In this paper, we focus on resource allocation schemes for minimizing the energy consumption of subscriber stations (SSs) in uplink flows of the IEEE 802.16 OFDMA systems. The resource allocation schemes assign subcarriers, powers, and data rates to each SS based on the measured signal to noise ratio (SNR) of the uplink channel and predefined modulation and coding scheme as system parameters. Previous research efforts to optimize resource allocation focus on the rate and throughput maximizations, and develop suboptimal heuristic algorithms. However, this paper intends to reduce the energy consumption of SSs by considering the relationship between energy efficiency and resource allocation. In order to clearly formulate the relationship, we use the Multiple Choice Knapsack (MCK) problem, which is proved to be an NP-hard problem. We propose two heuristic schemes to solve the NP-hard problem, which adaptively use the modulation and coding scheme, defined in the IEEE 802.16 OFDMA systems to minimize the required transmission power of each SS. Our simulation results show that the proposed schemes can reduce the energy consumption by up to 53% compared to the channel state information (CSI) scheme, which determines the modulation and coding level only considering the channel state information.