This letter studies an intelligent reflecting surface (IRS)-aided downlink ultra-reliable and low-latency communication (URLLC) system, in which an IRS is dedicatedly deployed to assist a base station (BS) to send individual short-packet messages to multiple users. To enhance the URLLC performance, the users are divided into different groups and the messages for users in each group are encoded into a single codeword. By considering the time division multiple access (TDMA) protocol among different groups, our objective is to minimize the total latency for all users subject to their individual reliability requirements, via jointly optimizing the user grouping and blocklength allocation at the BS together with the reflective beamforming at the IRS. We solve the latency minimization problem via the alternating optimization, in which the blocklengths and the reflective beamforming are optimized by using the techniques of successive convex approximation (SCA) and semi-definite relaxation (SDR), while the user grouping is updated by K-means and greedy-based methods. Numerical results show that the proposed designs can significantly reduce the communication latency, as compared to various benchmark schemes, which unveil the importance of user grouping and reflective beamforming optimization for exploiting the joint encoding gain and enhancing the worst-case user performance.

中文翻译：

---

用于 IRS 辅助 URLLC 的用户分组和反射波束成形

这封信研究了一种智能反射面（IRS）辅助下行超可靠低时延通信（URLLC）系统，其中专门部署了一个IRS来辅助基站（BS）向多个基站发送单独的短包消息。用户。为了提高 URLLC 性能，用户被分成不同的组，每个组中用户的消息被编码成单个码字。通过考虑不同组之间的时分多址 (TDMA) 协议，我们的目标是通过联合优化 BS 的用户分组和块长度分配以及反射波束成形，最大限度地减少所有用户的总延迟，以满足他们各自的可靠性要求在国税局。我们通过交替优化解决延迟最小化问题，其中块长度和反射波束成形通过使用连续凸逼近 (SCA) 和半定松弛 (SDR) 技术进行优化，而用户分组通过 K-means 和基于贪婪的方法更新。数值结果表明，与各种基准方案相比，所提出的设计可以显着降低通信延迟，这揭示了用户分组和反射波束成形优化对于利用联合编码增益和提高最坏情况用户性能的重要性。