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On achievable rate regions for the Gaussian interference channel
- I. Sason
- Computer ScienceIEEE Transactions on Information Theory
- 1 June 2004
A lower bound on the sum-capacity (i.e., the maximal achievable total rate) is derived, and it is shown to have superiority over the maximal total rate which is achieved by the TDM/FDM approach with moderate interference.
Arimoto–Rényi Conditional Entropy and Bayesian $M$ -Ary Hypothesis Testing
In the setup of discrete memoryless channels, the exponentially vanishing decay of the Arimoto–Rényi conditional entropy of the transmitted codeword given the channel output when averaged over a random-coding ensemble is analyzed.
Concentration of Measure Inequalities in Information Theory, Communications, and Coding
This monograph focuses on some of the key modern mathematical tools that are used for the derivation of concentration inequalities, on their links to information theory, and on their various applications to communications and coding.
Variations on the Gallager bounds, connections, and applications
This work discusses many reported upper bounds on the maximum-likelihood (ML) decoding error probability and demonstrates the underlying connections that exist between them, and addresses the Gallager bounds and their variations.
Performance Analysis of Linear Codes under Maximum-Likelihood Decoding: A Tutorial
Upper and lower bounds on the error probability of linear codes under ML decoding are surveyed and applied to codes and ensembles of codes on graphs and establish the goodness of linear Codes under optimal maximum-likelihood (ML) decoding.
Improved upper bounds on the ML decoding error probability of parallel and serial concatenated turbo codes via their ensemble distance spectrum
The tangential sphere upper bound is employed to provide improved upper bounds on the block and bit error probabilities of these ensembles of codes for the binary-input additive white Gaussian noise (AWGN) channel, based on coherent detection of equi-energy antipodal signals and maximum-likelihood decoding.
Capacity-achieving ensembles for the binary erasure channel with bounded complexity
- H. Pfister, I. Sason, R. Urbanke
- Computer ScienceInternational Symposium onInformation Theory…
- 13 September 2004
We present two sequences of ensembles of nonsystematic irregular repeat-accumulate codes which asymptotically (as their block length tends to infinity) achieve capacity on the binary erasure channel…
$f$ -Divergence Inequalities
Systematic approaches to obtain f -divergence inequalities, dealing with pairs of probability measures defined on arbitrary alphabets, are developed, including “reverse Pinsker inequalities,” as well as on the Eγ divergence, which generalizes the total variation distance.
On the asymptotic input-output weight distributions and thresholds of convolutionaland turbo-like encoders
A general method is presented for computing the asymptotic input-output weight distribution of convolutional encoders and to derive lower bounds on the thresholds of these ensembles under maximum-likelihood (ML) decoding.
An improved sphere-packing bound for finite-length codes over symmetric memoryless channels
We present an improved sphere-packing (ISP) bound for finite-length error-correcting codes whose transmission takes place over symmetric memoryless channels, and the codes are decoded by an arbitrary…