The measurements of physical level parameters can become the area where decisions about cognitive radio will have the most striking effect. Field-programmable gate array (FPGA) enables real-time analyses of physical layer data to satisfy constraints like dynamic spectrum allocations, data throughput, and the coding rate. Cognitive radio will be based on simple network management techniques, using remote procedure calls. Intelligent knowledge-base system (IKBS) techniques will be used to search the parameter space in selecting changes to the system. Worldwide Interoperability for Microwave Access (WiMAX) PHY-layer functions will be managed cognitively by a FPGA-based controller to optimize the performance of the system. Instead of simple bit loading methods, the global multi-criteria optimization promise possibility to adapt more parameters with respect to several objectives. In this paper, the application of particle swarm optimization to fixed WiMAX-OFDM (Orthogonal Frequency Division Multiplexing) parameter adaptation is presented and compared with the greedy bit loading algorithm