Spectrum Allocation with an Improved BAS Algorithm for Cognitive Radio Networks

Abstract

Cognitive radio is a kind of intelligent radio technology that has cognitive ability to the external environment and can adapt to the external environment by adaptively adjusting the relevant working parameters according to the needs of the external environment. There are two main objectives for cognitive radio network applications: one is high-reliability communication that can be guaranteed anywhere, anytime, and the other is efficient use of spectrum resources. The paper mainly studies the optimization and application of spectrum allocation algorithms. This paper introduces the concept and function of cognitive radio, expounds the key technologies of cognitive radio, and analyzes the research status of cognitive radio at home and abroad. The graph theory shading model is discussed and the mathematical description of the model is given. By abstracting the cognitive radio network into a graph, the graph theory coloring method is used for spectrum allocation. On this basis, fairness parameters are introduced to improve the fairness of spectrum allocation. In order to obtain the maximum spectrum benefit, the new intelligent optimization algorithm - Beetle Antennae Search Algorithm (BAS) proposed in 2017 was adopted. Based on the original BAS algorithm, an Improvement Beetle Antennae Search Algorithm (I-BAS) is proposed. Through simulation, the scheme using fairness allocation and I-BAS algorithm has obvious improvement effect.