多授权认知无线电网络的合作感知调度与网络选择研究
发布时间：2018-10-23 13:48
【摘要】：认知无线电技术是解决快速发展的无线应用和低效的固定频谱分配方式之间矛盾的一种有效手段。然而主用户的抢占式优先权以及空闲信道的空时变化特性导致认知无线电网络的性能极不稳定。随着网络融合技术的发展,异构网络的普及,认知无线电网络与多个授权网络交互构成的多授权认知无线电网络逐渐成为可能,其可以给次用户提供更多的频谱资源和网络选择。针对现有感知技术在多授权认知无线电网络下存在感知精度较低现象,研究了次用户的合作感知调度问题。考虑到错误的感知结果会对次用户的接入造成影响,基于合作感知调度得到的感知精度,研究了非完美感知下次用户接入时的网络选择问题。采用连续时间马尔可夫链模型对多授权认知无线电网络进行建模与频谱特性分析。建立无穷小生成矩阵,计算了网络的稳态概率以及已知信道上次用户分布情况的条件稳态概率。针对多授权认知无线电网络下的频谱感知精度较低问题,提出了一种基于离散粒子群优化算法的合作感知调度方案。综合考虑了各个次用户感知能力的差异性、频谱使用的统计特性以及主用户的抗干扰能力等因素,分别从主用户和次用户的角度出发,建立了两个关于次用户合作感知调度方案的整数规划问题。采用离散粒子群优化算法求解所建问题,并与随机调度方案和基于信噪比的贪婪调度方案进行仿真验证。仿真结果表明,本文提出的基于离散粒子群优化算法的合作感知调度方案得到的频谱感知精度高于另外两种合作感知调度方案。基于上述得到的频谱感知精度,研究了次用户接入时的网络选择问题,并提出了一种次优化网络选择方案。分析了非完美感知下次用户的接入行为,计算了非完美感知下网络的稳态概率,次用户的阻塞率和掉话率。以最大化认知无线电网络的吞吐量为目标,建立了网络选择问题的数学模型。采用次优化网络选择算法通过降维逐态优化的方式求解目标函数,并与随机网络选择方案和基于空闲信道数的贪婪网络选择方案进行仿真对比。仿真结果表明,本文提出的次优化网络选择方案得到的吞吐量高于其他两种网络选择方案。
[Abstract]:Cognitive radio technology is an effective means to solve the contradiction between the rapid development of wireless applications and inefficient fixed spectrum allocation. However, the preemptive priority of the primary user and the space-time characteristics of the free channel lead to the extremely unstable performance of the cognitive radio network. With the development of network fusion technology and the popularity of heterogeneous networks, it is possible that cognitive radio networks interact with multiple authorized networks. It can provide secondary users with more spectrum resources and network choices. In order to solve the problem of low perception precision in multi-authorization cognitive radio networks, the cooperative perceptual scheduling problem of secondary users is studied. Considering the effect of incorrect perception results on the access of secondary users, the problem of network selection for the next user access with imperfect perception is studied based on the perception accuracy obtained by cooperative perceptual scheduling. The continuous time Markov chain model is used to model and analyze the spectrum characteristics of multiple authorized cognitive radio networks. An infinitesimal generating matrix is established to calculate the steady-state probability of the network and the conditional steady-state probability of the known last user distribution of the channel. A cooperative perceptual scheduling scheme based on discrete particle swarm optimization (DPSO) is proposed to solve the problem of low spectral sensing accuracy in multi-authorization cognitive radio networks. Considering the difference of the perception ability of the secondary users, the statistical characteristics of the spectrum usage and the anti-interference ability of the primary users, the paper sets out from the perspective of the primary users and the secondary users, respectively. Two integer programming problems for sub-user cooperative aware scheduling schemes are established. The discrete particle swarm optimization (DPSO) algorithm is used to solve the proposed problem, which is verified by simulations with the stochastic scheduling scheme and the greedy scheduling scheme based on SNR. Simulation results show that the spectrum sensing accuracy of the proposed cooperative perceptual scheduling scheme based on discrete particle swarm optimization is higher than that of the other two cooperative perceptual scheduling schemes. Based on the spectrum sensing accuracy obtained above, the problem of network selection for secondary user access is studied, and a suboptimal network selection scheme is proposed. The access behavior of the next user with imperfect perception is analyzed and the steady-state probability of the network the blocking rate and the drop rate of the secondary user are calculated. Aiming at maximizing the throughput of cognitive radio networks, a mathematical model of network selection is established. The suboptimal network selection algorithm is used to solve the objective function by reducing dimension and state optimization, and compared with the random network selection scheme and the greedy network selection scheme based on the number of idle channels. The simulation results show that the throughput of the proposed sub-optimal network selection scheme is higher than that of the other two network selection schemes.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN925
[Abstract]:Cognitive radio technology is an effective means to solve the contradiction between the rapid development of wireless applications and inefficient fixed spectrum allocation. However, the preemptive priority of the primary user and the space-time characteristics of the free channel lead to the extremely unstable performance of the cognitive radio network. With the development of network fusion technology and the popularity of heterogeneous networks, it is possible that cognitive radio networks interact with multiple authorized networks. It can provide secondary users with more spectrum resources and network choices. In order to solve the problem of low perception precision in multi-authorization cognitive radio networks, the cooperative perceptual scheduling problem of secondary users is studied. Considering the effect of incorrect perception results on the access of secondary users, the problem of network selection for the next user access with imperfect perception is studied based on the perception accuracy obtained by cooperative perceptual scheduling. The continuous time Markov chain model is used to model and analyze the spectrum characteristics of multiple authorized cognitive radio networks. An infinitesimal generating matrix is established to calculate the steady-state probability of the network and the conditional steady-state probability of the known last user distribution of the channel. A cooperative perceptual scheduling scheme based on discrete particle swarm optimization (DPSO) is proposed to solve the problem of low spectral sensing accuracy in multi-authorization cognitive radio networks. Considering the difference of the perception ability of the secondary users, the statistical characteristics of the spectrum usage and the anti-interference ability of the primary users, the paper sets out from the perspective of the primary users and the secondary users, respectively. Two integer programming problems for sub-user cooperative aware scheduling schemes are established. The discrete particle swarm optimization (DPSO) algorithm is used to solve the proposed problem, which is verified by simulations with the stochastic scheduling scheme and the greedy scheduling scheme based on SNR. Simulation results show that the spectrum sensing accuracy of the proposed cooperative perceptual scheduling scheme based on discrete particle swarm optimization is higher than that of the other two cooperative perceptual scheduling schemes. Based on the spectrum sensing accuracy obtained above, the problem of network selection for secondary user access is studied, and a suboptimal network selection scheme is proposed. The access behavior of the next user with imperfect perception is analyzed and the steady-state probability of the network the blocking rate and the drop rate of the secondary user are calculated. Aiming at maximizing the throughput of cognitive radio networks, a mathematical model of network selection is established. The suboptimal network selection algorithm is used to solve the objective function by reducing dimension and state optimization, and compared with the random network selection scheme and the greedy network selection scheme based on the number of idle channels. The simulation results show that the throughput of the proposed sub-optimal network selection scheme is higher than that of the other two network selection schemes.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN925
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相关期刊论文 前5条
1 杜白;;基于用户需求和进化博弈的认知无线电网络选择[J];郑州大学学报(工学版);2014年04期
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