Research on Age of Information in Multi-access User with Energy Harvesting Cognitive Radio Network

‍ ‍For the multi-access channel wireless sensor network scenario with limited channel resources， the transmission of real-time information needs to consider the channel environment and information freshness. Based on the cognitive radio-internet of things （CR-IoT） system， this paper constructed a network model of a primary user （PU） with spectrum access rights and two secondary users （SU） that can share the PU spectrum. Under the conditions of considering the PU operating state and the power connection SU node data queue stability， a minimized node average AoI was proposed. Second， two policies were used for optimization， including probabilistic random access policy （PRA）， in which two SU nodes made independent transmission decisions according to the corresponding probability distribution； and the drift plus penalty policy （DPP） based on the Lyapunov optimization framework was used to optimize the scheduling decision in the time slot. The simulation results show that the average AoI value obtained under the DPP policy is significantly lower than the PRA policy， indicating that the use of the DPP policy to optimize the average AoI is more significant， and can effectively improve the timeliness and freshness of data packets.