统具有重要意义。在本文中,我们提出了一种基于压缩感知的时频联合NOMA方案,该方案在上行免授权低密度签名正交频分复用(LDS-OFDM)系统中进行,其中先验信息是从时域m序列和频域训练序列用于CS框架下的用户活动检测,而MPA用于连续的用户数据检测。与传统的MPA检测器相比,该方法在数值激励方面具有优越的性能和较低的复杂度。

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