基于LDPC碼的BP譯碼改進(jìn)算法研究
發(fā)布時(shí)間：2019-01-03 19:20
【摘要】：隨著時(shí)代的發(fā)展,通信在人們的日常生活中變得越來(lái)越重要。低密度奇偶校驗(yàn)碼(LDPC Codes,Low Density Parity-Check Codes)作為一類逼近Shannon限的糾錯(cuò)碼,以其優(yōu)良的性能已經(jīng)成為Turbo碼的有力競(jìng)爭(zhēng)者,成為信道編碼領(lǐng)域中的一個(gè)研究熱點(diǎn)。在LDPC碼所有譯碼算法中,BP算法是最常用的。在理論和實(shí)際中,BP算法都有優(yōu)異的性能。雖然BP算法有很多的優(yōu)勢(shì),但是其還是有很高的復(fù)雜度,在實(shí)現(xiàn)中的譯碼效率仍需提高。BP算法的復(fù)雜度主要體現(xiàn)在:在每次迭代過(guò)程中,都需要計(jì)算全部的比特和校驗(yàn)信息,所以,在每次迭代過(guò)程中,BP算法需要的計(jì)算量是相同的。但是隨著迭代次數(shù)的增加,每次迭代過(guò)程中糾正的比特?cái)?shù)卻越來(lái)越少;另外,BP算法只有在譯碼成功或者迭代次數(shù)達(dá)到規(guī)定的最大迭代次數(shù)時(shí)才停止譯碼,但是在進(jìn)行一定次數(shù)的迭代以后,一些沒(méi)有正確譯出的比特即使進(jìn)行更多的迭代也不能正確譯出。由上面提到的這些可以知道,BP算法雖然優(yōu)良,但是還有一定的改進(jìn)空間。在眾多BP算法的改進(jìn)算法中,FC算法通過(guò)在后續(xù)迭代中停止更新可靠性高的節(jié)點(diǎn),從而降低算法的復(fù)雜度;NSPC算法通過(guò)利用滿足奇偶校驗(yàn)要求的比特?cái)?shù)spcN來(lái)提前預(yù)判一個(gè)碼字是否譯碼失敗,從而來(lái)減少迭代次數(shù),以此來(lái)減少算法的計(jì)算量。但是由于FC算法的性能表現(xiàn)不好,本文首先在FC算法的基礎(chǔ)上,對(duì)其進(jìn)行了改進(jìn)。然后本文將改進(jìn)后的FC算法和NSPC算法相結(jié)合,提出了FCES算法。FCES算法既可以像FC算法一樣減少每次迭代中需要更新的節(jié)點(diǎn)數(shù)量,又可以像NSPC算法一樣減少算法的平均迭代次數(shù),另外,FCES算法的性能優(yōu)于FC算法和NSPC算法。經(jīng)過(guò)仿真和分析,我們得出:與BP算法相比,FCES算法在性能損失不大的基礎(chǔ)上,大大降低了譯碼的復(fù)雜度,提高了譯碼效率和收斂速度。
[Abstract]:With the development of the times, communication becomes more and more important in people's daily life. Low density parity check (LDPC Codes,Low Density Parity-Check Codes) codes, as a class of error-correcting codes that approach the Shannon limit, have become a powerful competitor of Turbo codes due to their excellent performance, and have become a research hotspot in the field of channel coding. Of all the decoding algorithms for LDPC codes, the BP algorithm is the most commonly used. In theory and practice, BP algorithm has excellent performance. Although the BP algorithm has many advantages, it still has a high complexity. The decoding efficiency in the implementation still needs to be improved. The complexity of the BP algorithm is mainly reflected in: in each iteration, all bits and check information need to be calculated. Therefore, in each iteration, the BP algorithm needs the same amount of computation. However, with the increase of the number of iterations, the number of bits corrected in each iteration process is less and less. In addition, the BP algorithm only stops decoding when the decoding is successful or the number of iterations reaches the specified maximum number of iterations, but after a certain number of iterations, Some bits that are not correctly translated will not be translated correctly even if more iterations are carried out. From the above mentioned, we can know that the BP algorithm is good, but there is still some room for improvement. Among the improved BP algorithms, the FC algorithm reduces the complexity of the algorithm by stopping updating the nodes with high reliability in subsequent iterations. The NSPC algorithm can reduce the number of iterations by using the bit number spcN which meets the parity check requirement to predict whether a codeword decoding fails in advance and thus to reduce the computational complexity of the algorithm. But because the performance of FC algorithm is not good, this paper improves the algorithm based on FC algorithm. Then, by combining the improved FC algorithm with the NSPC algorithm, a FCES algorithm is proposed. The FCES algorithm can not only reduce the number of nodes that need to be updated in each iteration as FC algorithm, but also reduce the average number of iterations of the algorithm like NSPC algorithm. In addition, the performance of FCES algorithm is better than that of FC algorithm and NSPC algorithm. Through simulation and analysis, we conclude that compared with BP algorithm, FCES algorithm greatly reduces the complexity of decoding and improves the efficiency and convergence speed of decoding on the basis of less performance loss.
