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本文在研究Turbo 码反向SOVA(Soft-Output ViterbiAlgorithm )译码性能的基础上,提出了一种同时利用正向和反向SOVA译码软输出信息的基于SOVA 的改进译码结构及其相应的软输出修正公式。计算机模拟结果表明,所提出的改进方案与传统的SOVA算法相比,其译码性能有明显的改善,并略优于Max-Log-MAP的性能 相似文献
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第三代移动通信系统IMT-2000的高速率业务倾向于选择Turbo码,这就要求采用低时延、低复杂度的迭代译码技术,主要是软输出Viterbi算法(SOVA)和Max-Log-MAP算法.在先验等概和无限译码深度条件下,已证明略加修改的SOVA等效于Max-Log-MAP算法.由于在迭代译码中,先验概率须不断更新,本文证明了在存在先验概率的条件下改进型SOVA与Max-Log-MAP也是等效的,并讨论了有限译码深度限制下改进型SOVA与滑动窗口Max-Log-MAP算法的等效性. 相似文献
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Fabrice Labeau 《Wireless Communications and Mobile Computing》2007,7(5):643-653
In this paper, we explore computationally efficient implementations of the soft output viterbi algorithm (SOVA) applied to Soft‐Input Soft‐Output (SISO) decoding of linear block codes. In order to simplify the trellis‐based decoding of binary block codes with SOVA, we use the technique of sectionalization of the trellis, which has been successfully applied to the simplification of the MAP and Max‐Log‐MAP algorithms. Due to the branch complexity of the sectionalized trellis, we define a generalization of a non‐binary version of SOVA. However, the computational complexity of directly applying this approach remains too high for efficient implementation; we thus introduce the concept of non‐binary SOVA (NSOVA) with propagation of bit‐level reliabilities (BLR). This new algorithm is analyzed from a computational complexity viewpoint. Both serial and parallel implementations are explored. Finally, optimal sectionalizations are derived for selected codes; since the normal SOVA decoding is a particular case of NSOVA with BLR, we show that our approach is more efficient than a bit‐level trellis by showing that, for all the codes tested, the optimal trellis is a sectionalized one. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
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SISO decoding for block codes can be carried out based on a trellis representation of the code. However, the complexity entailed
by such decoding is most often prohibitive and thus prevents practical implementation. This paper examines a new decoding
scheme based on the soft-output Viterbi algorithm (SOVA) applied to a sectionalized trellis for linear block codes. The computational
complexities of the new SOVA decoder and of the conventional SOVA decoder, based on a bit-level trellis, are theoretically
analyzed and derived for different linear block codes. These results are used to obtain optimum sectionalizations of a trellis
for SOVA. For comparisons, the optimum sectionalizations for Maximum A Posteriori (MAP) and Maximum Logarithm MAP (Max-Log-MAP)
algorithms, and their corresponding computational complexities are included. The results confirm that the new SOVA decoder
is the most computationally efficient SISO decoder, in comparisons to MAP and Max-Log-MAP algorithms. The simulation results
of the bit error rate (BER) performance, assuming binary phase -- shift keying (BPSK) and additive white Gaussian noise (AWGN)
channel, demonstrate that the performance of the new decoding scheme is not degraded. The BER performance of iterative SOVA
decoding of serially concatenated block codes shows no difference in the quality of the soft outputs of the new decoding scheme
and of the conventional SOVA. 相似文献
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It is shown that after a proper simple modification, the soft-output Viterbi algorithm (SOVA) proposed by Hagenauer and Hoeher (1989) becomes equivalent to the max-log-maximum a posteriori (MAP) decoding algorithm. Consequently, this modified SOVA allows to implement the max-log-MAP decoding algorithm by simply adjusting the conventional Viterbi algorithm. Hence, it provides an attractive solution to achieve low-complexity near-optimum soft-input soft-output decoding 相似文献
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等价于MAP的SOVA译码方法 总被引:1,自引:0,他引:1
不同于MAP(Maximum A Posteriori)算法,SOVA(Soft-Output Viterbi Algorithm)算法的软输出不是真正意义上的后验概率,很少有文献给出SOVA算法的完整数学解释。该文给出了一种完整的SOVA的数学表达形式,并从SOVA的数学表达出发推导出了两种等价于MAP,具有SOVA形式的译码方法,一种是Li等人(1995)给出的适用于连续传输的最佳软输出算法(Optimal Soft output Algorithm, OSA);后一种是对OSA算法的改进,后者可以得到与前者等价的软输出,但是降低了运算复杂度。 相似文献
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基于Turbo码编译码技术,在Rician衰落信道模型下,详细研究了Turbo码Log-MAP译码算法和SOVA译码算法在低Rician因子衰落信道下的性能,并结合调制技术对整个编译码系统进行Matlab仿真。仿真结果表明,在低Rician因子信道下,Log-MAP译码算法的性能优于SOVA译码算法。 相似文献
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Soft output Viterbi algorithm(SOVA) is a turbo decoding algorithm that is suitable for hardware implementation. But its performance is not so good as maximum a posterior probability(MAP) algorithm. So it is very important to improve its performance. The non-correlation between minimum and maximum likelihood paths in SOVA is analyzed. The metric difference of both likelihood paths is used as iterative soft information, which is not the same as the traditional SOVA. The performance of the proposed SOVA is demonstrated by the simulations. For 1024-bit frame size and 9 iterations with signal to noise ratio from 1dB to 4dB, the experimental results show that the new SOVA algorithm obtains about more 0.4dB and 0.2dB coding gains more than the traditional SOVA and Bi-SOVA algorithms at bit error rate(BER) of 1×10~ -4 , while the latency is only half of the Bi-direction SOVA decoding. 相似文献
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Two step SOVA-based decoding algorithm for tailbiting codes 总被引:1,自引:0,他引:1
《Communications Letters, IEEE》2009,13(7):510-512
In this work we propose a novel decoding algorithm for tailbiting convolutional codes and evaluate its performance over different channels. The proposed method consists on a fixed two-step Viterbi decoding of the received data. In the first step, an estimation of the most likely state is performed based on a SOVA decoding. The second step consists of a conventional Viterbi decoding that employs the state estimated in the previous step as the initial and final states of the trellis. Simulations results show a performance close to that of maximum-likelihood decoding. 相似文献
