Browsing by Author "Wu, Ting-Yi"

Now showing 1 - 9 of 9

A Low-Complexity Maximum-Likelihood Decoder for Tail-Biting Convolutional Codes
(2018-05-01)
Han, Yunghsiang S.
;
Wu, Ting-Yi
;
Chen, Po-Ning
;
Varshney, Pramod K.
;
電機工程學系
Due to the growing interest in applying tail-biting convolutional coding techniques in real-time communication systems, fast decoding of tail-biting convolutional codes has become an important research direction. In this paper, a new maximumlikelihood decoder for tail-biting convolutional codes is proposed. It is named bidirectional priority-first search algorithm (BiPFSA) because priority-first search algorithm has been used both in forward and backward directions during decoding. Simulations involving the antipodal transmission of (2, 1, 6) and (2, 1, 12) tail-biting convolutional codes over additive white Gaussian noise channels shows that BiPFSA not only has the least average decoding complexity among the state-of-the-art decoding algorithms for tail-biting convolutional codes but can also provide a highly stable decoding complexity with respect to growing information length and code constraint length. More strikingly, at high SNR, its average decoding complexity can even approach the ideal benchmark complexity, obtained under a perfect noise-free scenario by any sequential-type decoding. This demonstrates the superiority of BiPFSA in terms of decoding efficiency.
An Efficient Tree Search Algorithm for the Free Distance of Variable-Length Error-Correcting Codes
(2018-03-01)
Huang, Chun
;
Wu, Ting-Yi
;
Chen, Po-Ning
;
Alajaji, Fady
;
Han, Yunghsiang S.
We propose an efficient tree search algorithm for determining the free distance of variable-length error-correcting codes (VLECs). A main idea behind the algorithm is to structure all pairs of code word-concatenated sequences as a tree, in which we seek the pair of sequences that determine the free distance. In order to speed up the algorithm, we establish constraints that do not compromise optimality in determining the free distance. Experimental results on VLECs algorithmically constructed for the English alphabet show that our algorithm requires a considerably smaller number of bitwise distance computations and covers a much smaller number of tree nodes than Dijkstra's algorithm operating over the pairwise distance graph while being a hundred times faster in terms of execution time.
Early-Elimination Modification for Priority-First Search Decoding
(2010-12-01)
Shieh, Shin-Lin
;
Chen, Po-Ning
;
Han, Yunghsiang S.
;
Wu, Ting-Yi
;
電機工程學系
In order to release the growing demand for computational complexity with respect to increasing information sequence length in the priority-first search decoding algorithm, a path elimination modification is proposed and also analyzed in this work. Specifically, we propose to directly eliminate all paths whose end nodes are Delta-level prior to the farthest node among those that have been visited thus far by the priority-first search. Following the argument on random coding, we then analyze the path elimination window Delta that results in a larger exponent for additional decoding error caused by path elimination than the exponent of the maximum-likelihood error performance, and hence guarantees exponentially negligible performance degradation. Our analytical results indicate that under additive white Gaussian noise (AWGN) channels, the path elimination window required for exponentially negligible performance degradation is just three times the code constraint length for rate one-half convolutional codes. It can be further reduced to 1.7-fold of the code constraint length when rate one-third convolutional codes are considered instead. Simulation results confirm these analytical window sizes. 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.
On the Construction and MAP Decoding of Optimal Variable-Length Error-Correcting Codes
(2011-01-01)
Wu, Ting-Yi
;
Chen, Po-Ning
;
Alajaji, Fady
;
Han, Yunghsiang S.
;
電子工程學系及電子研究所
In this paper, we present a novel algorithm that guarantees of finding a variable-length error-correcting code (VLEC) with minimal average codeword length for a fixed free distance d(free). We also propose a low complexity maximum a posterior (MAP) decoding algorithm for our codes under the premise that the receiver knows the number of codewords being transmitted. The resulting VLEC provides significant gains over other codes from the literature. When compared with separate source-channel tandem codes with identical d(free), such as a tandem code consisting of a Huffman source code concatenated with a (2, 1, 4) tail-biting convolutional channel code, our system has only a 0.3 dB performance loss at a bit error rate of 10(-5) while requiring significantly less decoding complexity.
On the Design of Variable-Length Error-Correcting Codes
(2013-09-01)
Wu, Ting-Yi
;
Chen, Po-Ning
;
Alajaji, Fady
;
Han, Yunghsiang S.
