论文标题
具有线性MMSE通道估计的流体天线的大规模细胞网络
Fluid Antenna with Linear MMSE Channel Estimation for Large-Scale Cellular Networks
论文作者
论文摘要
可重新配置流体天线(FA)的概念是提高无线通信网络光谱效率的潜在解决方案。尽管它们具有许多优势,但支持FA的通信仍存在局限性,因为它们需要大量的光谱资源,以便从大量规定的位置中选择辐射元素最理想的位置。在本文中,我们提出了一个分析框架,用于大规模实现FA的通信的中断性能,其中所有用户设备(UES)都采用循环多FA阵列。与现有的研究相反,该研究具有完美的渠道状态信息,开发的框架准确捕获了所考虑的网络部署性能的渠道估计错误。特别是,我们专注于有限的相干间隔方案,其中仅对少数的FA端口进行了新型的顺序线性最小均值误差(LMMSE)基于基于的通道估计方法。接下来,对于每个BS与其相关的UE的通信,采用了低复杂性端口选择技术,其中在端口中选择了提供最高的信号到信号间隔 - 噪声差异的端口,这些端口估计可以从每个FA提供最强的通道。通过使用随机几何工具,我们为中断概率得出了分析和闭合形式表达式,突出了通道估计对基于FA的UES性能的影响。我们的结果表明,在提高网络的性能和降低渠道估计质量之间实现了权衡,这表明了设计支持FA的通信的新见解。
The concept of reconfigurable fluid antennas (FA) is a potential and promising solution to enhance the spectral efficiency of wireless communication networks. Despite their many advantages, FA-enabled communications have limitations as they require an enormous amount of spectral resources in order to select the most desirable position of the radiating element from a large number of prescribed locations. In this paper, we present an analytical framework for the outage performance of large-scale FA-enabled communications, where all user equipments (UEs) employ circular multi-FA array. In contrast to existing studies, which assume perfect channel state information, the developed framework accurately captures the channel estimation errors on the performance of the considered network deployments. In particular, we focus on the limited coherence interval scenario, where a novel sequential linear minimum mean-squared error (LMMSE)-based channel estimation method is performed for only a very small number of FA ports. Next, for the communication of each BS with its associated UE, a low-complexity port-selection technique is employed, where the port that provides the highest signal-to-interference-plus-noise-ratio is selected among the ports that are estimated to provide the strongest channel from each FA. By using stochastic geometry tools, we derive both analytical and closed-form expressions for the outage probability, highlighting the impact of channel estimation on the performance of FA-based UEs. Our results reveal the trade-off imposed between improving the network's performance and reducing the channel estimation quality, indicating new insights for the design of FA-enabled communications.