Efficient data collection from a multitude of Internet of Things (IoT) devices is crucial for various applications, yet existing solutions often struggle with minimizing access delay and Age of Information (AoI), especially when managing multiple simultaneous transmissions and access strategies. This challenge becomes increasingly critical as IoT deployments continue to expand, demanding robust mechanisms for handling diverse traffic scenarios. In this study, we propose a novel approach leveraging Successive Interference Cancellation (SIC) based on adaptive and fixed parameter schemes to address these limitations. By analyzing both throughput and AoI along with access delay, we demonstrate the effectiveness of our adaptive approach compared to the fixed approach, particularly in scenarios featuring heavy and light traffic. Our findings highlight the pivotal role of adaptive approaches in optimizing data collection processes in IoT ecosystems, with a particular focus on minimizing access delay, AoI, and spectral efficiency.
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