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On the channel memory-diversity tradeoff in communication systems. (English) Zbl 1071.94529
Blaum, Mario (ed.) et al., Information, coding and mathematics. Proceedings of workshop honoring Professor Bob McEliece on his 60th birthday, Pasadena, CA, USA, May 24–25, 2002. Boston, MA: Kluwer Academic Publishers (ISBN 1-4020-7079-9/hbk). The Kluwer International Series in Engineering and Computer Science 687, 221-238 (2002).
Summary: The authors investigate the tradeoff between channel estimation and channel diversity for channels with memory. Block memory channels are analytically tractable yet provide practical models for many communication systems. They show that for finite block length transmission techniques there is a fundamental tradeoff between the channel estimator and the channel diversity. When the channel is operating at rates much below capacity, smaller channel memory is better since channel estimation is not crucial. This is because the code contains more than adequate redundancy to compensate for mismatch due to the potentially poor channel estimate as well as channel errors. However, at rates close to capacity, channel state information is crucial for successful decoding and therefore longer channel memory, which allows better estimates, is better. The authors draw these conclusions based on the analysis of some simple discrete-input, discrete-output channels using the channel reliability function and on simulation results for more realistic channels (soft output) using low-density parity check codes with a joint iterative decoder and channel estimator.
For the entire collection see [Zbl 1054.94001].
MSC:
94A40 Channel models (including quantum) in information and communication theory
94A24 Coding theorems (Shannon theory)
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