A proposed resource allocation(RA) scheme is given to device-to-device(D2D) communication underlaying cellular networks from an end-to-end energy-efficient perspective, in which, the end-to-end energy consumptions were taken into account. Furthermore, to match the practical situations and maximize the energy-efficiency(EE), the resource units(RUs) were used in a complete-shared pattern. Then the energy-efficient RA problem was formulated as a mixed integer and non-convex optimization problem, extremely difficult to be solved. To obtain a desirable solution with a reasonable computation cost, this problem was dealt with two steps. Step 1, the RU allocation policy was obtained via a greedy search method. Step 2, after obtaining the RU allocation, the power allocation strategy was developed through quantum-behaved particle swarm optimization(QPSO). Finally, simulation was presented to validate the effectiveness of the proposed RA scheme. A proposed resource allocation (RA) scheme is given to device-to-device (D2D) communication underlaying cellular networks from an end-to-end energy-efficient perspective, in which, the end- to-end energy consumptions were taken into account ., To match the practical situations and maximize the energy-efficiency (EE), the resource units (RUs) were used in a complete-shared pattern. Then the energy-efficient RA problem was formulated as a mixed integer and non-convex optimization problem, extremely difficult to be solved. To obtain a desirable solution with a reasonable computation cost, this problem was dealt with two steps. allocation, the power allocation strategy was developed through quantum-behaved particle swarm optimization (QPSO). Finally, simulation was presented to validate the effectiveness of the proposed RA scheme.