MIMO多小区联合传输策略研究

发布时间：2018-05-18 05:20

本文选题：MIMO技术 + 空分复用　；参考：《西安电子科技大学》2014年硕士论文

【摘要】：随着无线通信行业的飞速发展,有限的频谱资源日益成为无线通信行业发展的瓶颈,严重的影响了无线通信的发展,为了有效的解决这一矛盾,人们只能另辟蹊径,从频谱利用率着手,通过减少频谱资源浪费,采用频率复用技术和MIMO技术来大幅度提高频谱利用率。MIMO技术的思想是空分复用,即采用多根独立的发送天线发送不同的数据流以获取更高速的数据传输性能。频率复用技术也是一种非常有效的提高频谱资源利用率的方法,不过频率复用技术也会使得来自不同小区的同一频率上的信号产生相互的干扰。近年来,解决干扰问题的一个新的方法就是干扰对齐技术。干扰对齐技术是将多个干扰信号全都对齐到同一个干扰子空间中,从而大大减小干扰信号的空间纬度,提高期望信号的可用空间资源。目前已经出现了多种干扰对齐的算法,如基本干扰对齐算法、最小均方误差算法、最大信干噪比算法等。这些算法中并没有任何一个算法可以在各个信噪比条件下都获得最大的传输速率。为了能够让系统在各个信噪比条件下获得最大的传输速率,本文提出联合使用这些算法,通过穷举法找到一组能使传输速率最大的算法的组合。但是,多种算法联合使用的复杂度会随着算法数量的增加而极速增长,为了降低联合传输策略的算法复杂度,本文引入了遗传算法(GA),并且结合联合传输策略提出了的低复杂度的基于遗传算法的联合传输策略,可以在降低复杂度的同时获得非常优秀的系统性能。通过仿真验证,基于遗传算法的联合传输策略可以获得优于单一算法系统速率的传输速率,并且非常逼近采用穷举法所获得的最优的联合传输策略。
[Abstract]:With the rapid development of wireless communication industry, limited spectrum resources increasingly become the bottleneck of the development of wireless communication industry, seriously affect the development of wireless communications, in order to effectively solve this contradiction, people can only find another way. From the spectrum efficiency, by reducing the waste of spectrum resources, the idea of using frequency multiplexing technology and MIMO technology to greatly improve the spectrum efficiency .MIMO technology is space-division multiplexing. Multiple independent transmit antennas are used to transmit different data streams to achieve faster data transmission performance. Frequency multiplexing technology is also a very effective method to improve the efficiency of spectrum resources, but frequency multiplexing technology can also cause interference between signals from different cells on the same frequency. In recent years, a new method to solve the interference problem is interference alignment technology. The interference alignment technique is to align multiple interference signals into the same interference subspace, thus greatly reducing the spatial latitude of the interference signals and increasing the available space resources of the desired signals. At present, there are many kinds of interference alignment algorithms, such as the basic interference alignment algorithm, the minimum mean square error algorithm, the maximum signal-to-noise ratio algorithm and so on. None of these algorithms can obtain the maximum transmission rate under various SNR conditions. In order to obtain the maximum transmission rate under various signal-to-noise ratio conditions, this paper proposes a combination of these algorithms to find a set of algorithms which can maximize the transmission rate by exhaustive method. However, the complexity of the combined use of many algorithms will increase rapidly with the increase of the number of algorithms. In order to reduce the algorithm complexity of the joint transmission strategy, In this paper, genetic algorithm (GA) is introduced, and a low complexity joint transmission strategy based on genetic algorithm (GA) is proposed, which can reduce the complexity and achieve excellent system performance. The simulation results show that the combined transmission strategy based on genetic algorithm can obtain the transmission rate which is superior to that of the single algorithm system and is very close to the optimal joint transmission strategy obtained by exhaustive method.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN919.3

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