Massive MIMO is Very Useful for Pilot-Free Uplink Communications

N. Lee
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Abstract

Pilot-free (or non-coherent) communications are of great significance for short-packet communications in beyond 5G applications. The absence of pilots brings a fundamental challenge when decoding a message because of no knowledge of channel state information at a receiver. In this paper, we aim to show that a massive number of antennas at a base station (BS) is very useful for pilot-free uplink communications. Specifically, for a single-input multiple-output channel, we show that the spectral efficiency linearly scales with channel coherence time, provided that the number of antennas is infinite. We prove this result by both a variant of binary sparse superposition codes and a compressive covariance sensing-based decoding method. We also present a novel covariance matching pursuit (CMP) decoding method that is computationally efficient yet achieving a nearoptimal decoding performance. By simulations, we demonstrate the proposed decoding algorithm significantly outperforms the existing approximated message-passing based algorithm.
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大规模MIMO对无导频上行通信非常有用
无导频(或非相干)通信对于超5G应用中的短分组通信具有重要意义。由于不知道接收机的信道状态信息,导频的缺失给解码带来了根本性的挑战。在本文中,我们的目的是证明在一个基站(BS)中大量的天线对于无导频上行通信是非常有用的。具体来说,对于单输入多输出信道,我们证明了在天线数量无限的情况下,频谱效率与信道相干时间呈线性关系。我们用一种二进制稀疏叠加码的变体和一种基于压缩协方差感知的译码方法来证明这一结果。我们还提出了一种新的协方差匹配追踪(CMP)解码方法,该方法计算效率高,但实现了接近最优的解码性能。通过仿真,我们证明了所提出的解码算法明显优于现有的基于近似消息传递的算法。
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