论文标题
部分可观测时空混沌系统的无模型预测
Integrated Access and Backhaul in Cell-free Massive MIMO Systems
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。
One of the major challenges with cell-free (CF) massive multiple-input multiple-output (MIMO) networks is providing backhaul links for a large number of distributed access points (APs). In general, providing fiber optics backhaul for these APs is not cost-effective and also reduces network scalability. Wireless backhauling can be a promising solution that can be integrated with wireless access links to increase spectrum efficiency. In this paper, the application of integrated access and backhaul (IAB) technique in millimeter-wave (mmWave) CF massive MIMO systems is investigated. The access and backhaul links share a frequency spectrum in the mmWave bands, and in both, hybrid beamforming techniques are adopted for signal transmission. The bandwidth allocation (division) parameter between the two link types as well as the beamforming matrices are optimized to maximize the end-to-end data-rate. This leads to a non-convex optimization problem for which an efficient solution method is proposed. The simulation results show the effectiveness of the IAB technique and our proposed scheme in CF massive MIMO systems. These simulations also compare the proposed hybrid beamforming method with a fully digital solution in terms of the number of radio frequency (RF) chains and the volume of backhaul traffic. Finally, the effect of increasing the number of APs on the users data rates in terms of wireless access and backhaul links constraints is also examined.
