  This paper studies a wireless powered mobile edge computing (MEC) system,
where a dedicated energy transmitter (ET) uses the radio-frequency (RF) signal
enabled wireless power transfer (WPT) to charge wireless devices for
sustainable computation. In such a system, we present a new user cooperation
approach to improve the computation performance of active devices, in which
surrounding idle devices are enabled as helpers to use their opportunistically
harvested wireless energy from the ET to help remotely execute active users'
computation tasks. In particular, we consider a basic scenario with one user
(with computation tasks to execute) and multiple helpers, in which the user can
partition the computation tasks into various parts for local execution and
computation offloading to helpers, respectively. Both the user and helpers are
subject to the so-called energy neutrality constraints, such that their energy
consumption does not exceed the respective energy harvested from the ET. Under
this setup and considering a frequency division multiple access (FDMA) based
computation offloading protocol, we maximize the computation rate (i.e., the
number of computation bits over a particular time block) of the user, by
jointly optimizing the transmit energy beamforming at the ET, as well as the
communication and computation resource allocations at both the user and
helpers. By leveraging the Lagrange duality method, we present the optimal
solution to this problem in a semi-closed form. Numerical results show that the
proposed wireless powered user cooperative computation design significantly
improves the computation rate at the user, as compared to conventional schemes
without such cooperation.
