基于吞吐量最大化的认知无线电频谱感知算法研究

发布时间：2018-09-13 12:03

【摘要】：传统的频谱管理机制存在资源分配不合理、频谱利用率低的弊端,已不能满足高速无线通信业务飞速增长的需求,频谱资源紧缺问题日益严重。认知无线电通过机会式接入空闲频谱能够有效提高频谱利用率和缓解频谱资源紧张现状,逐渐成为近年来的研究热点。频谱感知作为认知无线电的核心技术之一,需要快速、准确的识别空闲频谱,并在保护主用户不受干扰的前提下为次级用户提供频谱接入机会,因此,研究频谱感知算法具有十分重要的意义。本文详细介绍了认知无线电及频谱感知的研究现状与关键问题,系统分析了频谱感知的基本算法,对基于吞吐量最大化的频谱感知算法进行了深入研究,在此基础上提出了双阈值频谱感知算法和多信道频谱感知算法。针对传统能量检测使用单阈值判决不能兼顾漏检率和虚警率要求、感知时间长的问题,提出了基于吞吐量最大化的双阈值频谱感知算法。该算法引入双阈值分别控制漏检率与虚警率,通过对目标函数和约束条件的分析化简,吞吐量最大化问题转化为关于感知时间和阈值之差的联合优化问题,将联合优化问题分解为两个单变量的子优化问题,采用交替优化迭代法求解。与传统单阈值方法相比,所提算法能够在满足检测率要求的条件下降低感知虚警率,且缩短所需感知时间,从而有效提高认知用户系统的吞吐量。考虑到让单个认知用户感知全频带的方法在实际应用中会受到硬件复杂度和成本的限制,本文从实际应用角度出发,研究了多个认知用户共同完成对多条信道感知的问题,提出了基于吞吐量最大化的多信道频谱感知算法。该算法联合优化感知时间和认知用户分配,为每条信道寻找最优感知时间,在多信道间合理分配认知用户资源,将认知用户分配问题建模为多选择背包问题,使用动态规划法求解。与传统固定相同感知时间、平均分配认知用户的方法相比,所提算法实现了在多信道频谱感知时差别对待不同信道,从而有效提高认知用户系统的吞吐量。
[Abstract]:The traditional spectrum management mechanism has the disadvantages of unreasonable resource allocation and low spectrum efficiency, which can not meet the demand of rapid growth of high-speed wireless communication services. The problem of spectrum resource shortage is becoming more and more serious. Cognitive radio can effectively improve spectrum efficiency and alleviate the current situation of spectrum resource shortage by opportunistic access to idle spectrum. It has gradually become a hot research topic in recent years. Spectrum sensing, as one of the core technologies of cognitive radio, requires fast and accurate identification of free spectrum, and provides spectrum access opportunities for secondary users on the premise of protecting primary users from interference. It is very important to study spectrum sensing algorithm. In this paper, the research status and key problems of cognitive radio and spectrum sensing are introduced in detail. The basic algorithms of spectrum sensing are systematically analyzed, and the spectrum sensing algorithm based on maximum throughput is deeply studied. Based on this, a dual threshold spectrum sensing algorithm and a multi-channel spectrum sensing algorithm are proposed. A dual-threshold spectrum sensing algorithm based on maximum throughput is proposed to solve the problem that single threshold decision can not take into account the requirements of false alarm rate and has long perceptual time in traditional energy detection. In this algorithm, double thresholds are introduced to control the false alarm rate and miss detection rate respectively. Through the analysis of the objective function and the constraint conditions, the throughput maximization problem is transformed into a joint optimization problem about the difference between the perceptual time and the threshold. The joint optimization problem is decomposed into two single variable suboptimization problems and is solved by alternating optimization iterative method. Compared with the traditional single threshold method, the proposed algorithm can reduce the false alarm rate and shorten the required sensing time under the condition that the detection rate is satisfied, thus effectively improving the throughput of the cognitive user system. Considering that the method of making a single cognitive user aware of the full frequency band will be limited by the hardware complexity and cost in practical applications, this paper studies the problem of multiple cognitive users accomplishing multi-channel perception from the perspective of practical application. A multichannel spectrum sensing algorithm based on throughput maximization is proposed. The algorithm optimizes the perceptual time and cognitive user allocation, finds the optimal perceptual time for each channel, reasonably allocates cognitive user resources among multiple channels, and models the cognitive user assignment problem as a multi-selection knapsack problem. The dynamic programming method is used to solve the problem. Compared with the traditional method of allocating cognitive users equally with the same perceptual time, the proposed algorithm can effectively improve the throughput of cognitive user systems by treating different channels differently in multi-channel spectrum sensing.
【学位授予单位】：东北大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN925

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