分布式MIMO系统能效优化算法研究

发布时间：2018-04-28 20:51

  本文选题：能效 + 分布式MIMO　； 参考：《南通大学》2015年硕士论文

【摘要】：随着移动互联网的快速发展,以宽带多媒体业务为代表的数据业务成为主流,无线接入速率越来越高,而可用的频谱资源却日益紧张。以MIMO及MIMO-OFDM技术为代表的新一代无线传输技术极大提高了无线链路性能,成为下一代移动通信系统中的关键技术。然而,通信产业的迅猛发展加剧了全球的能源消耗与环境污染。因此,绿色通信成为通信领域新的研究热点。研究分布式MIMO及分布式MIMO-OFDM系统的能效优化问题。在深入分析分布式MIMO及分布式MIMO-OFDM系统架构基础上,以提高系统能效为目的,围绕一维资源分配技术中的天线选择技术以及联合资源分配技术中的联合天线选择与功率分配技术展开研究。主要工作如下:(1)根据分布式MIMO系统的结构特点,提出一种基于大尺度衰落信息的分簇选择算法。该算法通过采用分簇选择的策略有效缩小待选天线范围,并且用迭代算法更新参数。仿真结果表明,该算法在有效降低计算复杂度的同时,明显改善系统能效。(2)在基于大尺度衰落信息的分簇选择算法基础上,进一步提出能效逐增算法。该算法采用多个局部最优解逼近全局最优解的方式改进系统能效。仿真分析表明,系统能效逼近最优。(3)针对分布式MIMO-OFDM系统,采用多维资源联合优化思想,在子梯度功率分配算法与快速天线选择算法基础上,提出联合快速天线选择与子梯度功率分配的次优能效优化算法。仿真结果表明,该联合算法使系统能效趋近最优。
[Abstract]:With the rapid development of mobile Internet, the data services represented by broadband multimedia services become the mainstream. The wireless access rate is getting higher and higher, but the available spectrum resources are increasingly scarce. The new generation wireless transmission technology, represented by MIMO and MIMO-OFDM technology, has greatly improved the wireless link performance and become the key technology in the next generation mobile communication system. However, the rapid development of the communications industry has increased global energy consumption and environmental pollution. Therefore, green communication has become a new research hotspot in the field of communication. The energy efficiency optimization of distributed MIMO and distributed MIMO-OFDM systems is studied. Based on the deep analysis of distributed MIMO and distributed MIMO-OFDM system architecture, the purpose of this paper is to improve system energy efficiency. The antenna selection technology in one-dimensional resource allocation technology and the joint antenna selection and power allocation technology in joint resource allocation technology are studied. The main work is as follows: (1) according to the structural characteristics of distributed MIMO system, a clustering algorithm based on large-scale fading information is proposed. The algorithm effectively reduces the range of the antenna to be selected by adopting the strategy of clustering selection, and updates the parameters with iterative algorithm. The simulation results show that the proposed algorithm not only reduces the computational complexity but also improves the energy efficiency of the system obviously. On the basis of the clustering selection algorithm based on large-scale fading information, the algorithm of increasing energy efficiency is further proposed. In this algorithm, the energy efficiency of the system is improved by using multiple local optimal solutions to approximate the global optimal solutions. Simulation results show that the energy efficiency approach to the optimal. 3) for distributed MIMO-OFDM systems, the idea of multi-dimensional resource joint optimization is adopted, based on sub-gradient power allocation algorithm and fast antenna selection algorithm. A sub-optimal energy efficiency optimization algorithm combining fast antenna selection and sub-gradient power allocation is proposed. The simulation results show that the joint algorithm approaches the optimal energy efficiency.
【学位授予单位】：南通大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TN919.3
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本文编号：1816819