认知无线电中基于能量效率和频谱效率的资源分配

发布时间：2019-04-19 03:04

【摘要】：近年来,随着无线通信的快速发展,人们对高速率无线业务的需求越来越高。因此无线频谱资源日益短缺,能源消耗也越来越大。认知无线电技术能够很好地解决频谱利用率低的问题。在认知无线电网络中,次用户能够很好地感知周围环境并改变工作参数,从而自适应地接入频谱。同时协作通信技术的出现满足了用户对高速率业务的需求,它通过协作分集技术提高了系统的容量。未来的无线通信不仅要考虑频谱资源利用率低的问题,还要强调能量效率的绿色无线电。鉴于此,本文针对认知无线电中的频谱效率以及能量效率做了相关研究,具体内容包括:1、针对认知无线电网络,研究了基于OFDM非完美频谱感知下能量效率的资源分配。为了不将功率浪费在错误检测,通过定义一个速率损失函数引入了一个新的能效模型,优化该能效的表达式可以节省宝贵的资源,例如电池寿命等,使该能效比传统能效的增益大。在优化中对所有的子信道都进行功率约束,有两种对主用户的干扰容限:峰值干扰功率约束以及平均干扰功率约束,通过比较两种功率约束来衡量能效的性能。经过计算验证了能效和传输功率是拟凹的关系,提出了一种优化的能效资源分配算法。仿真结果表明,新的算法比传统的算法提高了能效,并且在一定的干扰功率下,基于平均干扰功率约束的能效比基于峰值干扰功率约束的能效大。2、针对认知无线电中的双向中继网络,研究了基于OFDM非完美频谱感知下频谱效率的资源分配问题。考虑了两种接入机制:机会式的频谱接入以及共享式的频谱接入。与传统的基于认知的双向中继资源分配方法不同的是,所提的算法联合优化感知时间和发射功率,从而最大化次级系统的吞吐量。在频谱感知阶段,次级系统的两个用户和中继用户联合感知主用户的存在状态,确保了感知结果的准确性。在数据传输阶段,为了有效地保护主用户,每个阶段都考虑平均干扰功率约束以及次级系统总的功率约束,在这些约束条件下,求得最优的感知时间和功率分配。最后仿真比较了两种接入机制的性能,验证了所提算法的有效性。
[Abstract]:In recent years, with the rapid development of wireless communication, the demand for high-speed wireless services becomes higher and higher. Therefore, the wireless spectrum resources are increasingly short, and the energy consumption is also increasing. Cognitive radio technology can solve the problem of low spectrum efficiency. In cognitive radio networks, secondary users are able to sense their surroundings and change their working parameters so that they can access the spectrum adaptively. At the same time, the emergence of cooperative communication technology meets the needs of users for high-speed services, and it improves the capacity of the system through cooperative diversity technology. The future wireless communication should not only consider the low efficiency of spectrum resources, but also emphasize the energy efficiency of green radio. In view of this, this paper studies the spectrum efficiency and energy efficiency of cognitive radio. The main contents are as follows: 1. For cognitive radio network, the energy efficiency allocation based on OFDM imperfect spectrum sensing is studied. In order not to waste power on error detection, a new energy efficiency model is introduced by defining a rate loss function, which can save valuable resources, such as battery life, to optimize the expression of that energy efficiency. Make the energy efficiency greater than the traditional energy efficiency gain. In the optimization, all subchannels are constrained by power, and there are two kinds of interference tolerance for primary users: peak interference power constraint and average interference power constraint. The performance of energy efficiency is measured by comparing the two power constraints. The relationship between energy efficiency and transmission power is proved to be quasi-concave, and an optimized energy efficiency resource allocation algorithm is proposed. Simulation results show that the energy efficiency of the new algorithm is higher than that of the traditional algorithm, and the energy efficiency based on the average interference power constraint is higher than that based on the peak interference power constraint under certain interference power, and the energy efficiency based on the peak interference power constraint is higher than that based on the peak interference power constraint. For two-way relay networks in cognitive radio, the problem of spectrum efficiency allocation based on OFDM imperfect spectrum sensing is studied. Two access mechanisms are considered: opportunistic spectrum access and shared spectrum access. Different from the traditional cognitive-based bi-directional relay resource allocation method, the proposed algorithm jointly optimizes the perceived time and transmit power to maximize the throughput of the secondary system. In the spectrum sensing phase, two users and relay users of the secondary system jointly sense the state of the primary user, which ensures the accuracy of the sensing results. In the data transmission phase, in order to protect the master user effectively, the average interference power constraints and the overall power constraints of the secondary system are considered in each stage. Under these constraints, the optimal perceptual time and power allocation are obtained. Finally, the performance of the two access mechanisms is compared, and the effectiveness of the proposed algorithm is verified.
【学位授予单位】：郑州大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TN925

【相似文献】