认知无线电系统中基于能量收集的频谱感知优化方法研究

发布时间：2019-07-01 14:45

【摘要】：随着无线通信技术的发展,有越来越多的无线用户开始接入并使用无线频谱资源。实际中,可用频谱资源是有限的,这使得频谱资源随无线通信技术的发展变得尤为珍贵。与此同时,在已分配频段中,经研究调查发现,用户对无线频谱资源的使用率较低,这一现象与频谱资源紧张相矛盾,因此提高无线频谱资源的利用率值得关注。认知无线电技术能够有效缓解频谱紧张所带来的压力。无线用户数目的增多预示着通信系统对能量的消耗会增大,例如会增大电网能耗的压力;当使用常规电源供能如电池,由于电池自身能量是有限的,随着使用时间的增长,电池能量的匮竭,因此需要定期对设备维护,这对数目不断增多的无线用户来说变得不太现实。利用能量收集技术自给供能可以很好地解决无线用户自身能量消耗问题。本文结合认知无线电技术和能量收集技术,从提高无线频谱资源利用率层面和能量收集自给供能层面对能量收集认知无线电进行优化,实现认知用户吞吐容量的最大化。本文主要研究工作和成果如下:(1)能量收集认知用户与授权用户工作在同步状态,认知用户的帧长恒定,且帧结构为能量收集、频谱感知和数据传输三个部分。为最大化认知用户数据传输吞吐容量,对三部分时间分配进行联合优化。优化问题处理过程中,通过转化首先消除随机变量影响,而后为降低计算量提出贪婪迭代法优化求解。(2)能量收集认知用户与授权用户工作在异步状态,认知用户帧长待优化,并考虑授权用户的到达服从泊松分布。为最大化认知用户数据传输吞吐容量,对帧长和能量收集时间进行联合优化。优化过程中,采用交替迭代方法求解降低了优化运算量。并导出其吞吐容量上限。(3)能量收集认知用户与授权用户工作在同步状态,考虑频谱感知时间相对帧长很短,可以忽略其能耗。将认知用户的能量收集和消耗建模为收集或消耗一定个数“能量包”,并假设能量包的收集和消耗可以同时进行。为最大化认知用户数据传输吞吐容量,将其问题建模为关于能量门限的函数,并优化能量门限。
[Abstract]:With the development of wireless communication technology, more and more wireless users start to access and use wireless frequency spectrum resources. In practice, the available spectrum resources are limited, which makes spectral resources more valuable with the development of wireless communication technologies. At the same time, in the allocated frequency band, the research and investigation have found that the utilization rate of the wireless frequency spectrum resources by the user is low, which is in contradiction with the frequency of the frequency spectrum resource, and therefore, the utilization rate of the wireless frequency spectrum resource is paid attention. The cognitive radio technology can effectively relieve the pressure caused by the frequency spectrum. the increase in the number of wireless users is indicative of an increase in the consumption of energy by the communication system, for example, which increases the pressure of the power grid energy consumption; when a conventional power supply such as a battery is used, as the battery's own energy is limited, as the usage time increases, the battery energy is exhausted, It is therefore necessary to keep the device regularly, which is less realistic for the increasing number of wireless users. The energy consumption of the wireless user can be well solved by using the self-sufficient energy of the energy collection technology. In this paper, we combine the cognitive radio technology and the energy collection technology to optimize the energy collection and cognitive radio from the aspect of improving the utilization level of the wireless frequency spectrum resource and the energy collection self-sufficient energy supply level, and realize the maximization of the throughput capacity of the cognitive user. The main research work and results are as follows: (1) The energy collection cognitive user works in the synchronous state with the authorized user, the frame length of the cognitive user is constant, and the frame structure is three parts of energy collection, spectrum sensing and data transmission. In ord to maximize that data transmission throughput capacity of the cognitive user, the three-part time distribution is jointly optimized. In that proces of optimization problem, the influence of random variable is first eliminated by transformation, and then the greedy iteration method is put forward to optimize the solution. (2) the energy collection cognitive user works in an asynchronous state with the authorized user, the cognitive user frame is long to be optimized, and the arrival of the authorized user is considered to be subject to the Poisson distribution. In ord to maximize that data transmission throughput capacity of the cognitive user, the frame length and the energy collection time are jointly optimized. In the optimization process, the alternative iteration method is used to solve the reduction of the optimization computation. And the upper limit of the throughput capacity thereof is derived. (3) the energy collection cognitive user is in a synchronous state with the authorized user, and the energy consumption can be ignored in consideration of the short spectrum sensing time relative to the frame length. The energy collection and consumption modeling of the cognitive user is modeled as the collection or consumption of a certain number of "energy pack", and it is assumed that the collection and consumption of the energy packets can be performed at the same time. In ord to maximize that data transmission throughput capacity of the cognitive user, the problem is modeled as a function of the energy threshold and the energy threshold is optimized.
【学位授予单位】：宁波大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN925

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