We develop an optimal version of a prior two-stage channel estimation protocol for RIS-assisted channels. The new design uses a modified DFT matrix (MDFT) for the training phases at the RIS and is shown to minimize the total channel estimation error variance. In conjunction with interpolation (estimating fewer RIS channels), the MDFT approach accelerates channel estimation even when the channel from base station to RIS is line-of-sight. In contrast, prior two-stage techniques required a full-rank channel for efficient estimation. We investigate the resulting channel estimation errors by comparing different training phase designs for a variety of propagation conditions using a ray-based channel model. To examine the overall performance, we simulate the spectral efficiency with MRC processing for a single-user RIS-assisted system using an existing optimal design for the RIS transmission phases. Results verify the optimality of MDFT while simulations and analysis show that the performance is more dependent on the user-to-RIS channel correlation and the coarseness of the interpolation used, rather than the training phase design. For example, under a scenario with more highly correlated channels, the procedure accelerates channel estimation by a factor of 16, while the improvement is a factor of 5 in a less correlated case. The overall procedure is extremely robust, with a maximum performance loss of 1.5bits/sec/Hz compared to that with perfect channel state information for the considered channel conditions.
翻译:我们为RIS协助的渠道开发了前两阶段信道估计协议的最佳版本。新设计在RIS培训阶段使用经修改的DFT矩阵(MDFT),以尽量减少整个频道估计误差差异。结合内推(估计RIS频道较少),MDFT方法加快了频道估计,即使从基站到RIS的渠道是直线的。相比之下,前两阶段技术需要有一个全级的渠道才能有效估计。我们调查由此产生的频道估计错误,方法是利用光基频道模型比较各种传播条件的不同培训阶段设计。为了检查总体性能,我们用MRC处理单一用户的RIS辅助系统模拟光谱效率,使用现有最佳的RIS传输阶段设计。结果核查MFT的最佳性,同时进行模拟和分析表明,其性能更取决于用户对RIS频道的关联性能以及所使用的内推系统不精确性能。例如,在具有高度关联的频道/分级模型的情况下,与MRC处理单一用户的RIS辅助系统进行光谱的处理。根据一个最强的频道/分级的分级数据程序加速了第16级的分级的分级,而加速了第15级的分级的分级的分级的分级的分级的分级的分级程序,而加速了第15级的分级的分级的分级的分级的分级的分级的分级的分级的分级程序是第16级程序。