Intelligent reflecting surface (IRS) is a promising technology to improve the performance of backscatter communication systems by smartly reconfiguring the multi-reflection channel. To fully exploit the passive beamforming gain of IRS in backscatter communication, channel state information (CSI) is indispensable but more practically challenging to acquire than conventional IRS-assisted systems, since IRS passively reflects signals over both the forward and backward (backscattering) links between the reader and tag. To address this issue, we propose in this letter a new and efficient channel estimation scheme for the IRS-assisted backscatter communication system. To minimize the mean-square error (MSE) of channel estimation, we formulate and solve an optimization problem by designing the IRS training reflection matrix for channel estimation under the constraints of unit-modulus elements and full rank. Simulation results verify the effectiveness of the proposed channel estimation scheme as compared to other baseline schemes.

中文翻译：

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智能反射面辅助后向散射通信的信道估计

智能反射面（IRS）是一种很有前途的技术，通过智能地重新配置多反射通道来提高反向散射通信系统的性能。为了在反向散射通信中充分利用 IRS 的无源波束形成增益，信道状态信息 (CSI) 是必不可少的，但比传统的 IRS 辅助系统更难获取，因为 IRS 通过前向和后向（反向散射）链路被动反射信号阅读器和标签。为了解决这个问题，我们在这封信中为 IRS 辅助的反向散射通信系统提出了一种新的有效的信道估计方案。为了最小化信道估计的均方误差 (MSE)，我们通过设计用于在单位模元素和满秩约束下进行信道估计的 IRS 训练反射矩阵来制定和解决优化问题。与其他基线方案相比，仿真结果验证了所提出的信道估计方案的有效性。