高速移动MIMO-OFDMA系统资源分配算法的研究

发布时间：2018-03-31 03:16

本文选题：MIMO　切入点：OFDMA　出处：《北京交通大学》2017年硕士论文

【摘要】：MIMO和OFDMA等5G移动通信技术快速发展,正逐渐被应用于高速移动场景中,而且随着视频流等海量数据迅猛增加,高速铁路乘客对数据传输速率、网络服务质量等需求也日益增加。因此,合理进行无线资源分配将对解决高速移动通信中的频谱资源短缺和高能耗等问题具有一定的实用价值。本文充分考虑高速移动场景特殊性,研究了 OFDMA系统及高铁大规模天线OFDMA系统的资源分配问题,提出了应用于高速移动场景下的低能耗高能效的资源优化分配策略。本文的主要工作总结如下:(1)研究OFDMA系统资源分配问题。针对Shen算法的信噪比要求高、计算复杂度高的问题进行了改进,提出了一种复杂度低的速率比例公平条件下的资源分配算法,更加适用于高速移动环境下的无线通信系统。本文算法考虑了用户实际信道状况,将用户速率比例近似为用户子载波数目比例,在功率分配阶段重新推导功率分配的函数表达式,然后通过简单的线性运算计算出最优功率分配策略。仿真结果表明,与Shen算法相比,本文算法具有较低的计算复杂度和较高的系统吞吐量。(2)研究基于大规模天线的OFDMA系统的资源分配模型。首先,结合大规模天线系统的信道特点给出了系统能效的表达式。其次,对子载波、发射功率和天线等资源进行联合考虑,在保证用户公平性和最低传输速率的前提下,达到最大化系统能效的目标。(3)研究高速移动场景下大规模天线OFDMA下行系统能效资源分配问题。首先,考虑高速移动场景下信道变化特点和多普勒频移的影响,提出一种信道状态信息反馈机制,并计算了各子载波间的干扰功率。其次,在保证用户公平性和最低速率的前提下,将资源分配问题建模为最大化能效的混合整数规划问题。在子载波分配阶段,本文算法充分考虑了信道质量和载波偏移,采用了混合式子载波分配思想;在发射功率和天线分配阶段,将分数形式的目标函数转换为等效的凹函数,通过多次迭代获得最优分配策略。仿真结果显示,在高速移动场景下,本文算法具有较好的系统吞吐量性能和能效性能。
[Abstract]:With the rapid development of 5G mobile communication technology, such as MIMO and OFDMA, it is gradually used in high-speed mobile scene, and with the rapid increase of mass data such as video stream, high-speed railway passenger to data transmission rate, The demand of network service quality is also increasing day by day. The rational allocation of wireless resources will be of practical value to solve the problems of shortage of spectrum resources and high energy consumption in high-speed mobile communication. In this paper, the problem of resource allocation in OFDMA system and OFDMA system with high-speed rail antenna is studied. A resource allocation strategy with low energy consumption and high energy efficiency is proposed for high-speed mobile scenarios. The main work of this paper is summarized as follows: (1) the problem of resource allocation in OFDMA system is studied. The signal-to-noise ratio (SNR) of Shen algorithm is very high. In this paper, the problem of high computational complexity is improved, and a resource allocation algorithm with low complexity and fair rate ratio is proposed. It is more suitable for wireless communication systems in high-speed mobile environment. In this paper, the user rate ratio is approximated to the number of user subcarriers, taking into account the actual channel condition of the user. The function expression of power allocation is rededuced at the power allocation stage, and then the optimal power allocation strategy is calculated by simple linear calculation. The simulation results show that, compared with the Shen algorithm, This algorithm has lower computational complexity and higher system throughput.) the resource allocation model of OFDMA system based on large scale antenna is studied. Firstly, the expression of system energy efficiency is given according to the channel characteristics of large scale antenna system. The joint consideration of subcarrier, transmit power and antenna is given to ensure the fairness of the user and the minimum transmission rate. To achieve the goal of maximizing system energy efficiency, the problem of energy efficiency resource allocation for large-scale antenna OFDMA downlink systems in high-speed mobile scenarios is studied. Firstly, the channel variation characteristics and the influence of Doppler frequency shift in high-speed mobile scenarios are considered. A channel state information feedback mechanism is proposed, and the interference power between subcarriers is calculated. Secondly, the fairness and minimum rate of users are guaranteed. The resource allocation problem is modeled as a mixed integer programming problem to maximize energy efficiency. In the phase of subcarrier allocation, the channel quality and carrier offset are fully considered in this algorithm, and the hybrid subcarrier allocation idea is adopted. In the phase of transmit power and antenna allocation, the objective function in fractional form is converted into an equivalent concave function, and the optimal allocation strategy is obtained through multiple iterations. This algorithm has better system throughput performance and energy efficiency performance.
【学位授予单位】：北京交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN919.3

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