In this article, a Co-existing Preamble and Data (CoPD) random access approach for machine-type communications (MTC) is proposed and studied in massive multiple input multiple output (MIMO) systems. Unlike conventional grant-free random access in which preambles are time-multiplexed with data, the proposed approach enables CoPD transmissions by different groups of devices, which leverages favourable propagation of massive MIMO and successive interference cancellation (SIC) technique. To fully understand the performance behavior of the proposed approach, the error characteristics of channel estimation (CE) due to SIC error propagation are investigated. To avoid the CE error variance growing arbitrarily with time that leads to data transmission failure, key conditions, with respect to preamble length $L$ , traffic intensity $\lambda $ , and average number of data packets per active device $\bar b$ , are derived. Under the conditions, we demonstrate that the throughput of the proposed CoPD approach cannot be arbitrarily high by increasing $\bar b$ and $\lambda $ even though the antenna array size, denoted by $M$ , grows arbitrarily in massive MIMO. Accordingly, its maximum throughput and success probability are theoretically obtained. Simulation results verify our analysis results and confirm that the maximum throughput of the proposed CoPD approach can be at least 4 times than that of the conventional one. Furthermore, its success probability approaches 1 when $M \to \infty $ as long as the derived conditions are met.

中文翻译：

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具有大规模 MIMO 的 MTC 随机接入中的共存前导码和数据传输

在本文中，在大规模多输入多输出 (MIMO) 系统中提出并研究了一种用于机器类型通信 (MTC) 的共存前导码和数据 (CoPD) 随机接入方法。与前同步码与数据时间复用的传统免授权随机接入不同，所提出的方法支持不同设备组的 CoPD 传输，这利用了大规模 MIMO 和连续干扰消除 (SIC) 技术的有利传播。为了充分理解所提出方法的性能行为，研究了由于 SIC 错误传播引起的信道估计 (CE) 的错误特征。为了避免 CE 错误方差随时间任意增长而导致数据传输失败，关键条件是前导码长度 $L$ , 交通强度 $\lambda $ ，以及每个活动设备的平均数据包数 $\bar b$ , 导出。在这些条件下，我们证明了所提出的 CoPD 方法的吞吐量不能通过增加 $\bar b$ 和 $\lambda $ 即使天线阵列大小，表示为 百万美元 ，在大规模 MIMO 中任意增长。因此，理论上获得了其最大吞吐量和成功概率。仿真结果验证了我们的分析结果，并确认所提出的 CoPD 方法的最大吞吐量至少是传统方法的 4 倍。此外，当它的成功概率接近 1 时 $M \to \infty $ 只要满足派生条件。