  This paper studies the resource allocation algorithm design for secure
information and renewable green energy transfer to mobile receivers in
distributed antenna communication systems. In particular, distributed remote
radio heads (RRHs/antennas) are connected to a central processor (CP) via
capacity-limited backhaul links to facilitate joint transmission. The RRHs and
the CP are equipped with renewable energy harvesters and share their energies
via a lossy micropower grid for improving the efficiency in conveying
information and green energy to mobile receivers via radio frequency (RF)
signals. The considered resource allocation algorithm design is formulated as a
mixed non-convex and combinatorial optimization problem taking into account the
limited backhaul capacity and the quality of service requirements for
simultaneous wireless information and power transfer (SWIPT). We aim at
minimizing the total network transmit power when only imperfect channel state
information of the wireless energy harvesting receivers, which have to be
powered by the wireless network, is available at the CP. In light of the
intractability of the problem, we reformulate it as an optimization problem
with binary selection, which facilitates the design of an iterative resource
allocation algorithm to solve the problem optimally using the generalized
Bender's decomposition (GBD). Furthermore, a suboptimal algorithm is proposed
to strike a balance between computational complexity and system performance.
Simulation results illustrate that the proposed GBD based algorithm obtains the
global optimal solution and the suboptimal algorithm achieves a
close-to-optimal performance. Besides, the distributed antenna network for
SWIPT with renewable energy sharing is shown to require a lower transmit power
compared to a traditional system with multiple co-located antennas.
