基于DNA遗传蛙跳算法优化的MIMO盲均衡算法研究

发布时间：2018-07-12 11:50

本文选题：码间干扰 + 盲均衡算法　；参考：《南京信息工程大学》2017年硕士论文

【摘要】：码间干扰是通信时难以避免的问题,它会对通信质量产生很大的影响,而利用盲均衡算法可以对接收到的信号进行有效的恢复,从而得到较好效果的恢复信号。实际上,传统的盲均衡算法收敛速度较慢、均方误差较大,因此本文提出了新的算法,利用DNA遗传算法、新型DNA遗传算法和混合蛙跳算法对盲均衡算法性能进行优化和改进,研究内容主要包括以下几个方面:1.提出了基于DNA遗传蛙跳优化的常模盲均衡算法。由于常模盲均衡收敛速度慢、均方误差较大,而混合蛙跳算法具有寻优能力强,参数少且通用性较好的优点,但它容易陷入局部收敛,若将其寻优得到的最优青蛙个体位置向量直接作为常模盲均衡的初始权向量进行均衡,不能得到较好的均衡结果,而DNA遗传算法全局搜索能力强,先用DNA遗传算法优化混合蛙跳算法,得到DNA遗传蛙跳算法,该算法弥补了混合蛙跳算法全局搜索能力弱的缺点,具有更强的寻优能力和更快的收敛速度。先用DNA遗传蛙跳算法搜索出最优的青蛙个体,然后将其位置向量作为常模盲均衡的初始权向量,提出了基于DNA遗传蛙跳优化的常模盲均衡算法。仿真结果表明,相比于基于混合蛙跳算法优化的常模盲均衡算法和常模盲均衡算法,该新算法在均方误差上分别降低了 8dB和12dB,收敛速度分别提高了 200步和900步。2.提出了新型DNA遗传蛙跳优化的MIMO多模盲均衡算法。MIMO通信系统具有容量较大和频谱利用率较高的优点,已成为通信领域中研究的热点内容,但是通信过程中仍存在码间干扰。利用多模盲均衡的载波相位恢复特性处理MIMO系统中接收的信号,能够有所改善。为了进一步提高DNA遗传算法优化混合蛙跳算法的性能,这里提出一种新型交叉算子和新型变异算子,能够丰富青蛙个体的多样性,使全局搜索能力得到进一步提升,从而得到新型DNA遗传蛙跳优化的MIMO多模盲均衡算法。仿真结果表明,相比于MIMO系统多模盲均衡算法,该新算法在码间干扰上降低了 3dB,收敛速度提高了 2000步。3.提出了基于新型DNA遗传蛙跳优化的相关MIMO信道盲均衡算法。无线通信系统传输信号的质量直接受到信道性能影响,首先对高斯、瑞利、莱斯和相关MIMO信道下的MIMO通信系统的误码率进行比较,比较结果发现在信噪比为16dB以上时,相关MIMO信道误码率最低。仿真采用新型DNA遗传蛙跳优化的MIMO盲均衡算法检验不同信道的性能,其中相关MIMO信道下,算法的收敛速度比在莱斯,瑞利,高斯信道下分别快了 300, 200和100步,码间干扰上分别降低了 3dB, 2.7dB和1.5dB。
[Abstract]:Inter-symbol interference (ISI) is an unavoidable problem in communication, which has a great impact on the quality of communication. Blind equalization algorithm can be used to recover the received signal effectively and obtain a better recovery signal. In fact, the convergence speed of the traditional blind equalization algorithm is slow and the mean square error is large. Therefore, a new algorithm is proposed in this paper. The performance of the blind equalization algorithm is optimized and improved by using DNA genetic algorithm, new DNA genetic algorithm and hybrid leapfrog algorithm. The research mainly includes the following aspects: 1. A constant modulus blind equalization algorithm based on DNA genetic leapfrog optimization is proposed. Because of the slow convergence speed and large mean square error of constant modulus blind equalization, the hybrid leapfrog algorithm has the advantages of strong searching ability, few parameters and good versatility, but it is easy to fall into local convergence. If the optimal individual position vector of frog is directly equalized as the initial weight vector of the blind equalization of norm, it can not get a better equilibrium result, and DNA genetic algorithm has strong global searching ability. First, DNA genetic algorithm is used to optimize the hybrid leapfrog algorithm. This algorithm makes up for the weak global search ability of the hybrid leapfrog algorithm, and has stronger optimization ability and faster convergence speed. First, the optimal frog individual is searched by DNA genetic leapfrog algorithm, then the position vector is used as the initial weight vector of constant modulus blind equalization, and a constant mode blind equalization algorithm based on DNA genetic leapfrog optimization is proposed. The simulation results show that compared with the conventional blind equalization algorithm based on hybrid leapfrog algorithm and the constant modulus blind equalization algorithm, the new algorithm reduces the mean square error by 8dB and 12dBrespectively, and improves the convergence speed by 200 step and 900 step 路2, respectively. A novel DNA genetic leapfrog optimization MIMO blind equalization algorithm is proposed. MIMO communication system has the advantages of large capacity and high spectral efficiency. It has become a hot topic in the field of communication. However, there is still inter-symbol interference in the communication process. Using the carrier phase recovery characteristic of multimode blind equalization to deal with the received signals in MIMO system can be improved. In order to further improve the performance of DNA genetic algorithm, a new crossover operator and a new mutation operator are proposed, which can enrich the diversity of frog individuals and further improve the global search ability. Thus a novel DNA genetic leapfrog optimization MIMO multimode blind equalization algorithm is obtained. The simulation results show that compared with the MIMO system multi-mode blind equalization algorithm, the new algorithm reduces the inter-symbol interference (ISI) by 3dBand improves the convergence speed by 2000 step. 3. A novel DNA genetic leapfrog optimization based blind equalization algorithm for correlated MIMO channels is proposed. The quality of transmission signal in wireless communication system is directly affected by the channel performance. Firstly, the BER of Gao Si, Rayleigh, Rice and correlated Gao Si communication systems is compared. The comparison results show that the SNR is more than 16dB. Correlated MIMO channel has the lowest bit error rate. A novel DNA-genetic leapfrog-optimized blind equalization algorithm is used to test the performance of different channels. In the correlated MIMO channel, the convergence rate of the algorithm is 300,200 and 100 steps faster than that in Rice, Rayleigh and Gao Si channels, respectively. The ISI is reduced by 3 dB, 2.7 dB and 1.5 dB respectively.
【学位授予单位】：南京信息工程大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN911.5;TP18

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