  The separate receiver architecture with a time- or power-splitting mode,
widely used for simultaneous wireless information and power transfer (SWIPT),
has a major drawback: Energy-intensive local oscillators and mixers need to be
installed in the information decoding (ID) component to downconvert radio
frequency (RF) signals to baseband signals, resulting in high energy
consumption. As a solution to this challenge, an integrated receiver (IR)
architecture has been proposed, and, in turn, various SWIPT modulation schemes
compatible with the IR architecture have been developed. However, to the best
of our knowledge, no research has been conducted on modulation scheduling in
SWIPT-based IoT sensor networks while taking into account the IR architecture.
Accordingly, in this paper, we address this research gap by studying the
problem of joint scheduling for unicast/multicast, IoT sensor, and modulation
(UMSM) in a time-slotted SWIPT-based IoT sensor network system. To this end, we
leverage mathematical modeling and optimization techniques, such as the
Lagrangian duality and stochastic optimization theory, to develop an UMSM
scheduling algorithm that maximizes the weighted sum of average unicast service
throughput and harvested energy of IoT sensors, while ensuring the minimum
average throughput of both multicast and unicast, as well as the minimum
average harvested energy of IoT sensors. Finally, we demonstrate through
extensive simulations that our UMSM scheduling algorithm achieves superior
energy harvesting (EH) and throughput performance while ensuring the
satisfaction of specified constraints well.
