  Leveraging massive numbers of sensors in user equipment as well as
opportunistic human mobility, mobile crowd sensing (MCS) has emerged as a
powerful paradigm, where prolonging battery life of constrained devices and
motivating human involvement are two key design challenges. To address these,
we envision a novel framework, named wirelessly powered crowd sensing (WPCS),
which integrates MCS with wireless power transfer (WPT) for supplying the
involved devices with extra energy and thus facilitating user incentivization.
This paper considers a multiuser WPCS system where an access point (AP)
transfers energy to multiple mobile sensors (MSs), each of which performs data
sensing, compression, and transmission. Assuming lossless (data) compression,
an optimization problem is formulated to simultaneously maximize data utility
and minimize energy consumption at the operator side, by jointly controlling
wireless-power allocation at the AP as well as sensing-data sizes, compression
ratios, and sensor-transmission durations at the MSs. Given fixed compression
ratios, the proposed optimal power allocation policy has the threshold-based
structure with respect to a defined crowd-sensing priority function for each MS
depending on both the operator configuration and the MS information. Further,
for fixed sensing-data sizes, the optimal compression policy suggests that
compression can reduce the total energy consumption at each MS only if the
sensing-data size is sufficiently large. Our solution is also extended to the
case of lossy compression, while extensive simulations are offered to confirm
the efficiency of the contributed mechanisms.
