Optimizing Information Freshness in Grant-Free Communication Under AoI Threshold Constraints

In this paper, we investigate a compressive sensing (CS)-based grant-free communication scheme for the Internet of Things (IoT), where devices transmit only when their realtime age of information (AoI) reaches a predefined threshold. This novel approach, termed CS-based age-dependent grant-free (ADGF) communication, integrates a discrete-time Markov chain model to analyze AoI evolution and closed-form expressions for average AoI is derived. To achieve optimal AoI performance, the framework systematically optimizes key parameters, including device activation probabilities, AoI threshold, and the maximum number of simultaneously active devices, while ensuring compliance with constraints like transmitting power and system sparsity. Simulation results validate that the proposed approach outperforms existing methods, achieving lower average AoI through efficient channel access and collision reduction. The study reveals key design insights, including the inverse relationship between AoI threshold and transmitting power, as well as the impact of spreading sequence length on performance. The ADGF scheme offers a scalable and effective solution for maintaining timely updates in grant-free IoT systems, facilitating more reliable and efficient real-time communication and monitoring.