標題: Robust Decoding for Convolutionally Coded Systems Impaired by Memoryless Impulsive Noise
作者: Tseng, Der-Feng
Han, Yunghsiang S.
Mow, Wai Ho
Chen, Po-Ning
Deng, Jing
Vinck, A. J. Han
電機資訊學士班
Undergraduate Honors Program of Electrical Engineering and Computer Science
關鍵字: Impulsive noise;Bernoulli-Gaussian channel;Middleton Class-A model;metric erasure Viterbi Algorithm (MEVA);power line communications
公開日期: 1-十一月-2013
摘要: It is well known that communication systems are susceptible to strong impulsive noises. To combat this, convolutional coding has long served as a cost-efficient tool against moderately frequent memoryless impulses with given statistics. Nevertheless, impulsive noise statistics are difficult to model accurately and are typically not time-invariant, making the system design challenging. In this paper, because of the lack of knowledge regarding the probability density function of impulsive noises, an efficient decoding scheme was devised for single-carrier narrowband communication systems; a design parameter was incorporated into recently introduced joint erasure marking and Viterbi decoding algorithm, dubbed the metric erasure Viterbi algorithm (MEVA). The proposed scheme involves incorporating a well-designed clipping operation into a Viterbi algorithm, in which the clipping threshold must be appropriately set. In contrast to previous publications that have resorted to extensive simulations, in the proposed scheme, the bit error probability performance associated with the clipping threshold was characterized by deriving its Chernoff bound. The results indicated that when the clipping threshold was judiciously selected, the MEVA can be on par with its optimal maximum-likelihood decoding counterpart under fairly general circumstances.
URI: http://dx.doi.org/10.1109/TCOMM.2013.101813.130122
http://hdl.handle.net/11536/23661
ISSN: 0090-6778
DOI: 10.1109/TCOMM.2013.101813.130122
期刊: IEEE TRANSACTIONS ON COMMUNICATIONS
Volume: 61
Issue: 11
起始頁: 4640
結束頁: 4652
顯示於類別:期刊論文


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