Dynamic spectrum sensing through accelerated particle swarm optimization

Abstract

In this paper, a novel optimization algorithm, called the acceleration-aided particle swarm optimization (A-APSO), is proposed for reliable dynamic spectrum sensing in cognitive radio networks. In A-APSO, the acceleration variable of the particles in the swarm is also considered in the search space of the optimization problem. We show that the proposed A-APSO based spectrum sensing technique is more efficient in terms of performance than the corresponding one based on the standard particle swarm optimization algorithm.

Intelligent cognitive spectrum collaboration: Convergence of spectrum sensing, spectrum access, and coding technology

“…To solve the problem of spectrum access in dynamic networks, many methods can implement dynamic spectrum access, including competition algorithms (such as ALOHA [46] and CSMA [47] ), reservation algorithms (such as FPRP [48] and NbIA [49] ), and the queuing algorithms (such as DLPS [50] ). With the development of evolutionary algorithms, including GA [51,52] , PSO [53] , and biological foraging algorithms [54] , researchers are increasingly trying to integrate their use in dynamic spectrum access.…”