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Density evolution for low-density parity-check codes under max-log-map decoding

ELECTRONICS LETTERS 2001年第18期37卷 1125-1126页

作者： Wei, X Akansu, AN New Jersey Inst Technol ECE Dept Newark NJ 07102 USA

A density evolution procedure for low-density parity-check (LDPC) codes under max-log-map decoding is presented. Using this technique. the precise convergence threshold for LDPC code could be easily derived.

关键词： convergence LDPC code density evolution error correction codes max-log-map decoding decoding low-density parity-check codes convergence threshold

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Theoretical analysis of bit-error probability for max-log-map decoding

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IEEE TRANSACTIONS ON INFORMATION THEORY 2007年第5期53卷 1935-1939页

作者： Yoshikawa, Hideki Suzuka Natl Coll Technol Suzuka 5100294 Japan

In this correspondence, an analytical technique for bit-error probability of 2-state convolutional code with max-log-maximum a posteriori probability (map) decoding is presented. This technique employs an iterative calculation of the probability density function (pdf) of the state metric per one transition, and gives the exact the bit-error probability for the overall signal-to-noise ratio (SNR).

关键词： bit-error probability exact analysis maximum a posteriori probability (map) decoding max-log-map decoding

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Theoretical Analysis of Bit Error Probability for 4-State Convolutional Code with max-log map decoding

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2008年第10期E91A卷 2877-2880页

作者： Yoshikawa, Hideki Tohoku Gakuin Univ Fac Engn Tagajo Miyagi 9858537 Japan

In this letter, a theoretical analysis of bit error probability for 4-state convolutional code with max-log-maximum a posteriori probability (map) decoding is presented. This technique employs ail iterative calculation of probability density function of the state metric per one transition, and gives the exact bit error probability for all signal-to-noise power ratio.

关键词： maximum a posteriori probability (map) decoding max-log-map decoding bit error probability exact analysis

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Further Results on the Equivalence Between SOVA and max-log-map decodings

Further Results on the Equivalence Between SOVA and Max-Log-...

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2000 International Conference on Communication Technology(WCC2000·ICCT2000)

作者： Ling Cong Cui Long Wu Xiaofu National Mobile Communications Research Laboratory Southeast University Institute of Communications Engineering

ISBN: (纸本)0780363949

Turbo codes are preferred for high rate data services in the third generation mobile communication system *** low decoding delay and low complexity iterative decoding is of paramount importance. The modified soft output Viterbi algorithm(SOVA) and the max-log-maximum a posteriori(map) algorithm are such decoding *** equivalence of modified SOVA and max-log-map decodings has been proven on the assumption of no a priori information and infinite decoding *** the a priori information has to be updated continuously in iterative decoding,we prove their equivalence when there exits a priori information in this *** further demonstrate the equivalence between the sliding window(SW) max-log-map algorithm and the modified SOVA for finite decoding depth.

关键词： SOVA map decoding max-log-map decoding SW-max-log-map decoding

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On Blind Recognition of Channel Codes Within a Candidate Set

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IEEE COMMUNICATIONS LETTERS 2016年第4期20卷 736-739页

作者： Yu, Peidong Peng, Hua Li, Jing Zhengzhou Inst Informat Sci & Technol Dept Signal Anal & Proc Zhengzhou 450002 Peoples R China

Existing schemes for blind recognition of channel codes make use of the average log-likelihood ratio (LLR) of each code's parity checks. There are difficulties in setting necessary thresholds and in theoretical analysis of the method. This letter proposes to use the average likelihood difference (LD) of the parity checks. The computational complexity is reduced while the recognition performance is kept comparable to that of the LLR method. Moreover, an optimum decoding-based blind recognition is also described. Simulations show that, for rate 1/2 convolutional codes, this new method notably improves the performance.

关键词： Blind recognition channel code parity check log-likelihood ratio (LLR) max-log-map decoding

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Parallel decoding of Turbo Codes 10th

Parallel Decoding of Turbo Codes

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10th International Conference on ICT Innovations (ICT Innovations) - Engineering and Life Sciences

作者： Spasov, Dejan Fac Comp Sci & Engn Skopje North Macedonia

ISBN: (纸本)9783030008253;9783030008246

Given a turbo code generated by parallelly concatenated recursive systematic convolutional encoders, the turbo decoder comprises map decoders coupled in a serial connection, where each map decoder decodes a recursive systematic convolutional code. We propose a turbo decoding algorithm that, on a logical level of abstraction, is made of several turbo decoders working in parallel. Each turbo decoder is initialized with different recursive convolutional code. Practical implementation of the proposed algorithm may be achieved with a single turbo decoder, where map decoders are working concurrently.

关键词： Turbo codes map decoding max-log-map decoding Turbo decoding Convolutional codes

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Simplified recursion units for max-log-map: New trade-offs through variants of Local-SOVA 11

Simplified recursion units for Max-Log-MAP: New trade-offs t...

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11th International Symposium on Topics in Coding (ISTC)

作者： Klaimi, Rami Weithoffer, Stefan Nour, Charbel Abdel Douillard, Catherine IMT Atlantique Lab STICC UMR CNRS 6285 F-29238 Brest France

ISBN: (纸本)9781665409438

The log-domain BCJR algorithm is broadly used in iterative decoding processes. However, the serial nature of the recursive state metric calculations is a limiting factor for throughput increase. A possible solution resorts to high-radix decoding, which involves decoding several successive symbols at once. Despite several studies aiming at reducing its complexity, high-radix processing remains the most computationally intensive part of the decoder when targeting very high throughput. In this work, we propose a reformulation specifically targeting the complexity reduction of the recursive calculation units by either limiting the required number of operations or by selectively removing unnecessary ones. We report a complexity reduction of the add-compare-select units in the order of 50% compared to the recently proposed local-SOYA algorithm. In addition, our results show that several performance/complexity trade-offs can be achieved thanks to the proposed simplified variants. This represents a promising step forward in order to implement efficient very high throughput convolutional decoders.

关键词： max-log-map decoding local-SOVA algorithm low-complexity decoding high-throughput turbo decoders

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