Prediction-Based Spectrum Management in Cognitive Radio Networks

Cognitive radio networks (CRNs) have been widely studied to improve spectrum utilization through a dynamic spectrum allocation scheme. However, many challenges remain and one big issue is how to provide an efficient spectrum management in a mobile environment. In this paper, we propose a new prediction-based spectrum management strategy to tackle this challenge. Both spectrum prediction and users' mobility prediction are fully considered in the proposed strategy. Combining the prediction information and cooperative sensing, a CR base station can obtain the sensing information for future location of each secondary user, so as to prearrange high-quality channels for secondary users ahead of time. In addition, we propose a new channel selection scheme when multiple channels are available simultaneously. Besides traditional decision factors, the new channel selection algorithm takes the channel's future availability obtained from spectrum prediction into account. By properly integrating the spectrum prediction, user mobility prediction, and channel selection, the new spectrum management strategy is capable of allocating the spectrum resource more efficiently. Extensive simulations are conducted and results verify that the proposed spectrum management strategy significantly improves the system performance in terms of reducing handoff times and improving user satisfactory, connection reliability, and channel utilization.

I. Introduction

Radio spectrum is the most valuable resource to implement wireless communications. With evergrowing new applications in wireless communications, the traditional static spectrum allocation scheme reveals its inherent limitation. On one hand, the limited amount of available radio spectrum can no longer meet new demands, which leads to the issue of spectrum scarcity [1]–[4] . On the other hand, according to the study of Federal Communications Commission, the utilization of allocated spectrum is relatively low, from 15% to 85% [5]. Therefore, novel paradigms are called for to improve spectrum efficiency, among which cognitive radio networks (CRN) is one promising solution that adopts the dynamic spectrum allocation strategy [6] –[9].