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Asymptotic Max-Min SINR Analysis of Reconfigurable Intelligent Surface Assisted MISO Systems

机译:可重新配置智能表面辅助MISO系统的渐近MAX-MINR分析

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This work focuses on the downlink of a single-cell multi-user system in which a base station (BS) equipped with M antennas communicates with K single-antenna users through a reconfigurable intelligent surface (RIS) installed in the line-ofsight (LoS) of the BS. RIS is envisioned to offer unprecedented spectral efficiency gains by utilizing N passive reflecting elements that induce phase shifts on the impinging electromagnetic waves to smartly reconfigure the signal propagation environment. We study the minimum signal-to-interference-plus-noise ratio (SINR) achieved by the optimal linear precoder (OLP), that maximizes the minimum SINR subject to a given power constraint for any given RIS phase matrix, for the cases where the LoS channel matrix between the BS and the RIS is of rankone and of full-rank. In the former scenario, the minimum SINR achieved by the RIS-assisted link is bounded by a quantity that goes to zero with K. For the high-rank scenario, we develop accurate deterministic approximations for the parameters of the asymptotically OLP, which are then utilized to optimize the RIS phase matrix. Simulation results show that RISs can outperform half-duplex relays with a small number of passive reflecting elements while large RISs are needed to outperform full-duplex relays.
机译:这项工作侧重于单个小区多用户系统的下行链路,其中配备有M天线的基站(BS)通过安装在线 - ofsight中的可重构智能表面(RIS)通信与K单天线用户(LOS )BS。设想RIS通过利用诱导电磁波上的诱导相位移位以巧妙地重新配置信号传播环境来提供前所未有的光谱效率提升。我们研究了通过最佳线性预编码器(OLP)实现的最小信号到干扰噪声比(SINR),其为任何给定的RIS相位矩阵而最大化对给定功率约束的最小SINR,对于其中的情况LOS频道矩阵在BS和RIS之间是Rankone和全级别的。在以前的场景中,RIS辅助链路所实现的最小SINR由K.对于高级方案,我们为渐近OLP的参数开发了准确的确定性近似值,然后利用以优化RIS相矩阵。仿真结果表明,RISS可以优于少量无源反射元件的半双工继电器,而大型riss需要大于全双工继电器。

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