Abstract
We derive various error exponents for communication channels with random states, which are available non-causally at the encoder only. For both the finite-alphabet Gel’fand–Pinsker channel and its Gaussian counterpart, the dirty-paper channel, we derive random coding exponents, error exponents of the typical random codes (TRCs), and error exponents of expurgated codes. For the two channel models, we analyze some sub-optimal bin-index decoders, which turn out to be asymptotically optimal, at least for the random coding error exponent. For the dirty-paper channel, we show explicitly via a numerical example, that both the error exponent of the TRC and the expurgated exponent strictly improve upon the random coding exponent, at relatively low coding rates, which is a known fact for discrete memoryless channels without random states. We also show that at rates below capacity, the optimal values of the dirty-paper design parameter α in the random coding sense and in the TRC exponent sense are different from one another, and they are both different from the optimal α that is required for attaining the channel capacity. For the Gel’fand–Pinsker channel, we allow for a variable-rate random binning code construction, and prove that the previously proposed maximum penalized mutual information decoder is asymptotically optimal within a given class of decoders, at least for the random coding error exponent.
Original language | English |
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Pages (from-to) | 7479-7498 |
Number of pages | 20 |
Journal | IEEE Transactions on Information Theory |
Volume | 69 |
Issue number | 12 |
DOIs | |
State | Accepted/In press - 2023 |
Keywords
- Channel models
- Codes
- Decoding
- Dirty-paper channel
- Encoding
- Error probability
- Gel’fand-Pinsker Channel
- Monte Carlo methods
- Optimization
- error exponent
- expurgated exponent
- random states
- side information
- typical random code
All Science Journal Classification (ASJC) codes
- Information Systems
- Library and Information Sciences
- Computer Science Applications