URLLC in IRS-Aided MIMO Systems: Finite Blocklength Analysis and Design

TL;DR

This paper analyzes the URLLC performance of IRS-aided MIMO systems using finite blocklength theory, deriving bounds on error probability, and proposes an algorithm to optimize IRS phase shifts for improved reliability.

Contribution

It introduces a new CLT for mutual information density in IRS-aided MIMO systems and develops a gradient-based method to optimize IRS phase shifts for URLLC.

Findings

Derived bounds on error probability for URLLC in IRS-MIMO systems.

Validated the CLT and optimization algorithm through simulations.

Showed improved system reliability with optimized IRS phase shifts.

Abstract

This paper investigates the ultra reliable and low latency communication (URLLC) performance of the IRS-aided MIMO system. The upper and lower bounds of the optimal average error probability (OAEP) for the coding rate 1/sqrt(Mn) of the capacity are derived, where n and M represent the blocklength and the number of transmit antennas, respectively. To achieve this goal, a new central limit theorem (CLT) for the mutual information density over the IRS-aided MIMO system is derived in the asymptotic regime where the block-length, the IRS size, and number of the antennas go to infinity with the same pace. The CLT is then utilized to derive the closed form upper and lower bounds for the OAEP. Based on the analysis result, a gradient-based algorithm is proposed to minimize the lower bound of the OAEP by optimizing the phase shift of the IRS. Simulation results validate the fitness of the CLT and the effectiveness of the proposed algorithm in optimizing the theoretical bound, as well as the performance of practical LDPC code.