  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.
