Optimizing Age of Information in Random Access Networks With Correlated Sources

Random access is a wireless network access technique that can meet the transmission requirements of a massive number of Internet of Things terminals under limited resource constraints. To address the needs of delay-sensitive applications, it is essential to study random access strategies from the perspective of information timeliness. Existing research often assumes that the information transmitted by terminals is independent of each other, neglecting the correlation between information in the design process of random access strategies. However, in scenarios such as video surveillance and sensor monitoring, adjacent terminal transmissions exhibit spatial correlation. To overcome this limitation, this paper proposes a random access strategy based on information timeliness and information correlation. Specifically, we establish information correlation between information sources and analyze the coupling variation of Age of Information (AoI) in multipoint transmission scenarios, deriving an expression for the average network AoI. Next, by jointly optimizing the random access probabilities of various terminals, we minimize the average network AoI. To address the non-convex and nonlinear optimization problem, we design an optimization algorithm based on Sequential Quadratic Programming and propose an approach to obtain initial values for improved algorithm stability. Simulation results demonstrate that the proposed method significantly reduces the average network AoI compared to random strategies that do not consider correlation.