  In this thesis, we study the downlink multiuser scheduling and power
allocation problem for systems with simultaneous wireless information and power
transfer (SWIPT). In the first part of the thesis, we focus on multiuser
scheduling. We design optimal scheduling algorithms that maximize the long-term
average system throughput under different fairness requirements, such as
proportional fairness and equal throughput fairness. In particular, the
algorithm designs are formulated as non-convex optimization problems which take
into account the minimum required average sum harvested energy in the system.
The problems are solved by using convex optimization techniques and the
proposed optimization framework reveals the tradeoff between the long-term
average system throughput and the sum harvested energy in multiuser systems
with fairness constraints. Simulation results demonstrate that substantial
performance gains can be achieved by the proposed optimization framework
compared to existing suboptimal scheduling algorithms from the literature. In
the second part of the thesis, we investigate the joint user scheduling and
power allocation algorithm design for SWIPT systems. The algorithm design is
formulated as a non-convex optimization problem which maximizes the achievable
rate subject to a minimum required average power transfer. Subsequently, the
non-convex optimization problem is reformulated by big-M method which can be
solved optimally. Furthermore, we show that joint power allocation and user
scheduling is an efficient way to enlarge the feasible trade-off region for
improving the system performance in terms of achievable data rate and harvested
energy.
