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Adaptive resource allocation is one of the hottest topic in almost every field of study and research now a day. It promises optimal utilization of resources while satisfying certain number of constraints. A similar constrained optimization problem has been solved for OFDM environment where channel hostilities are mitigated and throughput is maximized by adaptively selecting code rate, modulation symbol and transmits power. Many adaptive bit and power loading techniques have been investigated in the literature for enhancement of transmission rate in combination with Orthogonal Frequency Division Multiplexing (OFDM). In these systems mainly adaptive coding modulation or adaptive power was the focus but not both. In this paper, two new schemes are proposed to adapt code rate, modulation size as well as transmit power based upon channel conditions and quality of service demand by any subcarrier. Adaptive coding and modulation is done by using a Fuzzy Rule Base System (FRBS) to enhance the achievable data rate in an OFDM system with a fixed target bit error rate and fixed transmit power for each subcarrier. Moreover, for power adaptation two approaches are proposed, first the conventional water-filling algorithm and in second technique Genetic Algorithm is used to choose the optimum power vector. Both of these schemes are tuned in conjunction with FRBS. Moreover, the value of constant K for water-filling algorithm is calculated analytically. Simulation results show that water-filling performs algorithm better than flat power distribution while Genetic Algorithm assisted adaptive power outperforms both fixed and water-filling …