面向认知网络的链路初始化与频谱分配技术研究

发布时间：2018-06-20 02:13

本文选题：认知网络 + 频谱感知　；参考：《西安电子科技大学》2016年博士论文

【摘要】：在过去的二十年间,通信技术的发展突飞猛进,越来越多的新型通信产品出现在人们的日常生活之中。特别是无线网络的普及,使得人们的学习、工作,娱乐变得更加便利。同时,人们对无线频谱资源的需求也越来越高,在一些开放使用的非授权频段上,频谱资源总是“供不应求”。然而,现行的频谱分配政策采用固定的频谱划分原则,无论授权频段上用户的使用效率如何低下,非授权用户都不得使用空闲的频谱资源。在不重新划分频谱资源的情况下,为了解决频谱资源“匮乏”和固定频段利用率低下之间的矛盾,需要一种新的频谱共享技术来平衡频谱资源的使用。在这种需求的指引下,认知无线电技术应运而生。认知无线电设备的普及有利于提升频谱资源的使用效率,并解决授权频段与非授权频段使用不均的矛盾。与传统无线通信网络不同,认知网络是动态、异构的通信网络,这些特性使得将认知网络实用化面临着诸多挑战。论文针对认知网络中的协作频谱感知、次用户的链路初始化以及频谱分配等方面展开研究,提出了一系列面向认知网络关键技术的解决方案。下面,将本文的主要工作概括如下：为获得准确的频谱感知结果,对协作频谱感知方法进行研究,提出了基于可靠判决的协作频谱感知算法。首先,根据本地判决结果的可靠性随接收信噪比而提升的特点,计算使用单门限判决的信噪比分界线。在信噪比较高的情况下,为简化本地判决过程,仅用单门限进行判决。在信噪比较低的情况下,为提高判决的准确性,用双门限进行判决。如果能量累积统计量位于可信区间内,将判决结果直接输出至融合中心；如果能量累积统计量位于拟信区间内,先由最佳单门限得到本地判决结果,然后用接收信号的对数似然比对判决结果进行验证,通过验证的判决结果被发送至融合中心。为保证系统的检测性能,将以往判决经验作为现有检测结果的合并权重,得出最终的感知结果。为解决认知网络非对称模型中次用户的链路初始化问题,对发射机和接收机的信道交会方法进行研究,提出了基于认知网络非对称模型的交会算法。首先,对异步时隙通信系统进行分析。根据素数模序列的交会性,提出使不同类型基本序列长度互质的有限索数集划分方法。然后,发射机与接收机根据可用信道集自适应地定义基本序列长度。该方法可减少信道跳转序列中冗余,缩短交会时间。为提高序列的使用效率,提出使用“空白”时隙进行频谱感知以及交会的分配策略。为解决认知网络对称模型中次用户的链路初始化问题,对具有交会能力的通用信道跳转序列生成方法进行研究,提出基于认知网络对称模型的交会算法。首先,对不同跳转步长的序列交会性进行分析,然后根据跳转步长对基本序列分类。在次用户具有对等的可用信道集时,通过ID序列连接不同类型的基本序列组成跳转序列单元。ID序列的唯一、可辩性使跳转序列单元成为满足异步交会条件的基本单位。在次用户具有不对等的可用信道集时,通过改变基本序列产生参数,使交会信道在可用信道集中轮换,确保次用户在一个循环周期内发生有保证的交会。为了提高序列的使用效率,提出序列的“空白”时隙进行频谱感知以及交会的分配策略。为解决次用户配备多认知设备时的链路初始化问题,对具有交会能力的并行信道跳转序列构造方法进行研究,提出面向多认知设备的交会算法。首先,对用于多认知设备的交会模式进行分析,证明长度不同的快-慢基本序列组之间的交会性。然后,利用可用信道集直接生成并行跳转序列组。通过分析交会时间与基本序列长度以及快-慢序列分配参数之间的关系,提出基本序列优化分配策略,进一步缩短多认知设备的交会时间。为及时获得授权信道状态信息,在交会序列中加入“感知”时隙,使信道跳转序列不但能保证交会,并且还可用于周期性频谱感知。为提高频谱分配效率,提出基于拟态物理学优化的并行频谱分配算法。首先,对集中式频谱分配场景进行分析,通过定义干扰距离建立干扰图模型。以最大化网络吞吐量为目标,对分配向量的优化分配方案进行求解。由于难以获得最优的分配结果,利用拟态物理学优化方法搜索次优解。通过分解搜索空间,将分配向量分解为一组子向量,同时对所有分配子向量展开并行搜索。迭代搜索得到优化的分配结果,并将其组合生成优化解。为提高搜索效率,对群初始化方法进行改进。通过减少可行解中的随机操作提高初始群的适应度,使后续搜索从较高的“起点”开始。为提高分配的公平性,对去干扰约束操作进行改进,使所有分配维度都有平等参与信道分配的机会。为防止迭代搜索过程中发生粒子过早聚集,导致次优解陷入局部最优解,将多样性控制机制引入拟态物理学优化方法。在粒子运动过程中,对种群内粒子间的距离进行测量,用方向函数控制粒子群的“收缩”与“扩张”。
[Abstract]:In the past twenty years, the development of communication technology has developed rapidly. More and more new communication products have appeared in people's daily life. In particular, the popularity of wireless networks makes people's learning, work and entertainment more convenient. At the same time, the demand for wireless spectrum resources is becoming higher and higher, in some open use. The spectrum resource is always "short of supply" in unauthorized frequency bands. However, the current spectrum allocation policy adopts the fixed spectrum partitioning principle. The unauthorized users are not allowed to use free spectrum resources regardless of the user's inefficient use in the authorized frequency band. In order to solve the spectrum resources without remarking the frequency division spectrum resources, the spectrum resources are not reclassified. The contradiction between "lack" and the low utilization rate of fixed frequency band requires a new spectrum sharing technology to balance the use of spectrum resources. Under the guidance of this demand, cognitive radio technology emerges as the times require. The popularization of cognitive radio is beneficial to improve the efficiency of spectrum resources, and to solve the frequency and unauthorized frequency bands of authorization. Unlike traditional wireless communication networks, unlike the traditional wireless communication networks, the cognitive network is a dynamic, heterogeneous communication network. These characteristics make the application of cognitive networks facing many challenges. This paper presents a series of research on cooperative spectrum sensing, link initialization and spectrum allocation in cognitive networks. To solve the key technology of cognitive network, the main work of this paper is summarized as follows: in order to obtain accurate spectrum sensing results, the cooperative spectrum sensing method is studied, and a cooperative spectrum sensing algorithm based on reliable decision is proposed. First, the reliability of the local decision results is improved with the signal to noise ratio of the receiver. In the case of high signal-to-noise comparison, in order to simplify the local decision process, only a single threshold is used to make a decision. In the case of low signal-to-noise comparison, a two door limit is used to improve the verdict of the decision. If the energy accumulation statistic is located in the confidence interval, the decision result is direct. Output to the fusion center; if the energy accumulation statistic is located in the quasi letter interval, the local decision result is obtained by the best single threshold, then the result of the log likelihood ratio of the received signal is verified, and the verdict result is sent to the fusion center. In order to solve the link