In wireless powered communication networks (WPCNs), each user node, e.g., wireless powered sensor, is capable of either harvesting energy from a power station or transmitting data to a sink node. In the previous works, time division multiple access (TDMA) is typically used for transmission scheduling in WPCNs, that is, only one node can transmit data in one time slot. The spectrum efficiency is therefore limited by this orthogonality in time-domain scheduling. In this paper, to maximize the throughput in WPCNs, we present a new scheduling approach for energy harvesting and data transmission. Unlike TDMA, we consider that multiple nodes can simultaneously transmit their data in the same time slot, and the signals are separated at the sink node by performing successive interference cancellation (SIC). We formulate the throughput maximization problem as a linear programming problem. For solving the large scale instances, we design an algorithmic framework based on column generation. Numerical results demonstrate that compared to the TDMA based scheduling approach, substantial throughput improvement is achieved by the proposed algorithm.