Timely sampling and fresh information delivery are important in 6G communications. This is achieved by encoding samples into short packets/codewords for transmission, with potential decoding errors. We consider a broadcasting base station (BS) that samples information from multiple sources and transmits to respective destinations/users, using short-blocklength cyclic and deep learning (DL) based codes for error correction, and cyclic-redundancy-check (CRC) codes for error detection. We use a metric called reported age of information (AoI), abbreviated as RAoI, to measure the freshness of information, which increases from an initial value if the CRC reports a failure, else is reset. We minimize long-term average expected RAoI, subject to constraints on transmission power and distortion, for which we obtain age-agnostic randomized and age-aware drift-plus-penalty policies that decide which user to transmit to, with what message-word length and transmit power, and derive bounds on their performance. Simulations show that longer CRC codes lead to higher RAoI, but the RAoI achieved is closer to the true, genie-aided AoI. DL-based codes achieve lower RAoI. Finally, we conclude that prior AoI optimization literature with finite blocklengths substantially underestimates AoI because they assume that all errors can be detected perfectly without using CRC.

翻译：在6G通信中，及时采样和传递新鲜信息至关重要。这通过将样本编码为短分组/码字进行传输实现，但存在解码错误的可能。我们考虑一个广播基站（BS），它从多个信源采样信息，并使用短码长循环码和基于深度学习（DL）的纠错码以及循环冗余校验（CRC）检错码，将其传输至对应目标/用户。我们采用称为报告信息时效性（RAoI）的指标衡量信息新鲜度：若CRC报告校验失败，RAoI从初始值递增；否则重置为初始值。在传输功率和失真约束下，我们最小化长期平均期望RAoI，为此提出了与年龄无关的随机策略和与年龄相关的漂移加惩罚策略，以决定向谁传输、采用何种消息字长度及传输功率，并推导了其性能边界。仿真结果表明，更长的CRC码会导致更高RAoI，但所获RAoI更接近真实的理想辅助信息时效性（AoI）。基于DL的编码可实现更低的RAoI。最后，我们得出结论：现有有限码长下的AoI优化文献显著低估了实际AoI，因其假设无需CRC即可完美检测所有错误。