本文選題：碼間干擾 + 盲均衡算法�。� 參考：《南京信息工程大學(xué)》2017年碩士論文

【摘要】：碼間干擾是通信時(shí)難以避免的問題,它會(huì)對通信質(zhì)量產(chǎn)生很大的影響,而利用盲均衡算法可以對接收到的信號(hào)進(jìn)行有效的恢復(fù),從而得到較好效果的恢復(fù)信號(hào)。實(shí)際上,傳統(tǒng)的盲均衡算法收斂速度較慢、均方誤差較大,因此本文提出了新的算法,利用DNA遺傳算法、新型DNA遺傳算法和混合蛙跳算法對盲均衡算法性能進(jìn)行優(yōu)化和改進(jìn),研究內(nèi)容主要包括以下幾個(gè)方面:1.提出了基于DNA遺傳蛙跳優(yōu)化的常模盲均衡算法。由于常模盲均衡收斂速度慢、均方誤差較大,而混合蛙跳算法具有尋優(yōu)能力強(qiáng),參數(shù)少且通用性較好的優(yōu)點(diǎn),但它容易陷入局部收斂,若將其尋優(yōu)得到的最優(yōu)青蛙個(gè)體位置向量直接作為常模盲均衡的初始權(quán)向量進(jìn)行均衡,不能得到較好的均衡結(jié)果,而DNA遺傳算法全局搜索能力強(qiáng),先用DNA遺傳算法優(yōu)化混合蛙跳算法,得到DNA遺傳蛙跳算法,該算法彌補(bǔ)了混合蛙跳算法全局搜索能力弱的缺點(diǎn),具有更強(qiáng)的尋優(yōu)能力和更快的收斂速度。先用DNA遺傳蛙跳算法搜索出最優(yōu)的青蛙個(gè)體,然后將其位置向量作為常模盲均衡的初始權(quán)向量,提出了基于DNA遺傳蛙跳優(yōu)化的常模盲均衡算法。仿真結(jié)果表明,相比于基于混合蛙跳算法優(yōu)化的常模盲均衡算法和常模盲均衡算法,該新算法在均方誤差上分別降低了 8dB和12dB,收斂速度分別提高了 200步和900步。2.提出了新型DNA遺傳蛙跳優(yōu)化的MIMO多模盲均衡算法。MIMO通信系統(tǒng)具有容量較大和頻譜利用率較高的優(yōu)點(diǎn),已成為通信領(lǐng)域中研究的熱點(diǎn)內(nèi)容,但是通信過程中仍存在碼間干擾。利用多模盲均衡的載波相位恢復(fù)特性處理MIMO系統(tǒng)中接收的信號(hào),能夠有所改善。為了進(jìn)一步提高DNA遺傳算法優(yōu)化混合蛙跳算法的性能,這里提出一種新型交叉算子和新型變異算子,能夠豐富青蛙個(gè)體的多樣性,使全局搜索能力得到進(jìn)一步提升,從而得到新型DNA遺傳蛙跳優(yōu)化的MIMO多模盲均衡算法。仿真結(jié)果表明,相比于MIMO系統(tǒng)多模盲均衡算法,該新算法在碼間干擾上降低了 3dB,收斂速度提高了 2000步。3.提出了基于新型DNA遺傳蛙跳優(yōu)化的相關(guān)MIMO信道盲均衡算法。無線通信系統(tǒng)傳輸信號(hào)的質(zhì)量直接受到信道性能影響,首先對高斯、瑞利、萊斯和相關(guān)MIMO信道下的MIMO通信系統(tǒng)的誤碼率進(jìn)行比較,比較結(jié)果發(fā)現(xiàn)在信噪比為16dB以上時(shí),相關(guān)MIMO信道誤碼率最低。仿真采用新型DNA遺傳蛙跳優(yōu)化的MIMO盲均衡算法檢驗(yàn)不同信道的性能,其中相關(guān)MIMO信道下,算法的收斂速度比在萊斯,瑞利,高斯信道下分別快了 300, 200和100步,碼間干擾上分別降低了 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.
【學(xué)位授予單位】：南京信息工程大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TN911.5;TP18

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