Age of information analysis and optimization in wireless networks

The age of information (AoI) has emerged as a crucial metric in wireless communication systems, representing the freshness of information from its generation to its reception. This thesis focuses on optimizing AoI within wireless networks to improve the timeliness and reliability of information delivery and begins with a comprehensive review of existing literature on AoI, examining its significance, metrics, and challenges in modern wireless networks. One key area of investigation is the optimization of dynamic user pairing in downlink non-orthogonal multiple access (NOMA) systems. By dynamically pairing users based on AoI metrics, these algorithms aim to minimize information staleness while maximizing network efficiency. Furthermore, the thesis presents a novel scheduling strategy tailored for priority-aware Internet of things (IoT) networks to optimize AoI. This strategy prioritizes data packets based on their urgency, ensuring timely delivery of critical information. The impact of block coding on AoI in centralized IoT systems is also explored, leveraging insights from binary erasure channel (BEC) and binary symmetric channel (BSC). The effectiveness of block coding techniques in reducing AoI is evaluated through theoretical analysis and numerical experiments. Moreover, the role of network coding in improving information freshness and reliability across diverse Internet of things (IoT) networks is investigated. This includes examining its impact on AoI in multi-source multi-hop IoT networks, providing insights into optimizing AoI in complex network scenarios. In conclusion, this thesis presents a comprehensive exploration of AoI optimization in wireless networks, spanning algorithm design, network architecture, coding strategies and contributes to the evolution of next-generation wireless communication systems towards achieving timely and reliable information delivery.