Age of information in energy harvesting aided massive multiple access networks

Given the proliferation of the massive machine typecommunication devices (MTCDs) in beyond 5G (B5G) wirelessnetworks, energy harvesting (EH) aided next generation multipleaccess (NGMA) systems have drawn substantial attention inthe context of energy-efficient data sensing and transmission.However, without adaptive time slot (TS) and power allocationschemes, NGMA systems relying on stochastic sampling instantsmight lead to tardy actions associated both with high age ofinformation (AoI) as well as high power consumption. Formitigating the energy consumption, we exploit a pair of sleep scheduling policies, namely the multiple vacation (MV) policyand start-up threshold (ST) policy, which are characterized in thecontext of three typical multiple access protocols, including time division multiple access (TDMA), frequency-division multipleaccess (FDMA) and non-orthogonal multiple access (NOMA).Furthermore, we derive closed-form expressions for the MTCDsystem’s peak AoI, which are formulated as the optimizationobjective under the constraints of EH power, status update rateand stability conditions. An exact linear search based algorithmis proposed for finding the optimal solution by fixing the statusupdate rate. As a design alternative, a low complexity concave convex procedure (CCP) is also formulated for finding a near optimal solution relying on the original problem’s transformationinto a form represented by the difference of two convex problems.Our simulation results show that the proposed algorithms arebeneficial in terms of yielding a lower peak AoI at a low powerconsumption in the context of the multiple access protocolsconsidered.