Simulation-Based Computation of Information Rates for Channels With Memory

The information rate of finite-state source/channel models can be accurately estimated by sampling both a long channel input sequence and the corresponding channel output sequence, followed by a forward sum-product recursion on the joint source/channel trellis. This method is extended to compute upp...

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Bibliographic Details
Published in	IEEE transactions on information theory Vol. 52; no. 8; pp. 3498 - 3508
Main Authors	Arnold, D.M., Loeliger, H.-A., Vontobel, P.O., Kavcic, A., Wei Zeng
Format	Journal Article
Language	English
Published	New York, NY IEEE 01.08.2006 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects	Applied sciences Approximation AWGN Bounds Channel capacity Channels Coding, codes Communication channels Computation Computational modeling Computer simulation Data communications Detection, estimation, filtering, equalization, prediction Estimating techniques Exact sciences and technology finite-state models Hidden Markov models information rate Information rates Information technology Information theory Information, signal and communications theory Intersymbol interference Laboratories Lower bounds Mathematical models Recursion Recursive estimation Sampling Sampling, quantization Signal and communications theory Signal, noise sum-product algorithm Systems, networks and services of telecommunications Telecommunications Telecommunications and information theory Transmission and modulation (techniques and equipments) trellises Channel with memory Parameter estimation sum-product algorithm Channel capacity Probabilistic approach Bounds hidden-Markov models Information rate Algorithm Joint source channel coding Information transmission trellises Simulation Channel estimation Hidden Markov models finite-state models Sampling
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ISSN	0018-9448 1557-9654
DOI	10.1109/TIT.2006.878110

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Summary:	The information rate of finite-state source/channel models can be accurately estimated by sampling both a long channel input sequence and the corresponding channel output sequence, followed by a forward sum-product recursion on the joint source/channel trellis. This method is extended to compute upper and lower bounds on the information rate of very general channels with memory by means of finite-state approximations. Further upper and lower bounds can be computed by reduced-state methods
Bibliography:	SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23
ISSN:	0018-9448 1557-9654
DOI:	10.1109/TIT.2006.878110