基于模型的认知无线电网络频谱分配算法仿真与实现 的毕业论文
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【摘要】 本研究课题受到了国家自然科学基金《基于时域频谱利用概率分布曲线拟合的频谱检测研究》(编号:60772110),华为科技基金《基于授权用户频谱利用统计规律的认知MAC机制与算法研究》和北京邮电大学校级基金《认知无线电系统频谱检测与机会接入研究》的资助。随着飞速演进的无线通信不断朝着宽带化、无缝化、智能化的方向发展,我们不得不面对的瓶颈之一就是频谱资源的不足。目前特定通信业务固定分配专用频谱的方式,常常会出现频谱资源分配不均,甚至浪费的情形,这与当前广泛关注的频谱资源短缺问题相互矛盾。认知无线电(CR,Cognitive Radio)技术作为一种智能频谱共享技术可有效地缓解上述矛盾,它通过感知频域、时域和空域等频谱环境,自动搜寻并利用已授权频段的空闲频谱,实现不可再生频谱资源的再利用,为解决如何在有限频谱资源条件下提高频谱利用率这一无线通信难题开辟了一条新的途径。本文首先分析了课题的研究背景,简单说明了认知无线电的定义和功能,较细致地阐述了认知无线电的关键技术和典型应用;在接下来的第三、第四和第五章节中详细论述了本文完成的主要工作:本文主要就认知无线电频谱分配领域中所存在的问题做了较深入地研究,一是基于着色理论的频谱分配算法的研究,二是基于速率要求的频谱分配算法的研究,三是基于授权链路保护的频谱分配模型和算法的研究。在第三章中针对信道权值归一化问题研究了适用于实际网络的频谱分配算法。基于图着色原理给出了一种认知无线电的频谱分配模型,针对实际网络中信道存在吞吐量权值的情况,提出了加权分布式贪婪算法、加权分布式公平算法、加权分布式随机算法。经仿真验证,加权分布式贪婪算法、加权分布式公平算法和加权分布式随机算法分别获得了较高的吞吐量、公平性和复杂度性能。在第四章中研究了根据CR用户速率需求来进行频谱分配的优化算法。基于拥塞博弈给出了一种频谱分配模型,提出了一种基于传输速率要求的快速收敛的频谱分配算法。仿真分析证明,该算法能根据CR用户的传输速率要求最优化频谱分配,有较快的收敛速度。在第五章中研究了能够保护授权用户的频谱优化分配算法。基于博弈论提出了一种新型的频谱分配模型。仿真分析证明,基于该模型的迭代算法能在保护授权链路的前提下对CR链路进行最优化频谱分配;同时仿真给出了授权链路承受干扰和CR链路的信干噪比(SINR,Signal to Interference plus Noise Ratio)与比例因子的关系,为该模型应用于不同性能要求的认知无线电网络(CRN,Cognitive Radio Network)提供了参数。
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世界上没有任何东西是完美的，文章也是一样，我不敢保证我们团写出来的文章一定会让你捧上奖杯，获得名次。但这里面承载的心血和汗水不比任何写作团来的少，因为责任就是肩膀上的大山。不是我们写不出华丽清晰的文章，而是不可预定的因素太多，轻易地给您承诺说我是最好的恰恰说明了我的不成熟和轻浮。我想我简单的介绍并不能让你感觉眼前一亮，但你细细的品读定会感觉我们团靠谱务实的作风。
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