Age of information in energy harvesting aided massive multiple access networks

Abstract

Given the proliferation of the massive machine type
communication devices (MTCDs) in beyond 5G (B5G) wireless
networks, energy harvesting (EH) aided next generation multiple
access (NGMA) systems have drawn substantial attention in
the context of energy-efficient data sensing and transmission.
However, without adaptive time slot (TS) and power allocation
schemes, NGMA systems relying on stochastic sampling instants
might lead to tardy actions associated both with high age of
information (AoI) as well as high power consumption. For
mitigating the energy consumption, we exploit a pair of sleep scheduling policies, namely the multiple vacation (MV) policy
and start-up threshold (ST) policy, which are characterized in the
context of three typical multiple access protocols, including time division multiple access (TDMA), frequency-division multiple
access (FDMA) and non-orthogonal multiple access (NOMA).
Furthermore, we derive closed-form expressions for the MTCD
system’s peak AoI, which are formulated as the optimization
objective under the constraints of EH power, status update rate
and stability conditions. An exact linear search based algorithm
is proposed for finding the optimal solution by fixing the status
update 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 transformation
into a form represented by the difference of two convex problems.
Our simulation results show that the proposed algorithms are
beneficial in terms of yielding a lower peak AoI at a low power
consumption in the context of the multiple access protocols
considered.

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Identifiers

ORCID for Lajos Hanzo: orcid.org/0000-0002-2636-5214

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