Multiple Quantum Hypothesis Testing Expressions and Classical-Quantum Channel Converse Bounds

Alternative exact expressions are derived for the minimum error probability of a hypothesis test discriminating among $M$ quantum states. The first expression corresponds to the error probability of a binary hypothesis test with certain parameters; the second involves the optimization of a given information-spectrum measure. Particularized in the classical-quantum channel coding setting, this characterization implies the tightness of two existing converse bounds; one derived by Matthews and Wehner using hypothesis-testing, and one obtained by Hayashi and Nagaoka via an information-spectrum approach.Comment: Presented at the 2016 IEEE International Symposium on Information Theory, July 10-15, 2016, Barcelona, Spai

Error Probability Bounds for Gaussian Channels under Maximal and Average Power Constraints

This paper studies the performance of block coding on an additive white Gaussian noise channel under different power limitations at the transmitter. Lower bounds are presented for the minimum error probability of codes satisfying maximal and average power constraints. These bounds are tighter than previous results in the finite blocklength regime, and yield a better understanding on the structure of good codes under an average power limitation. Evaluation of these bounds for short and moderate blocklengths is also discussed.Comment: Submitted to the IEEE Transactions on Information Theory. This article was presented in part at the 2019 IEEE International Symposium on Information Theory, Paris, France (ISIT 2019) and at the 2020 International Z\"urich Seminar on Communication and Information, Z\"urich, Switzerland (IZS 2020

Robust Signaling for Bursty Interference

This paper studies a bursty interference channel, where the presence/absence of interference is modeled by a block-i.i.d.\ Bernoulli process that stays constant for a duration of $T$ symbols (referred to as coherence block) and then changes independently to a new state. We consider both a quasi-static setup, where the interference state remains constant during the whole transmission of the codeword, and an ergodic setup, where a codeword spans several coherence blocks. For the quasi-static setup, we study the largest rate of a coding strategy that provides reliable communication at a basic rate and allows an increased (opportunistic) rate when there is no interference. For the ergodic setup, we study the largest achievable rate. We study how non-causal knowledge of the interference state, referred to as channel-state information (CSI), affects the achievable rates. We derive converse and achievability bounds for (i) local CSI at the receiver-side only; (ii) local CSI at the transmitter- and receiver-side, and (iii) global CSI at all nodes. Our bounds allow us to identify when interference burstiness is beneficial and in which scenarios global CSI outperforms local CSI. The joint treatment of the quasi-static and ergodic setup further allows for a thorough comparison of these two setups.Comment: 67 pages, 39 figure

On the Sum Capacity of A Class of Cyclically Symmetric Deterministic Interference Channels

Certain deterministic interference channels have been shown to accurately model Gaussian interference channels in the asymptotic low-noise regime. Motivated by this correspondence, we investigate a K user-pair, cyclically symmetric, deterministic interference channel in which each receiver experiences interference only from its neighboring transmitters (Wyner model). We establish the sum capacity for a large set of channel parameters, thus generalizing previous results for the 2-pair case.Comment: 5 pages; submitted to IEEE International Symposium on Information Theory (ISIT 2009

The Error Probability of Generalized Perfect Codes

This paper has been presented at : IEEE International Symposium on Information Theory 2018We introduce a definition of perfect and quasi-perfect codes for symmetric channels parametrized by an auxiliary output distribution. This new definition generalizes previous definitions and encompasses maximum distance separable codes. The error probability of these codes, whenever they exist, is shown to attain the meta-converse lower bound.This work has been funded in part by the European Research Council (ERC) under grants 714161 and 725411, by the Spanish Ministry of Economy and Competitiveness under Grants TEC2016-78434-C3 and IJCI-2015-27020, by the National Science Foundation under Grant CCF-1513915 and by the Center for Science of Information, an NSF Science and Technology Center under Grant CCF-0939370

The Error Probability of Generalized Perfect Codes via the Meta-Converse

We introduce a definition of perfect and quasiperfect codes for discrete symmetric channels based on the packing and covering properties of generalized spheres whose shape is tilted using an auxiliary probability measure. This notion generalizes previous definitions of perfect and quasiperfect codes and encompasses maximum distance separable codes. The error probability of these codes, whenever they exist, is shown to coincide with the estimate provided by the metaconverse lower bound. We illustrate how the proposed definition naturally extends to cover almost-lossless source-channel coding and lossy compression.ER

Bayesian M-Ary Hypothesis Testing: The Meta-Converse and Verdu-Han Bounds Are Tight

Two alternative exact characterizations of the minimum error probability of Bayesian M-ary hypothesis testing are derived. The first expression corresponds to the error probability of an induced binary hypothesis test and implies the tightness of the meta-converse bound by Polyanskiy et al.; the second expression is a function of an information-spectrum measure and implies the tightness of a generalized Verdú-Han lower bound. The formulas characterize the minimum error probability of several problems in information theory and help to identify the steps where existing converse bounds are loose

Multi-Class Source-Channel Coding

This paper studies an almost-lossless source-channel coding scheme in which source messages are assigned to different classes and encoded with a channel code that depends on the class index. The code performance is analyzed by means of random-coding error exponents and validated by simulation of a low-complexity implementation using existing source and channel codes. While each class code can be seen as a concatenation of a source code and a channel code, the overall performance improves on that of separate source-channel coding and approaches that of joint source-channel coding when the number of classes increase