;
電機資訊學士班
A joint source-channel coding problem that combines the efficient compression of discrete memoryless sources with their reliable communication over memoryless channels via binary prefix-free variable-length error-correcting codes (VLECs) is considered. Under a fixed free distance constraint, a priority-first search algorithm is devised for finding an optimal VLEC with minimal average codeword length. Two variations of the priority-first-search-based code construction algorithm are also provided. The first one improves the resilience of the developed codes against channel noise by additionally considering a performance parameter B-dfree without sacrificing optimality in average codeword length. In the second variation, to accommodate a large free distance constraint as well as a large source alphabet such as the 26-symbol English data source, the VLEC construction algorithm is modified with the objective of significantly reducing its search complexity while still yielding near-optimal codes. A low-complexity sequence maximum a posteriori (MAP) decoder for all VLECs (including our constructed optimal code) is then proposed under the premise that the receiver knows the number of codewords being transmitted. Simulations show that the realized optimal and suboptimal VLECs compare favorably with existing codes in the literature in terms of coding efficiency, search complexity and error rate performance.
Plasmonic Gold Nanorods Coverage Influence on Enhancement of the Photoluminescence of Two-Dimensional MoS2 Monolayer
(2015-11-17)
Lee, Kevin C. J.
;
Chen, Yi-Huan
;
Lin, Hsiang-Yu
;
Cheng, Chia-Chin
;
Chen, Pei-Ying
The 2-D transition metal dichalcogenide (TMD) semiconductors, has received great attention due to its excellent optical and electronic properties and potential applications in field-effect transistors, light emitting and sensing devices. Recently surface plasmon enhanced photoluminescence (PL) of the weak 2-D TMD atomic layers was developed to realize the potential optoelectronic devices. However, we noticed that the enhancement would not increase monotonically with increasing of metal plasmonic objects and the emission drop after the certain coverage. This study presents the optimized PL enhancement of a monolayer MoS2 in the presence of gold (Au) nanorods. A localized surface plasmon wave of Au nanorods that generated around the monolayer MoS2 can provide resonance wavelength overlapping with that of the MoS2 gain spectrum. These spatial and spectral overlapping between the localized surface plasmon polariton waves and that from MoS2 emission drastically enhanced the light emission from the MoS2 monolayer. We gave a simple model and physical interpretations to explain the phenomena. The plasmonic Au nanostructures approach provides a valuable avenue to enhancing the emitting efficiency of the 2-D nano-materials and their devices for the future optoelectronic devices and systems.
Priority-First Search Decoding for Convolutional Tail-biting Codes
(2008)
Han, Yunghsiang S.
;
Wu, Ting-Yi
;
Pai, Hung-Ta
;
Chen, Po-Ning
;
Shieh, Shin-Lin
Due to rapid interest on the applications of convolutional tail-biting to communication systems, several suboptimal algorithms have been proposed to achieve near-optimal Word error rate (WER) performances with circular Viterbi decoding approach. Among them, the wrap-around Viterbi algorithm (WAVA) proposed in [1] is the one with least decoding complexity. Very recently, a maximum likelihood (ML) decoding algorithm has been proposed in [2]. The scheme has two phases. The Viterbi algorithm is applied to the trellis of the convolutional tail-biting code and the information obtained in the first phase is used by algorithm A*, which is performed to all subtrellises, in the second phase. In this work, a new two-phase ML decoding algorithm is proposed. From the simulation results for the. (2,1,12) convolutional tail-biting code, the proposed algorithm has 16 times less average decoding complexity in the second phase when compared to the one using algorithm A* and 15123 times less than that of the WAVA., respectively, when SNRb = 4 dB.
Reliability-Based Decoding for Convolutional Tail-biting Codes
(2010)
Wu, Ting-Yi
;
Chen, Po-Ning
;
Pai, Hung-Ta
;
Han, Yunghsiang S.
;
Shieh, Shin-Lin
In this work, we proposed a reliability-based enhancement for the decoding of convolutional tail-biting codes (CTBC) from the observations that the decoding does not have to start from the beginning of the received vector, and that the reliability of the received vector can be used to determine a good starting position of the decoding process. Simulations show that our reliability-based enhancement can be used together with existing decoding algorithms of the CTBC to improve either their error rate or complexity.
The modified wrap-around Viterbi algorithm for convolutional tail-biting codes
(2012-06-01)
Han, Yunghsiang S.
;
Wu, Ting-Yi
;
Pai, Hung-Ta
;
Chen, Po-Ning
;
電機工程學系
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.