Modern wireless communication systems are expected to provide improved latency and reliability. To meet these expectations, a short packet length is needed, which makes the first-order Shannon rate an inaccurate performance metric for such communication systems. A more accurate approximation of the achievable rates of finite-block-length (FBL) coding regimes is known as the normal approximation (NA). It is therefore of substantial interest to study the optimization of the FBL rate in multi-user multiple-input multiple-output (MIMO) systems, in which each user may transmit and/or receive multiple data streams. Hence, we formulate a general optimization problem for improving the spectral and energy efficiency of multi-user MIMO-aided ultra-reliable low-latency communication (URLLC) systems, which are assisted by reconfigurable intelligent surfaces (RISs). We show that a RIS is capable of substantially improving the performance of multi-user MIMO-aided URLLC systems. Moreover, the benefits of RIS increase as the packet length and/or the tolerable bit error rate are reduced. This reveals that RISs can be even more beneficial in URLLC systems for improving the FBL rates than in conventional systems approaching Shannon rates.

翻译：现代无线通信系统对时延与可靠性提出了更高要求，为此需要采用短数据包传输，这使得一阶香农速率成为此类通信系统不精确的性能指标。针对有限块长编码机制可达速率的更精确近似称为正态近似。因此，研究多用户多输入多输出（MIMO）系统中有限块长速率的优化具有重要价值——在该系统中，每个用户可同时传输和/或接收多个数据流。为此，我们构建了一个通用优化问题，旨在提升由可重构智能表面辅助的多用户MIMO超可靠低时延通信系统的频谱与能量效率。研究表明，RIS能够显著提升多用户MIMO辅助URLLC系统的性能。此外，RIS的增益随数据包长度和/或可容忍误码率的降低而增大。这表明相较于逼近香农速率的传统系统，RIS在提升URLLC系统有限块长速率方面具有更显著的优势。