Browsing by Author "Alajaji, Fady"

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A Generalized Poor-Verdu Error Bound for Multihypothesis Testing
(2012-01-01)
Chen, Po-Ning
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Alajaji, Fady
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電子物理學系
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Department of Electrophysics
A lower bound on the minimum error probability for multihypothesis testing is established. The bound, which is expressed in terms of the cumulative distribution function of the tilted posterior hypothesis distribution given the observation with tilting parameter theta >= 1, generalizes an earlier bound due the Poor and Verdu (1995). A sufficient condition is established under which the new bound (minus a multiplicative factor) provides the exact error probability asymptotically in theta. Examples illustrating the new bound are also provided.
An Efficient Tree Search Algorithm for the Free Distance of Variable-Length Error-Correcting Codes
(2018-03-01)
Huang, Chun
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Wu, Ting-Yi
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Chen, Po-Ning
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Alajaji, Fady
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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.
On the Construction and MAP Decoding of Optimal Variable-Length Error-Correcting Codes
(2011-01-01)
Wu, Ting-Yi
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Chen, Po-Ning
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Alajaji, Fady
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Han, Yunghsiang S.
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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
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Chen, Po-Ning
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Alajaji, Fady
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Han, Yunghsiang S.
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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.