initialization problem in the asymmetric model of cognitive network, the channel rendezvous method of the transmitter and receiver is studied and the intersection algorithm based on the asymmetric model of cognitive network is proposed to solve the link initialization problem in the asymmetric model of cognitive network. According to the rendezvous of the prime module sequence, a finite cable number set division method is proposed to make each type of basic sequence length mutually qualitative. Then, the transmitter and receiver define the basic sequence length adaptively according to the available channel set. This method can reduce the redundancy and shorten the meeting time in the channel jump sequence. In order to improve the use efficiency of the sequence, the method is proposed. In order to solve the link initialization problem of the secondary users in the cognitive network symmetry model, this paper studies the generation method of the common channel jump sequence generating method with rendezvous ability, and proposes a rendezvous algorithm based on the cognitive network symmetry model. First, the sequence of different jump step length. The rendezvous is analyzed, and then the basic sequence is classified according to the jump step. When the secondary user has the equal available channel set, the.ID sequence of the jump sequence unit is composed of different types of basic sequences connected by the ID sequence. The plea makes the jump sequence unit become the basic unit to meet the condition of the different step rendezvous. In an unequal channel set, by changing the basic sequence to produce parameters, the intersection channel is rotated in the available channel, ensuring that the secondary user has a guaranteed intersection within a cycle. In order to improve the efficiency of the sequence, the "blank" time slot in the sequence is introduced into the spectrum sensing and the rendezvous allocation strategy. The problem of link initialization when the sub user is equipped with multiple cognitive devices, research on the construction method of the parallel channel jump sequence with rendezvous ability, and propose a rendezvous algorithm for multiple cognitive devices. First, the intersection mode of the multi cognitive equipment is analyzed to prove the rendezvous between the fast slow basic sequence groups with different length. Then, the parallel jump sequence group is generated directly by using the available channel set. By analyzing the relationship between the intersection time and the basic sequence length and the fast slow sequence distribution parameters, the basic sequence optimization allocation strategy is proposed to further shorten the intersection time of the multi cognitive equipment, and to get the authorized channel state information in time and join the rendezvous sequence in the rendezvous sequence. "Perception" time slot makes the channel jump sequence not only to guarantee the intersection, but also can be used for periodic spectrum sensing. In order to improve the efficiency of the spectrum distribution, a parallel spectrum allocation algorithm based on physical physics optimization is proposed. Firstly, the centralized spectrum allocation scene is analyzed, and the interference distance is established to establish an interference map model. With the goal of network throughput, the optimal allocation scheme of distribution vectors is solved. Due to the difficulty of obtaining the optimal distribution results, the optimal solution of the physical physics is used to search the suboptimal solution. By decomposing the search space, the distribution vector is decomposed into a group of subvectors, and all the sub vectors are searched in parallel. The iterative search is optimized. In order to improve the efficiency of the search, to improve the search efficiency, improve the group initialization method, improve the fitness of the initial group by reducing the random operation in the feasible solution, and make the follow-up search start from the higher "starting point". In order to improve the fairness of the allocation, the operation of the interference constraint is improved and all the allocation is made. All dimensions have equal opportunity to participate in channel allocation. In order to prevent the premature aggregation of particles in the iterative search process, the suboptimal solution falls into the local optimal solution, and the diversity control mechanism is introduced into the state physics optimization method. In the particle motion process, the distance between particles in the population is measured and the particle swarm is controlled by the direction function. "Contraction" and "expansion".
【学位授予单位】：西安电子科技大学
【学位级别】：博士
【学位授予年份】：2016
【分类号】：TN925

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