We comprehensively analyze the average block error rate (BLER) performance of intelligent reflecting surface (IRS) aided short-packet communication (SPC) systems over Rician fading. Our analysis covers two communication scenarios, depending on whether or not the direct link exists between the base station and the user, addresses two types of phase errors, namely, phase estimation errors modeled by the Von Mises distribution and quantization errors, and facilitates system design based on the instantaneous channel state information (CSI) and the statistical CSI. In our analysis, we first derive the distributions of the end-to-end channel and the received signal-to-noise ratio at the user under different phase adjustment strategies. Then we propose a more accurate approximation of the $Q$ function to derive closed-form expressions for the average BLER. Using numerical and simulation results, we corroborate the accuracy of our analysis and investigate the impacts of various parameters of the system, such as the number of IRS elements and the phase adjustment strategy, and different CSI availabilities on the average BLER performance. We also show that compared to the instantaneous CSI based design, the statistical CSI based design yields the near-optimal BLER performance for a large Rician factor, making it attractive for ultra-reliable and low-latency communications, given its low implementation complexity.

This paper analyzes the performance of an intelligent reflecting surface (IRS)-aided short-packet communication system over Nakagami-m fading channels. In this system, the base station adopts non-orthogonal multiple access (NOMA) to transmit to a near user and a far user, and its transmission to the far user is aided by the IRS. Both continuous phase shifts (CPSs) and discrete phase shifts (DPSs) are considered for the IRS. By using order statistic and moment matching, we approximate the end-to-end channel gain to follow the Gamma distribution and then derive the approximate closed-form expressions for the average block error rate (BLER) in the high signal-to-noise ratio (SNR) regime and then conduct a refifined analysis of the interplay among the minimum common blocklength, optimal power allocation, and the related parameters of IRS (e.g., the number of elements of the IRS) for achieving target BLERs at two users. Finally, numerical and simulation results demonstrate the accuracy of theoretical analysis. They also show that the IRS-aided short-packet NOMA system outperforms the system without IRS, and that DPSs with 3-bit quantization achieve a similar performance as the optimal CPSs.