Aiming at the problem of low energy consumption, high speed, and low latency required for resource allocation for multi-cell cellular networks, a deep unsupervised learning based resource allocation method is proposed. Firstly, an unsupervised learning based deep power control neural network is constructed to output an optimized channel power control scheme by constraint handling, so as to maximize the expectation of energy efficiency. Then, an unsupervised learning based deep channel allocation neural network is constructed to output an optimized channel allocation scheme by constraint handling, and the unsupervised learning based deep power control neural network trained well previously is combined to fit and output the optimized channel power control scheme to further optimize the expectation of energy efficiency. The simulation results show that the proposed method can obtain better transmission rate and energy efficiency than other algorithms while ensuring low computational latency.