In this paper, we study an IRS-assisted coverage enhancement problem for a given region, aiming to optimize the passive reflection of the IRS for improving the average communication performance in the region by accounting for both deterministic and random channels in the environment. To this end, we first derive the closed-form expression of the average received signal power in terms of the deterministic base station (BS)-IRS-user cascaded channels over all user locations, and propose an IRS-aided coverage enhancement framework to facilitate the estimation of such deterministic channels for IRS passive reflection design. Specifically, to avoid the exorbitant overhead of estimating the cascaded channels at all possible user locations, a location selection method is first proposed to select only a set of typical user locations for channel estimation by exploiting the channel spatial correlation in the region. To estimate the deterministic cascaded channels at the selected user locations, conventional IRS channel estimation methods require additional pilot signals, which not only results in high system training overhead but also may not be compatible with the existing communication protocols. To overcome this issue, we further propose a single-layer neural network (NN)-enabled IRS channel estimation method in this paper, based on only the average received signal power measurements at each selected location corresponding to different IRS random training reflections, which can be offline implemented in current wireless systems. Numerical results demonstrate that our proposed scheme can significantly improve the coverage performance of the target region and outperform the existing power-measurement-based IRS reflection designs.

翻译：本文研究针对特定区域的IRS辅助覆盖增强问题，旨在通过综合考虑环境中的确定性信道与随机信道，优化IRS的无源反射以提升区域内的平均通信性能。为此，我们首先推导了平均接收信号功率关于所有用户位置上确定性基站(BS)-IRS-用户级联信道的闭式表达式，并提出一种IRS辅助覆盖增强框架以促进此类确定性信道的估计，进而实现IRS无源反射设计。具体而言，为避免在所有可能用户位置估计级联信道的高昂开销，首先利用区域内的信道空间相关性提出一种位置选择方法，仅选取一组典型用户位置进行信道估计。针对所选用户位置上的确定性级联信道估计，传统IRS信道估计方法需要额外导频信号，这不仅导致较高的系统训练开销，还可能无法兼容现有通信协议。为解决该问题，本文进一步提出一种基于单层神经网络(NN)的IRS信道估计方法，该方法仅需利用各选定位置上对应不同IRS随机训练反射的平均接收信号功率测量值，可在现有无线系统中离线实现。数值结果表明，所提方案能显著提升目标区域的覆盖性能，且优于现有基于功率测量的IRS反射设计方案。