Unlike the scenario in traditional high-order QAM signals, viterbi and viterbi (V&V) algorithm becomes more powerful for carrier phase recovery (CPR) in probabilistically shaped (PS) signals. The reason relies on ...
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Unlike the scenario in traditional high-order QAM signals, viterbi and viterbi (V&V) algorithm becomes more powerful for carrier phase recovery (CPR) in probabilistically shaped (PS) signals. The reason relies on that the PS signals assign much higher probability to the innermost 4 constellation points, which are qualified for V&V algorithm. In this article, we compare the performance of V&V algorithm to that of blind phase search (BPS) algorithm for PS-64 QAM and PS-256 QAM in the aspects of window size and signal to noise ratio under the constraint of different laser linewidths. Besides, the impact of signal entropy on both algorithms is investigated. The computational complexity and running time for both algorithms are also summarized. Results show that the two algorithms perform similarly for PS-64 QAM signals when the linewidth is less than 1 MHz while the running time of BPS algorithm is at least 45 times longer than that of V&V algorithm. Finally, we conduct a coherent detection based optical back-to-back experiment where the laser linewidths of both transmitter laser and local oscillator are 100 kHz. For PS-64 QAM, both V&V and BPS algorithms show negligible penalty compared to the performance of homodyne detection, verifying the feasibility of applying V&V algorithm in the CPR of PS-64 QAM.
Recently, two near-optimal decoding algorithms [Shao, R.Y., Lin, S., and Fossorier, M.P.C., 2003. Two decoding algorithms for tailbiting codes. IEEE transactions on communications, 51(10), 1658-1665;Krishnan, K.M. and...
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Recently, two near-optimal decoding algorithms [Shao, R.Y., Lin, S., and Fossorier, M.P.C., 2003. Two decoding algorithms for tailbiting codes. IEEE transactions on communications, 51(10), 1658-1665;Krishnan, K.M. and Shankar, P., 2006. Approximate linear time ML decoding on tail-biting trellises in two rounds. In IEEE international symposium on information theory, Seattle, WA, USA, pp. 2245-2249] have been proposed for convolutional tail-biting codes. Both algorithms iterate the viterbi algorithm twice, but use different metrics in the second iteration. Simulations showed that the latter algorithm (Krishnan and Shankar 2006) improved on the earlier one (Shao et al. 2003) in word error rates at the price of additional storage consumption. In this work, we prove that with a proper modification to the earlier one, the two algorithms can be made to have exactly the same survivor path at each state in the trellis, and hence are equivalent in error performance. One can consequently adopt the modified algorithm to alleviate the need for extra storage consumption of the later algorithm and, at the same time, achieve equally good performance.
Dual-dimensional parallelisation for the viterbi algorithm is exploited. That is, parallelisation of the decoding procedures within each stage of the trellis and parallelisation of the decoding procedures are expanded...
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Dual-dimensional parallelisation for the viterbi algorithm is exploited. That is, parallelisation of the decoding procedures within each stage of the trellis and parallelisation of the decoding procedures are expanded to consecutive stages without excessive path memories. Since an arbitrary number of stages can be parallelised, the trade-off between computation speed and degree of integration can be adjusted as required
The growth of information available to learning systems and the increasing complexity of learning tasks determine the need for devising algorithms that scale well with respect to all learning parameters. In the contex...
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The growth of information available to learning systems and the increasing complexity of learning tasks determine the need for devising algorithms that scale well with respect to all learning parameters. In the context of supervised sequential learning, the viterbi algorithm plays a fundamental role, by allowing the evaluation of the best (most probable) sequence of labels with a time complexity linear in the number of time events, and quadratic in the number of labels. In this paper we propose CarpeDiem, a novel algorithm allowing the evaluation of the best possible sequence of labels with a sub-quadratic time complexity. 1 We provide theoretical grounding together with solid empirical results supporting two chief facts. CarpeDiem always finds the optimal solution requiring, in most cases, only a small fraction of the time taken by the viterbi algorithm;meantime, CarpeDiem is never asymptotically worse than the viterbi algorithm, thus confirming it as a sound replacement.
