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Truncation Error Probability In Viterbi Decoding

As Eb/N0 increases, the values of W' and k' decrease. The larger the truncation depth or the longer the decoding trellis, the better the performance, but also more computational overhead and longer delay.The goal of this paper is to investigate how It is to be noted that even if the trellis tail length is only 60+W (equivalently, the first 61 decoded bits are replaced in Step 3), the value of P3 + Study of decoding tailbiting convolutional codes. 1989, 52-56.Google Scholar13.Wang Q, Bhargava VK: An efficient maximum likelihood decoding algorithm for generalized tail biting convolutional codes including quasicyclic codes. http://u2commerce.com/truncation-error/truncation-error-example.html

Figure 4 plots the upper bounds of P4 and P1 + P2 + P3 for each decoded bit with Eb /N0 = 4 dB. In Figures 9 and 10, this problem is further complicated by code puncturing in rate-2/3 and rate-3/4 convolutional codes and unequal protection of each coded bit in high-order modulation. We conclude that if truncation depth is W ̃ and the first k ̃ - 1 decoded bits in Step 2 are replaced in Step 3 (equivalently, trellis tail After encoding, the TBCC code word is then punctured to realize the designated code rate r, where r can be one of the three possible code rates 1/2, 2/3, or 3/4. https://www.researchgate.net/publication/224731902_Truncation_Error_Probability_in_Viterbi_Decoding

Before encoding, the convolutional encoder memory is initialized with the last 6 bits of the data block being encoded. For comparison, the simulated BER for each decoded bit with truncation depth W = 100 is also plotted in the figure. These methods do not guarantee fixed number of computations.

  • It is convenient to explain the Viterbi decoding algorithm by means of a trellis dia- gram.Figure 1 illustrates an example of decoding trellis for a convolutional code with m = 2.
  • McEliece and Onyszchuk [11] studied the tradeoff between the truncation window size and performance loss for the random state strategy under both binary symmetric channels and additive white Gaussian noise (AWGN)
  • Knottenbelt+2 more authors…Fabian BrosigRead moreConference PaperAutomated extraction of architecture-level performance models of distributed component-based systemsOctober 2016Fabian BrosigNikolaus HuberSamuel KounevRead moreConference PaperS/T/A: Meta-Modeling Run-Time Adaptation in Component-Based System ArchitecturesOctober 2016Nikolaus HuberAndré van
  • Electron Lett 2000, 36: 643-645. 10.1049/el:20000517CrossRefGoogle Scholar9.Hemmati F, Costello DJ Jr: Truncation error probability in Viterbi decoding.
  • Practicing communications, electronics, and networking engineers who want to get a better grasp of the underlying concepts of convolutional coding and its applications will greatly benefit by the simple and concise
  • The truncation depth and the decoding trellis length that yield negligible performance loss are obtained for all transmission rates over the Rayleigh channel using computer simulations.

IEEE Trans Commun 1989, 37: 875-879. 10.1109/26.31187MathSciNetView ArticleGoogle ScholarShao RY, Lin S, Fossorier MPC: Two decoding algorithms for tailbiting codes. The values of W*, k*, and U* for the three code rates are obtained using a method similar to the one in [10] and are listed in Table 1. We observe that only a small fraction (less than 1/3) of the decoded bits in the first decoding round are unreliable, and thus should be replaced. J Wireless Com Network (2011) 2011: 111.

Hartmann,Giuseppe LongoNo preview available - 2014Common terms and phrasesalgebraic anticode association scheme asymptotic BCH codes block codes block length burst channel check sums code word code-book coding gain coding theory complex In order to alleviate the problem in the maximum-likelihood sequential decoding algorithm (MLSDA), we propose to directly eliminate the top path whose end node is $\Delta$-trellis-level prior to the farthest one Figure 2 Upper bounds on P 1 and P 2 . We also observe that all TBCCs require smaller truncation depth as E b /N0 increases, which agrees with the observation in the previous section.

Figure 2 plots the upper bounds of P1 and P2 and their sum versus the truncation depth W for Eb/N0 = 4 dB. Keywords WiMAX tail-biting convolutional codes circular decoding 1 IntroductionThe IEEE 802.16 defines the wireless metropolitan area network (MAN) technology that is commonly referred to as WiMAX. IEEE Trans Commun 1971, 19: 751-772. 10.1109/TCOM.1971.1090700MathSciNetView ArticleGoogle ScholarCopyright©Liu and Tsai; licensee Springer.2011 This article is published under license to BioMed Central Ltd. From (7) and (8), it follows that if the generator polynomials of convolutional codes are symmetric [10],Table 1The values of W*, k*, and U* for TBCCsCode ratedfreeW*k*U* d 4 * 1/210282046142/3634265873/454842887

We first consider the circular decoding algorithm with a very long tail length. https://books.google.com/books?id=Mg_aBwAAQBAJ&pg=PA222&lpg=PA222&dq=truncation+error+probability+in+viterbi+decoding&source=bl&ots=maaau2fxCO&sig=NmB5ho0hPC5RxxR-oftrw5GpiDc&hl=en&sa=X&ved=0ahUKEwjw_L-ck-7PAhUh9IMKHcwy It is convenient to explain the Viterbi decoding algorithm by means of a trellis diagram. For rate one-third convolutional codes, the required early-elimination window even reduces to the constraint length. As a consequence, the priority-first search decoding algorithm can considerably reduce its computation burden and memory consumption by directly eliminating a large number of paths with nearly no performance degradation.

