论文标题
从本地化的角度来看XL-MIMO系统的频道模型不匹配分析
Channel Model Mismatch Analysis for XL-MIMO Systems from a Localization Perspective
论文作者
论文摘要
无线电本地化是在高频（例如MMWave和THZ）系统中应用的，以支持通信并提供基于位置的服务而无需额外的基础架构。 {为了解决本地化问题，由于其紧凑的配方而广泛使用了简化，固定的，狭窄的远面通道模型。}但是，随着超大型MIMO系统中的阵列增加，在上mmwave频带上增加了阵列，频道空间非平台（SNS），swm operical Wave Model（Swm）和光束效应（swm squint squint squint n频道空间非平台（SNS），频道的效果增加。在这种情况下，当采用偏离真实模型的不准确的通道模型时，本地化性能将受到影响。在这项工作中，我们使用MCRB（误指定的Cramér-rao下限）使用简化的不匹配模型来降低定位误差，而观察到的数据则由更复杂的真实模型控制。仿真结果表明，在所有模型障碍中，SNS的贡献最小，与阵列大小相比，距离小时，SWM占主导地位，并且当距离大得多时，BSE的效果比阵列尺寸大得多。
Radio localization is applied in high-frequency (e.g., mmWave and THz) systems to support communication and to provide location-based services without extra infrastructure. {For solving localization problems, a simplified, stationary, narrowband far-field channel model is widely used due to its compact formulation.} However, with increased array size in extra-large MIMO systems and increased bandwidth at upper mmWave bands, the effect of channel spatial non-stationarity (SNS), spherical wave model (SWM), and beam squint effect (BSE) cannot be ignored. In this case, localization performance will be affected when an inaccurate channel model deviating from the true model is adopted. In this work, we employ the MCRB (misspecified Cramér-Rao lower bound) to lower bound the localization error using a simplified mismatched model while the observed data is governed by a more complex true model. The simulation results show that among all the model impairments, the SNS has the least contribution, the SWM dominates when the distance is small compared to the array size, and the BSE has a more significant effect when the distance is much larger than the array size.
