  In the emerging fifth generation (5G) technology, communication nodes are
expected to support two crucial classes of information traffic, namely, the
enhanced mobile broadband (eMBB) traffic with high data rate requirements, and
ultra-reliable low-latency communications (URLLC) traffic with strict
requirements on latency and reliability. The URLLC traffic, which is usually
analyzed by a metric called the age of information (AoI), is assigned the first
priority over the resources at a node. Motivated by this, we consider long-term
average throughput maximization problems subject to average AoI and power
constraints in a single user fading channel, when (i) perfect and (ii) no
channel state information at the transmitter (CSIT) is available. We propose
simple age-independent stationary randomized policies (AI-SRP), which allocate
powers at the transmitter based only on the channel state and/or distribution
information, without any knowledge of the AoI. We show that the optimal
throughputs achieved by the AI-SRPs for scenarios (i) and (ii) are at least
equal to the half of the respective optimal long-term average throughputs,
independent of all the parameters of the problem, and that they are within
additive gaps, expressed in terms of the optimal dual variable corresponding to
their average AoI constraints, from the respective optimal long-term average
throughputs.