This makes the priority-first search decoding algorithm with path elimination suitable for applications that demand low-complexity software implementation with near optimal performance. http://u2commerce.com/truncation-error/truncation-error-ppt.html The IEEE 802.16 includes two sets of standards, IEEE 802.16-2004 (802.16d) [1] for fixed WiMAX and IEEE 802.16-2005 (802.16e) [2] for mobile WiMAX. IEEE Trans Commun 1991, 39: 1023-1026. 10.1109/26.87203View ArticleGoogle ScholarCox RV, Sundberg CW: An efficient adaptive circular Viterbi algorithm for decoding generalized tailbiting convolutional codes. It is to be noted that even if the truncation length is only 60, the value of P2 + P4 is many orders of magnitude smaller than the upper bounds of

Figure 2 plots the upper bounds of P1 and P2 and their sum versus the truncation depth W for E b /N0 = 4 dB. New York 2006.Google ScholarMa HH, Wolf JK: On tail biting convolutional codes. Although carefully collected, accuracy cannot be guaranteed. his comment is here Please try the request again.

Observe that d 4 * > d free for every code rate. U.S Patent 5,369,671 1994.Google Scholar5.Chennakeshu S, Toy RL: Generalized Viterbi algorithm with tail-biting. Moreover, the values of W' and k' approach the values of W* and k* in Table 1 as E b /N0 approaches 5 dB and BER ≈ 5 × 10-7.

IEEE Trans Commun 1971, 19: 751-772. 10.1109/TCOM.1971.1090700MathSciNetCrossRefGoogle ScholarCopyright information© Liu and Tsai; licensee Springer. 2011This article is published under license to BioMed Central Ltd.

Institutional Sign In By Topic Aerospace Bioengineering Communication, Networking & Broadcasting Components, Circuits, Devices & Systems Computing & Processing Engineered Materials, Dielectrics & Plasmas Engineering Profession Fields, Waves & Electromagnetics General We show that the circular decoding algorithm with an appropriately chosen truncation depth and a fixed-length decoding trellis just a fraction longer than the original one can achieve almost the same It follows that the resulting TBCC code word with length n = L/r can be viewed as one period of the periodic convolutional code word generated by periodic data bits with This error probability is caused by both finite truncation depth and the uncertainty of the encoder's initial state.

Specifically, we propose to directly eliminate all paths whose end nodes are Δ-level prior to the farthest node among those that have been visited thus far by the priority-first search. Table 2 lists the least value of truncation depth W ̃ that yields losses within 0.05 dB of optimal ML decoding for BER ≈ 10-5. The rate-1/2 code requires a truncation depth of six to seven times the memory m, and the rate-2/3 and rate 3/4 codes require a truncation depth of ten to eleven times weblink Your cache administrator is webmaster.

Let L denote the length of a data block, and let (d0, d1,⋯, dL-1) denote the data block. U.S Patent 5,369,671 1994.Google ScholarChennakeshu S, Toy RL: Generalized Viterbi algorithm with tail-biting. A rule of thumb for the values of the truncation depth and the trellis tail length is also proposed. In other words, the degradation of decoder performance is mainly caused by finite truncation depth.

The upper bound of P4 depends both on the truncation depth W and the bit index k. Finally, we also obtain a rule of thumb for the relative values of truncation depth and trellis tail length. 2 Circular decoding algorithmIn mobile WiMAX systems, data bursts are divided into From the results, we obtain a rule of thumb for the truncation depth W and trellis tail length U . Following random coding argument, we analyze the early-elimination window $\Delta$ that results in negligible performance degradation for the MLSDA.

The results show that the circular decoding algorithm with an appropriately chosen truncation depth and a decoding trellis just a fraction longer than the original received code words can achieve almost Prentice-Hall, Englewood Cliffs, NJ, USA; 1983.Google Scholar8.Sung W: Minimum decoding trellis lengths for tail-biting convolutional codes. The third error event is caused by the uncertainty of the encoder's initial state. It is to be noted that the bit error probability is independent of the correct code word.

Authors’ Affiliations(1)Department of Electronic Engineering, National Taipei University of Technology ReferencesIEEE: IEEE Standard for Local and Metropolitan Area Networks. Upper bounds on the error probabilities induced by finite truncation depth and the uncertainty of the initial state are derived for the AWGN channel. Thus, the first few unreliable decoded bits are replaced by those decoded bits obtained in the second traverse of the circular decoding trellis.3 Upper bounds on error probabilitiesIn this section, we In this paper, we examine the performance of the circular decoding algorithm with finite truncation depth and fixed trellis length for all transmission rates in mobile WiMAX.