Abstract: For real-time monitoring applications, the age of information (AoI) is used as a key metric to quantify the freshness of updated information. In this paper, we consider the wireless powered networks where multiple source nodes observe processes and send update packets to the base station. Time is divided into slots which are equal duration. At each slot, either wireless energy transfer or packet update via non-orthogonal multiple access (NOMA) communication is scheduled. We aim to minimize the long-term average weighted sum of AoI of processes at the base station. Particularly, we formulate the AoI minimization problem as a multi-stage stochastic non-linear integer programming subject to the battery energy constraints. By adopting the Lyapunov optimization, we decouple the multi-stage stochastic problem into perframe deterministic subproblems and solve it with a low computational complexity algorithm. Simulation results show that our proposed scheme can achieve much smaller average weighted AoI than the benchmark algorithm.
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