| Title | Optimal Linear Joint Source-Channel Coding with Delay Constraint |
| Authors | Erik Johannesson, Anders Rantzer, Bo Bernhardsson, Andrey Ghulchak |
| Full-text | Available as PDF |
| Publication | IEEE Transactions on Information Theory |
| Year | 2012 |
| Document type | Article |
| Status | Submitted |
| Language | eng |
| Abstract English | The problem of joint source-channel coding is considered for a stationary remote (noisy) Gaussian source and a Gaussian channel. The encoder and decoder are assumed to be causal and their combined operations are subject to a delay constraint. It is shown that, under the mean-square error distortion metric, an optimal encoder-decoder pair from the linear and time-invariant (LTI) class can be found by minimization of a convex functional and a spectral factorization. The functional to be minimized is the sum of the well-known cost in a corresponding Wiener filter problem and a new term, which is induced by the channel noise and whose coefficient is the inverse of the channel's signal-to-noise ratio. This result is shown to also hold in the case of vector-valued signals, assuming parallel additive white Gaussian noise channels. It is also shown that optimal LTI encoders and decoders generally require infinite memory, which implies that approximations are necessary.<br> A numerical example is provided, which compares the performance to the lower bound provided by rate-distortion theory. |
| Keywords | Analog transmission, causal coding, delay constraint, joint source-channel coding, MSE distortion, remote source, signal-to-noise ratio (SNR)., |
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