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一种基于干扰温度限制的信道与功率联合分配新算法

ISSN号：1003-0530
期刊名称：《信号处理》
时间：0
分类：TN929.5[电子电信—通信与信息系统;电子电信—信息与通信工程]
作者机构：[1]南京邮电大学江苏省无线通信重点实验室,江苏南京210003, [2]东南大学移动通信国家重点实验室,江苏南京210096
相关基金：国家自然科学基金（60772062）; 国家重点基础研究发展计划资助（2007CB310607）; 863项目（2009AA01Z241）; 国家科技重大专项（2011ZX03001-006-02,2009ZX03003-002）

关键词：归一化容量, 联合分配, 公平性, 认知无线电, Normalized Capacity, Joint Allocation, Fairness, Cognitive Radio

中文摘要：

能否实现对系统可用无线资源的合理有效的分配,对整个认知无线电系统性能的优劣起着决定性作用。本文提出了一种在干扰温度限制下基于公平的功率与信道联合分配算法,该算法在主用户干扰温度及次用户发射功率的双重限制下,以最大化系统容量为基本目标,实现信道与功率的联合分配,并且引入贫困线来保证各个用户信道分配的公平性。论文建立了该问题的非线性规划数学模型,给出了模型的求解方法,并进一步设计了具体分配算法及其步骤。仿真结果表明,基于干扰温度限制的公平的功率与信道联合分配算法具有良好的性能,在保证系统公平性效益的同时,提高了系统的归一化容量。

英文摘要：

The performance of the cognitive radio system depends on the effective management of available spectrum resources. So spectrum allocation is one of the most challenging and crucial problems in cognitive radio.In this paper,a joint power and channel allocation algorithm based on fairness is proposed to maximize the normalized system capacity in cognitive radio networks under the constraints of interference temperature for primary（licensed） users and the power level for each secondary（cognitive） user.The poverty line（PL） is introduced to guarantee the number of available channels for each secondary user.We introduce a nonlinear programming model for this problem as well as the solutions,and we also design the associate allocation algorithm and procedure.The performance of normalized capacity cumulative distribution function is compared with different interference threshold.The simulation results show that our algorithm performs better with lower interference threshold.That is because the interference is the main constraint of power allocation with lower interference threshold,and our algorithm is right based on interference threshold.Both the system fairness utility and the normalized capacity of the proposed joint power and channel allocation algorithm are significantly improved compared with that of the original version of joint power and channel allocation algorithm without fairness.

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