一种基于干扰温度限制的信道与功率联合分配新算法

A Novel Algorithm for Joint Power and Channel Allocation Based on Interference Temperature Constraints

  • 摘要: 随着无线通信业务的不断增长,频谱资源越来越紧缺,然而另一方面大量授权的无线频谱却被闲置或者利用率极低,于是认知无线电技术应运而生,已成为无线通信领域的研究热点。认知无线电的基本思想是次用户(认知用户)利用主用户(授权用户)未占用的空闲频谱进行通信,其可用无线资源是根据授权用户的频谱使用情况而动态变化的。因此,能否实现对系统可用无线资源的合理有效管理,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。论文对干扰门限分别为-90dBm、-95dBm、-100dBm、-105dBm、-110dBm时的系统归一化容量累积分布函数进行了仿真比较,发现当干扰门限越低时,本文算法的优势越明显。这是因为在干扰门限较低时,干扰温度限制是功率分配的主要制约因素,而本文的算法正是基于干扰门限进行分配的。因此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,在保证了系统的公平性效益的同时,提高了系统的归一化容量。

     

    Abstract: The spectrum resource is becoming more and more scarce with the increased variety of the wireless communications, while, on the other hand, the current licensed and fixed spectrum allocation strategy often brings low utilization of spectral resource or even unused. Right aimed on this issue that Cognitive Radio has emerged as a hot topic in wireless communication in recent years. The basic idea of Cognitive Radio is that cognitive users have the ability to determine which portions of the spectrum is available and then dynamically alter its power, frequency, modulation, coding and other parameters to efficiently utilize vacant spectrum without harmful interference with other users. The performance of the whole 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 (such as -90dBm, -95dBm, -100dBm, -105dBm and -110dBm). 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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