Grant-access based legacy networks are unable to deliver Uplink (UL) dominated sporadic transmission of short packets with low signalling overhead, which are the requirements of Massive Machine Type Communication (mMTC). Hence, grant-free Non-Orthogonal Multiple Access (NOMA) techniques are more suited for mMTC. Due to the inherent sparsity in the user activity pattern in an mMTC system, the existing literature revolves around Compressive Sensing based Multi User Detection (CS-MUD) algorithms, which employ random or Zadoff-Chu spreading sequences for NOMA. In this paper we explore the utility of sinusoidal spreading sequences, which allow some non-iterative algorithms to be employed in the context of active user detection, channel estimation and data detection in a UL grant-free mMTC system. These algorithms do not need prior knowledge about the user behaviour statistics, noise statistics, and the level of sparsity in the user activity, which might be difficult to obtain at the Base Station (BS). We present a comprehensive performance and complexity analysis to assess the feasibility of our proposal. Extensive numerical trials demonstrate the utility of sinusoidal codes for mMTC.

中文翻译：

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具有正弦扩展序列的上行链路免授权 NOMA

基于授权访问的传统网络无法以低信令开销提供上行链路 (UL) 主导的短数据包的零星传输，这是大规模机器类型通信 (mMTC) 的要求。因此，免授权非正交多址 (NOMA) 技术更适合 mMTC。由于 mMTC 系统中用户活动模式的固有稀疏性，现有文献围绕基于压缩感知的多用户检测 (CS-MUD) 算法，该算法为 NOMA 使用随机或 Zadoff-Chu 扩展序列。在本文中，我们探讨了正弦扩展序列的效用，它允许在 UL 无授权 mMTC 系统中的活动用户检测、信道估计和数据检测的上下文中采用一些非迭代算法。这些算法不需要关于用户行为统计、噪声统计和用户活动稀疏程度的先验知识，这些在基站 (BS) 上可能很难获得。我们提出了全面的性能和复杂性分析，以评估我们提案的可行性。大量的数值试验证明了 mMTC 正弦代码的实用性。