Channel estimation overhead reduction scheme and its impact in IRS-assisted systems

Abstract

Intelligent reflecting surfaces (IRS) have been proposed as a promising solution for enhancing wireless communication by manipulating the wireless propagation environment. To facilitate IRS-assisted communication, the base station (BS) requires accurate channel state information (CSI), which is typically obtained by receiving sounding reference signals (SRS) from the user equipment (UE). Due to numerous reflecting elements in IRS, however, the transmission of SRS is resource-intensive and reduces the available resources for data transmission. To reduce the overhead, in this paper, the SRSs are transmitted exclusively to estimate only the dominant channel at the cost of reduced CSI accuracy. Next, we consider residual interference caused by the channel estimation error, and factor it into the signal-to-interference-plus-noise-ratio of a UE. We then formulate an optimization problem that jointly computes the coefficients of reflecting elements in the IRS and MIMO precoding. Lastly, we adopt a computationally efficient algorithm based on the weighted minimization of the minimum square error (WMMSE). The performance of the proposed scheme with reduced overhead is compared to that of the ideal and conventional schemes by varying the number of SRS transmissions, IRS elements, and penetration loss.

Keywords

• Intelligent reflecting surface (IRS)
• Incomplete channel state information
• Joint optimization
• MIMO precoding