Spectrum Decision-Making in Collaborative Cognitive Radio Networks

Abstract

Spectral decision making is a function of the cognitive cycle. It aims to select spectral opportunities within a set of finite possibilities. Decision-making methodologies, based on collaborative information exchanges, are used to improve the selection process. For collaborative decision making to be efficient, decisions need to be analyzed based on the amount of information. Using little data can produce inefficient decisions, and taking a lot of data can result in high computational costs and delays. This document presents three contributions: the incorporation of a collaborative strategy for decision making, the implementation of real data, and the analysis of the amount of information through the number of failed handoffs. The collaborative model acts as a two-way information node, the information it coordinates corresponds to the Global System for Mobile Communications (GSM) band, and the amount of information to be shared is selected according to five levels of collaboration: 10%, 20%, 50%, 80%, and 100%, in which each percentage represents the total number of users that will be part of the process. The decision-making process is carried out by using two multi-criteria techniques: Feedback Fuzzy Analytical Hierarchical Process (FFAHP) and Simple Additive Weighting (SAW). The results are presented in two comparative analyses. The first performs the analysis using the number of failed handoffs. The second quantifies the level of collaboration for the number of failed handoffs. Based on the obtained percentage ratios, the information shared, and the average of increase rates, the level of collaboration that leads to efficient results is determined to be between 20% and 50% for the given number of failed handoffs.