LAUSR

The Age of Information (AoI), which evaluates the information freshness, and the energy efficiency (EE) play key roles in cellular IoT networks. This is due to that outdated data can hardly provide any useful information for delay-sensitive applications and the IoT devices usually have limited battery life. In particular, the AoI can be significantly affected by the transmission latency, which becomes the bottleneck for the AoI performance in ultradensely deployed cellular IoT networks. Moreover, it is desirable for cellular IoT networks to achieve low AoI with high EE. The data compression (DC) can decrease the AoI and improve the EE by reducing the transmission latency. Therefore, in this work, the AoI and EE performance in a large-scale densely deployed uplink cellular IoT network are jointly analyzed with the DC technology. Specifically, the closed-form results of AoI are derived and validated by Monte Carlo simulations. Based on these results, the AoI–EE ratio is defined to evaluate the tradeoff between the AoI and the EE. Equipped with these results, the effects of compression ratio (CR) and status update packet generation rate (SUPGR) on both the AoI and the AoI–EE ratio are analyzed numerically. The results show that by jointly optimizing the CR and SUPGR, the AoI can be decreased by up to 82% and the AoI–EE ratio can be reduced by up to 83% as compared with the case that only adjusts the SUPGR without the DC. It indicates that the DC should be widely adopted in IoT devices, which can improve the information freshness with low-energy consumption, especially in an ultradensely deployed scenario.