sova
- 网络软输出维特比算法;译码算法;软输出Viterbi算法;软判决维特比算法;洗面奶
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Design and Optimization of Turbo Decoder Based on SOVA Algorithm
基于SOVA算法的Turbo译码器的设计与优化
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System Emulation and Performance Analysis of Turbo Codes with SOVA Decoders
Turbo码SOVA译码器的系统仿真及性能分析
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Make use of additional bits at the end of each frame of SOVA .
SOVA算法中采用帧尾加长处理的方法充分利用了每帧最后δ位信息。
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SOVA Algorithms Under Frequency-Selective Fading Channel for OFDM Wireless System
无线OFDM系统频率选择性衰落信道下的SOVA译码算法
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Study on efficient stopping criterion of decoding for SOVA
SOVA解码的有效中止判据
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Design of an SOVA Sub-Decoder IP Core with Memory Optimization
一种节省存储量的SOVA子译码器IP核的设计
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Realization for Turbo - code Decode Based on SOVA
基于SOVA算法的Turbo码译码实现
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Two SOVA decoding algorithms in OFDM system based on BPSK modulation with fading channel were presented .
提出了两种衰落信道下基于BPSK调制OFDM系统的SOVA译码算法。
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Soft output Viterbi algorithm ( SOVA ) is applied to decoding Turbo codes .
Turbo码的译码采用软输出维特比算法(SOVA)。
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Iterative Receiving Based on SOVA Algorithm for Serially Concatenated CPM
串行级联CPM基于SOVA算法的迭代接收
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MAP Decoding Methods Derived from SOVA
等价于MAP的SOVA译码方法
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Two ways of complexity reduced decoding algorithms ( Log-MAP and SOVA ) are developed and simulated .
进一步比较和分析了两种能够减小解码算法(Log-MAP算法和SOVA)复杂度的方法并给出了他们的计算机仿真曲线。
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Under the same iterative numbers , the error rate of Log-MAP is better than SOVA .
相同迭代次数下,Log-MAP算法比SOVA算法误码率性能好;
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The result shows that the Log - MAP algorithm is more operational and time consumptive than that of SOVA algorithm .
结果表明:Log-MAP算法比SOVA算法运算量大、费时更多;
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Extent the united-decision estimated algorithm to the SOVA decoding of the Turbo code .
把联合判决估计算法推广到Turbo码的SOVA译码中,仿真验证了有明显的改进效果,粗略估计了改进算法对复杂性、规模和功耗的优化。
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The Modification of SOVA on Viterbi Algorithm
SOVA算法对Viterbi算法的修正
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This article focuses on the optimization of architecture for the soft output viterbi algorithm ( SOVA ) decoder of Turbo code .
分析TurboCode的软输出维特比(SOVA)译码器的结构优化方法。
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Base on SOVA algorithm , an SOVA sub-decoder IP core is designed and the function of each module is described .
在简单分析SOVA译码算法的基础上,对SOVA子译码器IP核的设计进行了整体分析;
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SOVA is more practical than MAP in the algorithms for decoding Turbo codes , because of its shorter decoding delay .
SOVA算法因其译码时延低于MAP算法已成为Turbo码的实用译码算法。
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The computer imitation results show that the new SOVA obviously improves BER performance compared with general SOVA , while decoding complexity would not increase obviously .
仿真结果表明,与传统SOVA算法相比这种全新的SOVA算法在不会明显增加译码计算量的前提下,显著地改善了译码性能。
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This paper proposes a modification of the soft output Viterbi decoding algorithm ( SOVA ) which combines convolution code with Huffman coding .
提出了一种与Huffman码相结合的卷积码软判决译码方案。
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By using the relation of neighboring data , an improved Viterbi algorithm is proposed and extended it to SOVA decoding of Turbo code in this paper .
该文利用相邻判决数据间的相互关系,提出了一种Viterbi截尾译码的改进算法,并将其应用到Turbo码的SOVA译码中。
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Thirdly , encoding and decoding principles of Turbo code and main decoding algorithms are described , as well as the simulation results of MAP and SOVA algorithm .
接着,阐述了PCCC码的编译码原理和主要的迭代译码算法,并对LOG&MAP算法和SOVA算法进行了性能仿真。
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The combination of Log MAP and SOVA avoids updating the matrices of the maximum path , and also makes a contribution to the requirement of short delay .
由于对数最大似然算法和SOVA算法的结合避免了对最大路径中每步度量的更新,该算法也对低时延要求有所贡献。
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The equivalence of the modified SOVA and Max-Log-MAP algorithm has been proven under the condition of no a priori information and infinite decoding depth .
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MAXLogMAP算法。
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Last , turbo equalization based on joint iterative equalization and decoding is investigated , the performance of MAP / MAP and MMSE / SOVA algorithms are compared .
最后,对联合迭代均衡和译码TURBO均衡器进行了研究,并对MAP/MAP和MMSE/SOVA联合算法进行了性能比较。
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This paper summarizes the Turbo decoding algorithms , including SOVA , MAP , LOG-MAP , MAX-LOG-MAP , etc , and compares the performance of these algorithms .
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。
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Especially , we present the LCB iterative stopping algorithm , the symbol-based SOVA algorithm suitable to the TTCM system , and two joint source-channel decoding algorithms .
提出了LCB迭代停止算法、适用于TTCM系统的符号级软输出维特比算法以及两种联合信源信道译码算法,探讨了新方法在图像数据传输中的应用。
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Combined with SOVA algorithm , the redundancy between the symbols after compression is utilized . Not only the symbol error rate is reduced , but also the soft information of symbols is obtained .
由SOVA算法对接收序列中的信源残留冗余进行利用,不仅减小了符号错误率,同时获得了符号值的软信息。
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This paper comparatively analyses Log-MAP and SOVA algorithms by simulation based on their principle , and points out the effect of iterations number , frame size and SNR for the capability of Turbo code .
在研究MAP,Max-Log-MAP,Log-MAP和SOVA算法原理基础上,通过仿真,对Log-MAP和SOVA算法进行了比较性分析,同时指出了迭代次数、帧长和信噪比对Turbo码性能的影响。