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Secure ultra-reliable low-latency communication (URLLC) has been recentlyinvestigated with the fundamental limits of finite block length (FBL) regime inmind. Analysis has revealed that when eavesdroppers outnumber BS antennas orenjoy a more favorable channel condition compared to the legitimate users, basestation (BS) transmit power should increase exorbitantly to meet quality ofservice (QoS) constraints. Channel-induced impairments such as shadowing and/orblockage pose a similar challenge. These practical considerations candrastically limit secure URLLC performance in FBL regime. Deployment of anintelligent reflecting surface (IRS) can endow such systems with much-neededresiliency and robustness to satisfy stringent latency, availability, andreliability requirements. We address this problem and propose a joint design ofIRS platform and secure URLLC network. We minimize the total BS transmit powerby simultaneously designing the beamformers and artificial noise at the BS andphase-shifts at the IRS, while guaranteeing the required number of securelytransmitted bits with the desired packet error probability, informationleakage, and maximum affordable delay. The proposed optimization problem isnon-convex and we apply block coordinate descent and successive convexapproximation to iteratively solve a series of convex sub-problems instead. Theproposed algorithm converges to a sub-optimal solution in a few iterations andattains substantial power saving and robustness compared to baseline schemes.

Resource Allocation for IRS-Enabled Secure Multiuser Multi-Carrier Downlink URLLC Systems