无线系统中信息与功率联合传输技术的研究

发布时间：2018-09-19 13:47

【摘要】：移动互联网和物联网的蓬勃发展,为无线通信产业提供了巨大机遇,尤其是以无线传感器网络为代表的短距离通信,在智能城市、智能家居和智能交通等新型应用领域具有广阔的发展前景。无线传感器网络往往能量受限,而且传感器一般安置在不可触及的环境中,当传感器网络的电池能量耗竭时,传感器网络的寿命也随之终结。通过无线功率传输进行能量收获是解决此类无线网络能量续航的潜在方案。因为电磁波既可以作为信息的载体进行无线信息传输,又可以作为能量的载体进行无线功率传输,从而可以实现无线信息与功率联合传输(SWIPT)。本文总体目标是设计无线信息与功率联合传输的整体架构,重点研究无线信息与功率联合传输的容量最优化算法和能效最优化算法。本文主体第一部分介绍了以无线传感器网络为代表的短距离通信的无线信息与功率联合传输架构设计。基于窄带MISO单链路研究场景,建立了系统模型；推导了无线信息与功率联合传输的理论性能上界；介绍了接收机架构设计,并对比分析了时分转换接收机和功率分裂接收机、分离式接收机和集成式接收机的基本结构。第二部分研究了无线信息与功率联合传输容量最优化问题。首先,基于窄带MISO单链路研究场景,以功率分裂分离式接收机为基础,建立了最小能量收获需求约束的容量最优化数学模型。然后,基于连续功率分裂因子,通过拉格朗日对偶法求解该最优化问题并推导闭式解；基于离散功率分裂因子,通过穷举法求解该问题并给出具体算法。最后,通过仿真分析了算法可行性和系统性能,并对相关影响因素进行讨论。仿真结果表明,在15KHz带宽、2.4GHz发送频率和43dBm发送功率下,传输距离为1-2m,满足某些短距离通信要求,同时满足百Kbps级别的中速数据传输需求。第三部分研究了无线信息与功率联合传输能效最优化问题。首先,仍然以窄带MISO为研究场景,以功率分裂分离式接收机为基础,基于能效的概念建立了最小能量收获需求约束和最低QoS需求约束下的能效最优化数学模型。然后,结合分式规划理论、离散一维搜索和凸优化理论求解该最优化问题,并给出了具体的迭代求解算法。最后,通过仿真分析了算法可行性和系统性能,并对相关影响因素进行讨论。仿真结果表明,在满足最小能量收获需求和最低QoS需求的基础上,能效最优化算法较容量最优化算法的系统能效有显著提升。
[Abstract]:With the rapid development of mobile Internet and Internet of things, there are great opportunities for wireless communication industry, especially short distance communication, represented by wireless sensor networks, in intelligent cities. Intelligent home and intelligent transportation and other new applications have broad prospects for development. Wireless sensor networks (WSN) often have limited energy, and the sensors are usually placed in an unreachable environment. When the battery energy of WSN is exhausted, the lifetime of WSN also ends. Energy gain through wireless power transmission is a potential solution for such wireless networks. Because electromagnetic wave can be used not only as the carrier of information for wireless information transmission, but also as the carrier of energy for wireless power transmission, thus realizing the joint transmission of wireless information and power (SWIPT). The overall goal of this paper is to design the overall framework of wireless information and power joint transmission, focusing on the capacity optimization algorithm and energy efficiency optimization algorithm of wireless information and power joint transmission. The first part of this paper introduces the wireless information and power joint transmission architecture of short distance communication represented by wireless sensor network. Based on the research scene of narrow band MISO single link, the system model is established, the theoretical performance upper bound of wireless information and power joint transmission is derived, the architecture design of receiver is introduced, and the time division conversion receiver and power splitting receiver are compared and analyzed. The basic structure of separate receiver and integrated receiver. In the second part, the joint transmission capacity optimization of wireless information and power is studied. Firstly, based on the research scene of narrow band MISO single link, a capacity optimization model with minimum energy harvesting requirement constraints is established based on the split power receiver. Then, based on the continuous power splitting factor, the Lagrangian dual method is used to solve the optimization problem and the closed solution is derived. Based on the discrete power splitting factor, the exhaustive method is used to solve the problem and the specific algorithm is given. Finally, the feasibility and system performance of the algorithm are analyzed by simulation, and the related factors are discussed. The simulation results show that under the 15KHz bandwidth of 2.4GHz transmission frequency and 43dBm transmission power, the transmission distance is 1-2m, which can meet some requirements of short-range communication, and meet the requirements of mid-speed data transmission of 100 Kbps level at the same time. In the third part, the optimization of energy efficiency of wireless information and power transmission is studied. Firstly, based on the concept of energy efficiency, a mathematical model of energy efficiency optimization under minimum energy gain requirement constraint and minimum QoS requirement constraint is established based on the narrowband MISO research scenario and the power split receiver. Then, combined with fractional programming theory, discrete one-dimensional search and convex optimization theory are used to solve the optimization problem, and a specific iterative algorithm is given. Finally, the feasibility and system performance of the algorithm are analyzed by simulation, and the related factors are discussed. The simulation results show that the energy efficiency optimization algorithm is more efficient than the capacity optimization algorithm on the basis of satisfying the minimum energy harvesting requirement and the minimum QoS requirement.
【学位授予单位】：北京邮电大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TN92

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