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arXiv 2008.09843eess.SP
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具有信道估计开销的大型智能表面:可调速率和最优配置

Large Intelligent Surfaces with Channel Estimation Overhead: Achievable Rate and Optimal Configuration

Neel Kanth Kundu, Matthew R. McKay

摘要:

大型智能表面(LIS)是一种提高无线通信系统性能的新技术。实现LIS的增益需要精确的信道知识,并且实际上,由于LIS的被动性质,信道估计开销可能很大。在这里,我们研究了LIS辅助的单输入单输出通信系统的可达速率,占导频开销的最小二乘信道估计。我们证明,存在一个最佳的$K^{*}$,最大限度地提高可实现的速率,通过平衡LIS和信道估计开销提供的功率增益。我们提出了解析近似的$K^{*}$,基于最大化的分析上界的平均可达速率,我们得出,并研究了统计信道和系统参数的依赖关系的$K^*$。

英文摘要:

Large intelligent surfaces (LIS) present a promising new technology for enhancing the performance of wireless communication systems. Realizing the gains of LIS requires accurate channel knowledge, and in practice the channel estimation overhead can be large due to the passive nature of LIS. Here, we study the achievable rate of a LIS-assisted single-input single-output communication system, accounting for the pilot overhead of a least-squares channel estimator. We demonstrate that there exists an optimal $K^{*}$, which maximizes achievable rate by balancing the power gains offered by LIS and the channel estimation overhead. We present analytical approximations for $K^{*}$, based on maximizing an analytical upper bound on average achievable rate that we derive, and study the dependencies of $K^*$ on statistical channel and system parameters.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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