TD-LTE基站智能规划研究

发布时间：2018-02-17 01:31

本文关键词： TD-LTE 基站规划多目标优化进化算法正交频分复用　出处：《广东工业大学》2014年硕士论文　论文类型：学位论文

【摘要】：TD-LTE是TD-SCDMA向4G的平滑演进。与第三代移动通信系统采用的码分多址技术不同的是,LTE系统采用正交频分复用(OFDM)技术为基础的多址方式。OFDM技术的基本思想是把高速数据流分散到多个相互正交的子载波上进行传输,从而使各个子载波上的符号速率大大降低,相应的符号持续时间大大加长,并且采用循环前缀的方式抵抗无线信号多径传输的时延扩展,因此特别适用于宽带通信的场景。LTE采用多天线MIMO技术以满足系统在高数据速率和高系统容量方面的需求。根据天线部署形态和实际应用情况可以选择采用发射分集、空间复用、波束赋形这3种不同的MIMO实现方案。例如：对于基站部署大间距非相关天线阵列的情况,可以采用空间复用的方案同时传输多个数据流,实现很高的数据速率；对于部署小间距相关天线阵列的基站,可以采用波束赋形技术,将天线波束指向目标用户,减少用户间干扰；而对于控制信道等需要更好地保证接收正确性的场景,发射分集是一种合理的选择。基站规划是指考虑近期和远期业务发展需要,确定网络建设的目标,以及为达到该目标所需要的基站数量、相应位置和配置。针对TD-LTE基站规划,本文提出一种快速的、高效的、智能的方法。在模型上,本文通过综合考虑4G的同频干扰、OFDM、小区边缘速率、参考信号接收功率(RSRP)和基站站址密度等,对网络建设区域进行栅格化,用一个点(测试点)来代表这一小片区域的用户的业务需求,进而建立一个以建设成本、覆盖率和容量为目标的数学模型。在网络建设前期,根据建设区域的类型选择合适的栅格距离进行栅格化,并进行候选基站的撒点。接着可以通过激活基站的配置和资源分配方法对各个测试点的RSRP进行计算,进一步可以得到网络的覆盖和容量。在算法方面,本文采用带局部搜索的多目标遗传算法进行智能求解。所设计的局部搜索能对每个解进行局部调整,不但提高了网络的覆盖性和降低了建设成本,而且大大提高了算法的收敛速度。仿真结果表明本文的模型不但能够求出以最少的建设成本来满足网络指标,而且能够求出每个建设基站的天线类型、天线挂高和小区类型；使用局部搜索后的算法速度得到明显的提高。
[Abstract]:TD-LTE is the smooth evolution of TD-SCDMA to 4G. Different from the code division multiple access (CDMA) technology used in the third generation mobile communication system, the basic idea of the multiple access mode. OFDM technology based on orthogonal frequency division multiplexing (OFDM) technology is to transfer high speed data. The stream is spread over a plurality of orthogonal subcarriers for transmission, Thus, the symbol rate on each subcarrier is greatly reduced, the corresponding symbol duration is greatly prolonged, and the cyclic prefix is used to resist the delay spread of wireless signal multipath transmission. Therefore, the multi-antenna MIMO technology is adopted to meet the demand of the system in the aspect of high data rate and high system capacity. According to the configuration of antenna deployment and the actual application situation, it can be chosen to adopt transmit diversity and space multiplexing. For example, the spatial multiplexing scheme can be used to transmit multiple data streams at the same time, which can achieve high data rate. The beamforming technique can be used for the base station with small spacing antenna array to point the antenna beam to the target user, and to reduce the interference between users, while for the control channel, the receiving accuracy can be better guaranteed. Launch diversity is a reasonable choice. Base station planning is to consider the needs of short-term and long-term business development, determine the goal of network construction, as well as the number, location and configuration of base stations needed to achieve this goal. In this paper, a fast, efficient and intelligent method is proposed for TD-LTE base station planning. In the model, by synthetically considering 4G co-frequency interference (OFDM), cell edge rate, reference signal receiving power (RSRP) and base station address density, etc. The network construction area is rasterized, a point (test point) is used to represent the business needs of the users in this small area, and a mathematical model aiming at construction cost, coverage and capacity is established. According to the type of construction area, the appropriate grid distance is selected for rasterization, and the scatter point of candidate base station is carried out. Then, the RSRP of each test point can be calculated by activating the configuration of base station and the method of resource allocation. Further, the coverage and capacity of the network can be obtained. In the aspect of algorithm, the multi-objective genetic algorithm with local search is used to solve the problem intelligently. The designed local search can adjust each solution locally, which not only improves the coverage of the network, but also reduces the construction cost. The simulation results show that the proposed model can not only satisfy the network index with the least construction cost, but also can find the antenna type, antenna hanging height and cell type of each construction base station. The speed of local search algorithm is improved obviously.
【学位授予单位】：广东工业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN929.5

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