大规模IoT网络的嵌套混合圆柱阵设计及DoA估计
Nested Hybrid Cylindrical Array Design and DoA Estimation for Massive IoT Networks
摘要：
在保持高网络接入能力的同时降低成本和功耗是大规模物联网（mIoT）网络的关键物理层要求。部署混合阵列是满足要求的成本和能量有效的方式，但是会损害系统自由度（DoF）和信道估计精度。这是因为来自多个天线的信号由混合阵列的射频（RF）网络组合。本文提出了一种新的混合均匀圆柱阵列（UCyA）的mIoT网络。设计了一种基于稀疏阵列技术的嵌套式混合波束形成结构，并提出了相应的基于二阶信道统计量的信道估计方法。因此，仅需要少量RF链来保持UCyA的DoF。我们还提出了一种新的基于张量的二维（2-D）到达方向（DoA）估计算法量身定制的建议的混合阵列。该算法抑制了所有张量模式中的噪声分量，并直接对信号数据模型进行运算，从而以可承受的计算复杂度提高了估计精度。通过Cramer-Rao下限（CRLB）分析验证，仿真结果表明，所提出的混合UCyA阵列和DoA估计算法能够准确估计大量物联网设备的二维DoA。
英文摘要：
Reducing cost and power consumption while maintaining high network access capability is a key physical-layer requirement of massive Internet of Things (mIoT) networks. Deploying a hybrid array is a cost- and energy-efficient way to meet the requirement, but would penalize system degree of freedom (DoF) and channel estimation accuracy. This is because signals from multiple antennas are combined by a radio frequency (RF) network of the hybrid array. This paper presents a novel hybrid uniform circular cylindrical array (UCyA) for mIoT networks. We design a nested hybrid beamforming structure based on sparse array techniques and propose the corresponding channel estimation method based on the second-order channel statistics. As a result, only a small number of RF chains are required to preserve the DoF of the UCyA. We also propose a new tensor-based two-dimensional (2-D) direction-of-arrival (DoA) estimation algorithm tailored for the proposed hybrid array. The algorithm suppresses the noise components in all tensor modes and operates on the signal data model directly, hence improving estimation accuracy with an affordable computational complexity. Corroborated by a Cramer-Rao lower bound (CRLB) analysis, simulation results show that the proposed hybrid UCyA array and the DoA estimation algorithm can accurately estimate the 2-D DoAs of a large number of IoT devices.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
