  This paper investigates resource allocation for simultaneous wireless
information and power transfer (SWIPT) downlink systems based on a non-linear
energy harvesting model. The resource allocation algorithm design is formulated
as a non-convex optimization problem for the maximization of the total
harvested power. The proposed problem formulation not only takes into account
imperfect channel state information (CSI) but also guarantees the
quality-of-service (QoS) of information transfer. A novel iterative algorithm
is proposed to obtain the globally optimal solution of the considered
non-convex optimization problem. In each iteration, a rank-constrained
semidefinite program (SDP) is solved optimally by SDP relaxation. Simulation
results demonstrate the significant gains in harvested power and the robustness
against CSI imperfection for the proposed optimal resource allocation, compared
to a baseline scheme designed for perfect CSI and the conventional linear
energy harvesting model.