The central unit of a viterbi decoder is a data-dependent feedback loop which performs an add-compare-select (ACS) operation. This nonlinear recursion is the only bottleneck for a high-speed parallel implementation. A...
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The central unit of a viterbi decoder is a data-dependent feedback loop which performs an add-compare-select (ACS) operation. This nonlinear recursion is the only bottleneck for a high-speed parallel implementation. A linear scale solution (architecture) is presented which allows the implementation of the viterbi algorithm (VA) despite the fact that it contains a data-dependent decision feedback loop. For a fixed processing speed it allows a linear speedup in the throughput rate by a linear increase in hardware complexity. A systolic array implementation is discussed for the add-compare-select unit of the VA. The implementation of the survivor memory is considered. The method for implementing the algorithm is based on its underlying finite state feature. Thus, it is possible to transfer this method to other types of algorithms which contain a data-dependent feedback loop and have a finite state property.
Prominent turbo decoding algorithms used for wireless applications are Maximum A posteriori Probability (MAP) and Soft Output viterbi algorithm (SOVA). These algorithms are known for their error correcting performance...
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Prominent turbo decoding algorithms used for wireless applications are Maximum A posteriori Probability (MAP) and Soft Output viterbi algorithm (SOVA). These algorithms are known for their error correcting performance close to Shannon's limit. MAP algorithm is intense in terms of computational complexity but gives optimal performance. SOVA algorithm gives sub-optimal performance with reduced complexity and is appropriate for real time implementation. Sub-optimal performance of SOVA is attributed to correlation effect that exists between intrinsic and extrinsic information exchanged between component turbo decoders. This paper aims at reducing the correlation effect in SOVA using Attenuation Factor (AF) approach. In this approach, two AF values are selected through MATLAB simulation that minimizes the correlation between intrinsic and extrinsic information of the two constituent decoders. Acquired AF values are analysed in Additive White Gaussian Noise (AWGN) and Rayleigh fading channel. To justify the efficiency of the proposed SOVA algorithm, EXIT chart analysis, BER analysis and complexity analysis are done. The results depict that the proposed AF approach reduces the correlation effect in SOVA with nominal BER and complexity. (C) 2020 Elsevier B.V. All rights reserved.
A viterbi algorithm is formally modified to select a set of k state sequences with top a posteriori probabilities, where k is a prespecified positive integer. A hypercube parallel algorithm is then developed along wit...
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A viterbi algorithm is formally modified to select a set of k state sequences with top a posteriori probabilities, where k is a prespecified positive integer. A hypercube parallel algorithm is then developed along with a performance evaluation.
A new coded ARQ scheme based on a generalized viterbi decoding algorithm is proposed. The scheme utilizes the error propagation, which is commonly observed in reduced-complexity decoding, as a means of error detection...
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A new coded ARQ scheme based on a generalized viterbi decoding algorithm is proposed. The scheme utilizes the error propagation, which is commonly observed in reduced-complexity decoding, as a means of error detection. It is shown that a small undetectable error probability is obtained with a small retransmission probability for a discrete memoryless channel, contrary to the conventional convolutionally coded ARQ schemes with viterbi decoding where a compromise between the retransmission probability and the undetectable error probability must be reached.
Image processing and tracking of noise line is considered in this paper. Such line could be obtained for selected application where the line is not direct, but obtained from the image content. The estimation of line a...
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viterbi algorithm is used in different scientific applications including biological sequence alignment, speech recognition, and probabilistic inference. However, high computational complexity of the viterbi algorithm ...
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viterbi algorithm is used in different scientific applications including biological sequence alignment, speech recognition, and probabilistic inference. However, high computational complexity of the viterbi algorithm is a major concern. Accelerating the viterbi algorithm is important, especially when the number of states or the length of the sequences increase significantly. In this paper, a parallel solution to improve the performance of viterbi algorithm is presented. This is achieved by formulating a matrix product based algorithm. This algorithm has been mapped to a NVIDIA graphics processing unit. The performance for different parameters and realizations are compared. The results depicts matrix product is not a viable option for small number of states. However, matrix product solution using shared memory for large number of states gains good performance when compared with the serial version.
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