An Efficient Spectrum Decision Making Framework for Cognitive Radio Networks
Bhagyashree Anil Dere1, Sheetal Bhujade2
1Bhagyashree Anil Dere, P.G. Student, Department of E &TC Engineering, Saraswati College of Engineering, India.
2Sheetal Bhujade, Asst. Prof., Saraswati College of Engineering, Navi Mumbai, Maharashtra, India.

Manuscript received on January 02, 2015. | Revised Manuscript received on January 08, 2015. | Manuscript published on January 15, 2015. | PP: 45-48 | Volume-3 Issue-2, January 2015. | Retrieval Number: B0783013215/2014©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: This review paper is based on the spectrum decision framework for cognitive radio networks. Cognitive radio networks have been proposed as a solution to both spectrum inefficiency and spectrum scarcity problems. However, they face to a unique challenge based on the fluctuating nature of heterogeneous spectrum bands as well as the diverse service requirements of various applications. In this paper, a spectrum decision framework is proposed to determine a set of spectrum bands by considering the application requirements as well as the dynamic nature of spectrum bands. To this end, first, each spectrum is characterized by jointly considering primary user activity and spectrum sensing operations. Based on this, a minimum variance based spectrum decision is proposed for real-time applications, which minimizes the capacity variance of the decided spectrum bands subject to the capacity constraints. For best-effort applications, a maximum capacity-based spectrum decision is proposed where spectrum bands are decided to maximize the total network capacity.
Keywords: Spectrum decision framework, cognitive radio networks, spectrum scarcity, network capacity.