【學(xué)位授予單位】：西安電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN911.22
[Abstract]:With the development of the times, communication becomes more and more important in people's daily life. Low density parity check (LDPC Codes,Low Density Parity-Check Codes) codes, as a class of error-correcting codes that approach the Shannon limit, have become a powerful competitor of Turbo codes due to their excellent performance, and have become a research hotspot in the field of channel coding. Of all the decoding algorithms for LDPC codes, the BP algorithm is the most commonly used. In theory and practice, BP algorithm has excellent performance. Although the BP algorithm has many advantages, it still has a high complexity. The decoding efficiency in the implementation still needs to be improved. The complexity of the BP algorithm is mainly reflected in: in each iteration, all bits and check information need to be calculated. Therefore, in each iteration, the BP algorithm needs the same amount of computation. However, with the increase of the number of iterations, the number of bits corrected in each iteration process is less and less. In addition, the BP algorithm only stops decoding when the decoding is successful or the number of iterations reaches the specified maximum number of iterations, but after a certain number of iterations, Some bits that are not correctly translated will not be translated correctly even if more iterations are carried out. From the above mentioned, we can know that the BP algorithm is good, but there is still some room for improvement. Among the improved BP algorithms, the FC algorithm reduces the complexity of the algorithm by stopping updating the nodes with high reliability in subsequent iterations. The NSPC algorithm can reduce the number of iterations by using the bit number spcN which meets the parity check requirement to predict whether a codeword decoding fails in advance and thus to reduce the computational complexity of the algorithm. But because the performance of FC algorithm is not good, this paper improves the algorithm based on FC algorithm. Then, by combining the improved FC algorithm with the NSPC algorithm, a FCES algorithm is proposed. The FCES algorithm can not only reduce the number of nodes that need to be updated in each iteration as FC algorithm, but also reduce the average number of iterations of the algorithm like NSPC algorithm. In addition, the performance of FCES algorithm is better than that of FC algorithm and NSPC algorithm. Through simulation and analysis, we conclude that compared with BP algorithm, FCES algorithm greatly reduces the complexity of decoding and improves the efficiency and convergence speed of decoding on the basis of less performance loss.
【學(xué)位授予單位】：西安電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN911.22
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1 許成謙,林雪紅,陳嘉興;一種加速Turbo碼譯碼實(shí)現(xiàn)的改進(jìn)算法的研究[J];電子學(xué)報(bào);2002年08期
2 單永杰;韓家瑋;張洪群;李安;;衛(wèi)星數(shù)據(jù)組合譯碼技術(shù)研究與實(shí)現(xiàn)[J];微計(jì)算機(jī)信息;2011年04期
3 錢t，
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