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

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Document pages: 6 pages

Abstract: Large intelligent surfaces (LIS) present a promising new technology forenhancing the performance of wireless communication systems. So far, thesignificant performance gains brought by LIS have mainly been shown under theassumption that perfect channel state information is available. In practice,acquiring accurate channel knowledge poses a significant challenge, and thecorresponding overhead can be large. Here, we study the achievable rate of aLIS-assisted communication system accounting for such channel estimationoverhead. We demonstrate that there exists an optimal $K^{*}$, which maximizesachievable rate by balancing the power gains offered by LIS and the channelestimation overhead. We present analytical approximations for $K^{*}$, based onmaximizing an analytical upper bound on average achievable rate that we derive,and study the dependencies of $K^*$ on statistical channel and systemparameters.

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