Presentation 2000/3/17
An Efficient Evaluation Method of the Block Error Probability by Using an Importance Sampling Technique
Kenichi Tomita, Toyoo Takata, Masaaki Mori, Tadao Kasami,
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Abstract(in English) It is practically infeasible to evaluate the block error probability of soft-decision maximum likelihood decoding by simulation if the probability is very small since a large number of simulation trials is needed to obtain the value with the statistical reliability. A method that every received sequence is made to be in only the region in which the received sequence is likely to be incorrectly decoded in simulation for the evaluation of the block error probability is proposed. By using this method, the number of needed simulation trials can be reduced. In this paper, an efficient evaluation method of the block error probability of optimum or some sub-optimum decoding by simulation with an importance sampling technique is proposed.
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Keyword(in English) block error probability / importance sampling / AWGN channel
Paper # IT99-96,ISEC99-135,SST99-144
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Conference Date 2000/3/17(1days)
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Registration To Information Theory (IT)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) An Efficient Evaluation Method of the Block Error Probability by Using an Importance Sampling Technique
Sub Title (in English)
Keyword(1) block error probability
Keyword(2) importance sampling
Keyword(3) AWGN channel
1st Author's Name Kenichi Tomita
1st Author's Affiliation Department of Information Processing and Management, Shiga University()
2nd Author's Name Toyoo Takata
2nd Author's Affiliation Faculty of Software and Information Science, Iwate Prefectural University
3rd Author's Name Masaaki Mori
3rd Author's Affiliation Department of Information Processing and Management, Shiga University
4th Author's Name Tadao Kasami
4th Author's Affiliation Department of Computer Science, Hiroshima City University
Date 2000/3/17
Paper # IT99-96,ISEC99-135,SST99-144
Volume (vol) vol.99
Number (no) 700
Page pp.pp.-
#Pages 5
Date of Issue