基于认知OFDM的资源分配算法研究

发布时间：2018-03-04 00:19

本文选题：认知无线电　切入点：正交频分复用　出处：《新疆大学》2017年硕士论文　论文类型：学位论文

【摘要】：移动通信的发展,这一方面可以反映出当前无线电技术的爆发式发展,人们对各种业务需求是高质量、高服务、高品质等,从而导致频谱资源无法达到需求造成紧缺。认知无线电(Cognitive Radio,CR)是一个具有智能性和灵活性的无线通信系统,能够感知外部环境进而检测周围没有被占用的空闲时段和频谱段,使用人工智能技术在系统环境复杂变换的情况下对系统参数进行自适应改变,可以实现频谱的动态共享和最佳通信性能。正交频分复用(Orthogonal Frequency Division Multiplex,OFDM)可以动态分配频谱资源,灵活选择子载波传输和功率分配,从而对频谱资源进行动态分配。认知OFDM结合了两者的优点,可满足频谱分配需求,因此基于认知OFDM进行无线频谱资源分配是当前研究的热点。本文对基于OFDM的认知无线电资源分配的算法进行了研究,介绍了认知无线和OFDM的背景、研究现状和相关技术,以及认知OFDM系统对资源分配的系统模型和经典算法。为解决认知OFDM系统中由于授权用户未能充分利用频谱资源而引起资源短缺的问题,本文提出一种基于鱼群算法的资源分配策略。根据比例公平原则分配子载波,通过人工鱼群算法对认知用户的功率进行合理分配,考虑认知用户和授权用户互不干扰,同时兼顾适应度函数作为判断功率分配的合理性,实现认知OFDM系统容量最大化。实验结果表明,该算法在认知用户对授权用户干扰小于门限值要求条件下,保证认知用户子载波和功率分配的公平性,有效提高频谱利用率,实现了系统的传输速率最大化。本文还提出了一种基于布谷鸟搜索算法的频谱资源分配策略。保证一定公平原则,通过布谷鸟搜索算法对认知用户的功率进行合理分配,满足授权用户不受干扰,同时添加适应度函数作为判断功率分配的合理性,实现认知OFDM系统的容量最大化。实验结果表明,该算法保证公平性,有效提高频谱利用率,实现了系统的传输速率最大化。同时在同样的实验环境下,对鱼群算法和布谷鸟算法进行了实验仿真,实验结果表明,布谷鸟搜索算法优于鱼群算法,实现了系统容量的最大化。
[Abstract]:The development of mobile communication, on the one hand, can reflect the explosive development of current radio technology, and people's demand for various services is high quality, high service, high quality, etc. Cognitive Radio (CR) is an intelligent and flexible wireless communication system, which can sense the external environment and detect the idle time and spectrum segment. The dynamic spectrum sharing and optimal communication performance can be realized by using artificial intelligence technology to adaptively change the system parameters when the system environment is complex. Orthogonal Frequency Division multiplexing (OFDM) can dynamically allocate spectrum resources. Flexible selection of subcarrier transmission and power allocation to dynamically allocate spectrum resources. Cognitive OFDM combines the advantages of the two, can meet the spectrum allocation needs, Therefore, cognitive OFDM based radio spectrum resource allocation is the focus of current research. In this paper, the cognitive radio resource allocation algorithm based on OFDM is studied, the background of cognitive radio and OFDM, the research status and related technologies are introduced. In order to solve the problem of resource shortage caused by authorized users' failure to make full use of spectrum resources in cognitive OFDM systems, the system models and classical algorithms for resource allocation in cognitive OFDM systems are discussed. In this paper, a resource allocation strategy based on fish swarm algorithm is proposed. According to the principle of proportional fairness, the power of cognitive users is allocated reasonably by artificial fish swarm algorithm, which considers that cognitive users and authorized users do not interfere with each other. At the same time, the fitness function is considered as the rationality of power allocation, and the capacity of cognitive OFDM system is maximized. The experimental results show that the proposed algorithm is less than the threshold when the interference of cognitive users to authorized users is less than the threshold. Ensure the fairness of subcarrier and power allocation of cognitive users, and improve the spectrum efficiency effectively. This paper also proposes a spectrum resource allocation strategy based on cuckoo search algorithm, which ensures a certain fairness principle and reasonably allocates the power of cognitive users through the cuckoo search algorithm. The capacity of cognitive OFDM system can be maximized by adding fitness function as the rationality of power allocation. Experimental results show that the proposed algorithm ensures fairness and improves spectrum efficiency effectively. In the same experimental environment, the fish swarm algorithm and the cuckoo algorithm are simulated. The experimental results show that the Cuckoo search algorithm is superior to the fish swarm algorithm. The system capacity is maximized.
【学位授予单位】：新疆大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN929.53;TN925

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