A Spectrum Decision Framework for Cognitive Radio Networks
A Spectrum Decision Framework for Cognitive Radio Networks
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DOI：
10.1109/tmc.2010.147
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发表时间：
2011-02-01
影响因子：
7.9
通讯作者：
Akyildiz, Ian F.
中科院分区：
文献类型：
--
作者：
Lee, Won-Yeol;Akyildiz, Ian F.
认知无线电网络是解决频谱低效率和频谱稀缺问题的一种方法。然而，由于异构频段的波动性以及各种应用的不同业务需求，它们面临着独特的挑战。本文提出了一种频谱决策框架，通过考虑应用需求和频谱带的动态性，确定一组频谱带。为此，首先，通过联合考虑主要用户活动和频谱感知操作来表征每个频谱。在此基础上，提出了一种基于最小方差的实时频谱决策方法，该方法在容量约束下使决策频段的容量方差最小。对于“尽力而为”的应用，提出了基于最大容量的频谱决策，即以最大网络总容量为目标来确定频谱带。此外，提出了一种动态资源管理方案，根据时变的认知无线网络容量自适应协调频谱决策。仿真结果表明，该方法在满足业务需求的同时，有效地利用了带宽。
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. Moreover, a dynamic resource management scheme is developed to coordinate the spectrum decision adaptively dependent on the time-varying cognitive radio network capacity. Simulation results show that the proposed methods provide efficient bandwidth utilization while satisfying service requirements.