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Performance Analysis of Active Large Intelligent Surfaces (LISs): Uplink Spectral Efficiency and Pilot Training

机译:活跃大型智能表面的性能分析(LISS):上行谱效率和飞行员训练

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摘要

Large intelligent surfaces (LISs) constitute a new and promising wireless communication paradigm that relies on the integration of a massive number of antenna elements over the entire surfaces of man-made structures. The LIS concept provides many advantages, such as the capability to provide reliable and space-intensive communications by effectively establishing line-of-sight (LOS) channels. In this paper, the system spectral efficiency (SSE) of an active LIS system is asymptotically analyzed under a practical LIS environment with a well-defined uplink frame structure. In order to verify the impact on the SSE of pilot contamination, the SSE of a multi-LIS system is asymptotically studied and a theoretical bound on its performance is derived. Given this performance bound, an optimal pilot training length for multi-LIS systems subjected to pilot contamination is characterized and, subsequently, the number of devices that need to be serviced by the LIS in order to maximize the performance is derived. Simulation results show that the derived analyses are in close agreement with the exact mutual information in presence of a large number of antennas, and the achievable SSE is limited by the effect of pilot contamination and intra/inter-LIS interference through the LOS path, even if the LIS is equipped with an infinite number of antennas. Additionally, the SSE obtained with the proposed pilot training length and number of scheduled devices is shown to reach the one obtained via a brute-force search for the optimal solution.
机译:大型智能表面(Liss)构成了一种新的和有前途的无线通信范式,依赖于在人造结构的整个表面上积分大量的天线元件。 LIS概念提供了许多优点,例如通过有效地建立视线(LOS)频道来提供可靠和空间密集型通信的能力。在本文中,有源LIS系统的系统光谱效率(SSE)在具有明确定义的上行链路帧结构的实际LIS环境下渐近分析。为了验证对导频污染的SSE的影响,多LIS系统的SSE是渐近研究的,并且得出了其性能的理论界限。鉴于这种性能绑定,对经过导频污染的多LIS系统的最佳导频训练长度表征,随后,推导出最大化性能以最大化性能来维修的设备数量。仿真结果表明,衍生的分析与在大量天线存在下的确切互联信息密切一致,可实现的SSE受到通过洛杉矶路径的导频污染和内部/骚扰的影响的限制如果LIS配备有无限数量的天线。另外,利用所提出的导频训练长度和预定设备数量获得的SSE被示出通过Brute-Force搜索最佳解决方案来达到获得的SSE。

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