This article studies a wireless powered sensor network (WPSN), where sensors harvest energy from a hybrid access point (H-AP) and then transmit information to the H-AP via nonorthogonal multiple access (NOMA) scheme. The energy efficiency (EE) maximization problem for the NOMA-based WPSN is, for the first time, formulated as a nonlinear fractional programming, which is difficult to solve for global optimality due to the lack of convexity. To this end, we propose two important properties for the optimal solution to the EE maximization problem, based on which a particle-swarmoptimization-based solution algorithm is proposed. Simulations demonstrate the fast convergence and stability of the proposed algorithm.