Research Of Resource Allocation In Cognitive Radio Based On PSO

Recently, with the rapid development of wireless communication networks is widelyused in various fields, wireless spectrum resources as non-renewable resources arebecoming scarce. Cognitive radio technology can sense the spectrum environment, in timeand frequency domains utilize the idle state of licensed users for data transmission, whichgreatly improve the utilization of spectrum resources. The reasonable allocation oftransmit power and spectrum has significance for ensuring maximize the communicationefficiency. In this paper, resource allocation of cognitive radio is studied. The researchresults of transmit power and spectrum allocation in cognitive radio system aresummarized. Considering different scenarios and constraints, the optimization algorithmof cognitive radio resource allocation based on Particle Swarm Optimization (PSO) isproposed.Considering fairness threshold, the optimal resource allocation is solved under theconstraints of user service quality and transmit power in orthogonal frequency divisionmultiple access (OFDMA)-based cognitive cooperative relay network. In this paper, theoptimization problem is mixed-integer nonlinear programming problem, because transmitallocation is continuous variable and spectrum allocation is discrete variable in cognitiveradio system. The mixed-integer nonlinear programming problem is transformed intocontinuous nonlinear programming problem by variable replacement, then which is solvedby PSO. Simulation results show that the convergence of suggested algorithm is good, andthe optimization solution of total cognitive relay network system throughput is found.Simulation experiment validate that the suggested algorithm is better than simulatedannealing algorithm, can achieve much high system throughput.PSO-based power and spectrum collaborative allocation algorithm is proposed forsolving the question of OFDMA-based cognitive radio system resource allocation. In thisalgorithm, power and spectrum allocation are optimized simultaneously in the process ofparticle iterative, and the solving process is simply with the improvement of cognitiveradio system performance. The position and velocity parameters of PSO are adjusted toaccord with the request of collaborative optimization. In the improved PSO, power and subchannel allocation state are changed at the same time in the process of iterative. Theproposed power and spectrum collaborative allocation algorithm outperform conventionalalgorithm, can achieve much high system throughput. The proposed algorithm is validatedby simulation and analysis.