A Spectrum Allocation Mechanism Based on HJ-DQPSO for Cognitive Radio Networks

In cognitive radio network model consisting of secondary users and primary users, in order to solve the difficult multi-objective spectrum allocation issue about maximizing network efficiency and users’ fairness to access network, this paper proposes a new discrete multi-objective combinatorial optimization mechanism—HJ-DQPSO based on Hooke Jeeves (HJ) and Quantum Particle Swarm Optimization (QPSO) algorithm. The mechanism adopts HJ algorithm to local search to prevent falling into the local optimum, and proposes a discrete QPSO algorithm to match the discrete spectrum assignment model. The mechanism has the advantages of approximating optimal solution, rapid convergence, less parameters, avoiding falling into local optimum. Compared with existing spectrum assignment algorithms, the simulation results show that according to different optimization objectives, the HJ-DQPSO optimization mechanism for multi-objective optimization can better approximate optimal solution and　converge fast. We can obtain a reasonable spectrum allocation scheme in the case of satisfying multiple optimization objectives.