Wireless Powered Underground Sensor Networks (WPUSNs) extend the lifetime of underground Internet of Things (IoT) through Radio Frequency (RF) harvesting technology. However, severe transmission attenuation and dynamic Quality of Service (QoS) requirements often lead to energy imbalance and waste issues in WPUSNs. To address the challenges, we introduce a recycling mechanism that enables nodes to harvest energy from each other, thereby proposing the recycling WPUSN. Under this framework, the time allocation strategy is key to balancing energy harvesting and transmission performance. We take time slot as the optimization variable and formulate an energy efficiency maximization problem under heterogeneous QoS constraints. To solve this nonconcave fractional programming problem, we develop a Quadratic Transform-based Projected (QTP) Algorithm, which iteratively applies Karush–Kuhn–Tucker (KKT) conditions and projection operations to approximate the optimal solution. The simulation results demonstrate that the proposed method improves energy efficiency performance by 17.454% and converges 70 times faster compared with the commercial optimization solvers. The proposed recycling WPUSN opens up new prospects for sustainable underground environmental monitoring.