论文标题
部分可观测时空混沌系统的无模型预测
AERIQ: SDR-Based LTE I/Q Measurement and Analysis Framework for Air-to-Ground Propagation Modeling
论文作者
论文摘要
储层计算是预测湍流的有力工具，其简单的架构具有处理大型系统的计算效率。然而，其实现通常需要完整的状态向量测量和系统非线性知识。我们使用非线性投影函数将系统测量扩展到高维空间，然后将其输入到储层中以获得预测。我们展示了这种储层计算网络在时空混沌系统上的应用，该系统模拟了湍流的若干特征。我们表明，使用径向基函数作为非线性投影器，即使只有部分观测并且不知道控制方程，也能稳健地捕捉复杂的系统非线性。最后，我们表明，当测量稀疏、不完整且带有噪声，甚至控制方程变得不准确时，我们的网络仍然可以产生相当准确的预测，从而为实际湍流系统的无模型预测铺平了道路。
In this paper, we introduce AERIQ: a software-defined radio (SDR) based I/Q measurement and analysis framework for wireless signals for aerial experimentation. AERIQ is integrated into controllable aerial vehicles, it is flexible, repeatable, and provides raw I/Q samples for post-processing the data to extract various key parameters of interest (KPIs) over a 3D volume. Using SDRs, we collect I/Q data with unmanned aerial vehicles (UAVs) flying at various altitudes in a radio dynamic zone (RDZ) like outdoor environment, from a 4G LTE eNB that we configure to operate at 3.51 GHz. Using the raw I/Q samples, and using Matlab's LTE Toolbox, we provide a step-by-step description for frequency offset estimation/correction, synchronization, cell search, channel estimation, and reference signal received power (RSRP). We provide various representative results for each step, such as RSRP measurements and corresponding analytical approximation at different UAV altitudes, coherence bandwidth and coherence time of the channel at different UAV altitudes and link distances, and kriging based 3D RSRP interpolation. The collected raw data as well as the software developed for obtaining and post-processing such data are provided publicly for potential use by other researchers. AERIQ is also available in emulation and testbed environments for external researchers to access and use as part of the NSF AERPAW platform at NC State University.