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The Viterbi algorithm (VA) is the maximum likelihood decoding algorithm for convolutionally encoded data. Improvements in the performance of a concatenated coding system that uses VA decoding (inner decoder) can be obtained when, in addition to the standard VA output, an indicator of the reliability of the VA decision is delivered to the outer stage of processing. Two different approaches of extending the VA are considered. In the first approach, the VA is extended with a soft output (SOVA) unit that calculates reliability values for each of the decoded output information symbols. In the second approach, coding gains are obtained by delivering a list of the L best estimates of the transmitted data sequence, namely the list Viterbi decoding algorithm (LVA). Our main interest is to evaluate the LVA and the SOVA in comparison with each other, determine suitable applications for both algorithms and to construct extended versions of the LVA and the SOVA with low complexity that perform the task of the other algorithm. We define a list output VA using the output symbol reliability information of the SOVA to generate a list of size L and that also has a lower complexity than the regular LVA for a long list size. We evaluate the list-SOVA in comparison to the LVA. Further, we introduce a low complexity soft symbol output viterbi algorithm that accepts the (short) list output of the LVA and calculates for each of the decoded information bits a reliability value. The complexity and the performance of the soft-LVA (LVA and soft decoding unit) is a function of the list size L. The performance of the soft-LVA and the SOVA are compared in a concatenated coding system. A new software implementation of the iterative serial version of the LVA is also included 相似文献
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SOVA算法对Viterbi算法的修正 总被引:1,自引:0,他引:1
在Viterbi算法中引入软值进行修正之后的算法称作SOVA算法(Soft Output Viterbi Algorithm)。SOVA算法在Viterbi算法的基础上,路径量度引入了比特先验信息,对每位译码比特以后验概率似然比的形式提供软输出,因而可提供更高的译码性能。特别,SOVA算法可用于级联码的迭代译码,采用Tuobo原理使不同分量码之间交换软信息,从而可显著提高这类码的纠错能力。 相似文献
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In this paper, we propose a novel and simple approach for dealing with the exaggerated extrinsic information produced by the soft-output Viterbi algorithm (SOVA). The proposed remedy is based on mathematical analysis and it involves using two attenuators, one applied to the immediate output of the SOVA and another applied to the extrinsic information before it is passed to the other decoder (assuming iterative decoding). The use of these attenuators aims at reducing the inherent strong correlation between the intrinsic information (input to the SOVA) and extrinsic information (output of the SOVA). We examine the modified SOVA (MSOVA) on additive white Gaussian noise (AWGN) and flat fading channels for parallel concatenated codes (PCCs) and serial concatenated codes (SCCs). We show that the MSOVA provides substantial performance improvements over both channels. For example, it provides improvements of about 0.8 to 1.0 dB at P/sub b/ = 10/sup -5/ in AWGN, and about 1.4 to 2.0 dB at P/sub b/ = 10/sup -5/ on fading channels. We also show that there are cases where the MSOVA is superior to the a posteriori probability (APP) algorithm. With this motivation, we extend the proposed modification to the APP algorithm with favorable results. We demonstrate that the modified APP (MAPP) provides performance improvements between 0.3 to 0.6 dB at P/sub b/ = 10/sup -5/ relative to the APP. We lastly mention that the proposed modifications, while they provide considerable performance improvements, keep the complexity of these decoders almost the same, which is remarkable. 相似文献
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The performance of parallel and serial concatenated codes on frequency-nonselective fading channels is considered. The analytical average upper bounds of the code performance over Rician channels with independent fading are derived. Furthermore, the log-likelihood ratios and extrinsic information for maximum a posteriori (MAP) probability and soft-output Viterbi algorithm (SOVA) decoding methods on fading channels are developed. The derived upper bounds are evaluated and compared to the simulated bit-error rates over independent fading channels. The performance of parallel and serial codes with MAP and SOVA iterative decoding methods, with and without channel state information, is evaluated by simulation over independent and correlated fading channels. It is shown that, on correlated fading channels, the serial concatenated codes perform better than parallel concatenated codes. Furthermore, it has been demonstrated that the SOVA decoder has almost the same performance as the MAP decoder if ideal channel state information is used on correlated Rayleigh fading channels. 相似文献
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MAP算法在Turbo码译码中的应用和研究进展 总被引:2,自引:0,他引:2
对Turbo码译码算法进行了综述,包括SOVA、MAP、LOG-MAP、MAX-LOG-MAP等算法,并对这几种算法进行了比较。同时根据近年来对Turbo码译码算法的研究,对几种新的译码算法进行了介绍和讨论。 相似文献
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The concept of concatenated codes and turbo decoding is well known and leads to a remarkably good performance in many applications. The resulting signal processing for this concept shows high complexity relative to conventional Viterbi decoding. This paper, therefore, considers an alternative concept of turbo decoding to reduce the computational complexity. In thiscase, those sections of the sequence to be decoded, where changes of bit decisions (compared to the previous iteration step) are very unlikely,are excluded from the soft-output viterbi algorithm (SOVA). This decoding is much easier to process and the loss of bit error rate (BER) performance isquite small or even negligible in comparison to conventional turbo decoding. 相似文献