Compound Channel Capacities under Energy Constraints and Application
- URL: http://arxiv.org/abs/2105.04274v1
- Date: Mon, 10 May 2021 11:23:48 GMT
- Title: Compound Channel Capacities under Energy Constraints and Application
- Authors: Andrea Cacioppo, Janis N\"otzel, Matteo Rosati
- Abstract summary: We give explicit formulas for the cases of the Gaussian classical-quantum compound channels with unknown noise, unknown phase and unknown attenuation.
Our work demonstrates the value of the compound channel model as a method for the design of receivers in quantum communication.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Compound channel models offer a simple and straightforward way of analyzing
the stability of decoder design under model variations. With this work we
provide a coding theorem for a large class of practically relevant compound
channel models. We give explicit formulas for the cases of the Gaussian
classical-quantum compound channels with unknown noise, unknown phase and
unknown attenuation. We show analytically how the classical compound channel
capacity formula motivates nontrivial choices of the displacement parameter of
the Kennedy receiver. Our work demonstrates the value of the compound channel
model as a method for the design of receivers in quantum communication.
Related papers
- Resolvability of classical-quantum channels [54.825573549226924]
We study the resolvability of classical-quantum channels in two settings, for the channel output generated from the worst input, and form the fixed independent and identically distributed (i.i.d.) input.
For the fixed-input setting, while the direct part follows from the known quantum soft covering result, we exploit the recent alternative quantum Sanov theorem to solve the strong converse.
arXiv Detail & Related papers (2024-10-22T05:18:43Z) - Exponents for classical-quantum channel simulation in purified distance [5.598487000369366]
We determine the exact error and strong converse exponent for entanglement-assisted classical-quantum channel simulation.
We critically use various properties of the quantum fidelity, additional auxiliary channel techniques, approximations via Chebyshev inequalities, and entropic continuity bounds.
arXiv Detail & Related papers (2024-10-14T17:45:41Z) - Fully quantum arbitrarily varying channel coding for entanglement-assisted communication [0.0]
We study the problem of entanglement-assisted capacity in the presence of system uncertainty.
We find that, under the assumption of a finite environment dimension, it is equal to a corresponding compound capacity.
Our results imply that in certain fully quantum arbitrarily varying channel models, the entanglement-assisted capacity can be positive while the classical capacity is equal to zero.
arXiv Detail & Related papers (2024-04-12T02:10:04Z) - On Simultaneous Information and Energy Transmission through Quantum Channels [15.387256204743407]
We introduce the quantum-classical analogue of the capacity-power function.
We generalize results in classical information theory for transmitting classical information through noisy channels.
arXiv Detail & Related papers (2023-09-24T16:46:47Z) - Spiking Neural Network Decision Feedback Equalization [70.3497683558609]
We propose an SNN-based equalizer with a feedback structure akin to the decision feedback equalizer (DFE)
We show that our approach clearly outperforms conventional linear equalizers for three different exemplary channels.
The proposed SNN with a decision feedback structure enables the path to competitive energy-efficient transceivers.
arXiv Detail & Related papers (2022-11-09T09:19:15Z) - Analytical calculation formulas for capacities of classical and
classical-quantum channels [61.12008553173672]
We derive an analytical calculation formula for the channel capacity of a classical channel without any iteration.
Our extended analytical algorithm have also no iteration and output the exactly optimum values.
arXiv Detail & Related papers (2022-01-07T13:39:09Z) - Noisy Channel Language Model Prompting for Few-Shot Text Classification [87.23056864536613]
We introduce a noisy channel approach for language model prompting in few-shot text classification.
Instead of computing the likelihood of the label given the input, channel models compute the conditional probability of the input given the label.
We use channel models for recently proposed few-shot learning methods with no or very limited updates to the language model parameters.
arXiv Detail & Related papers (2021-08-09T15:06:26Z) - Coherent control and distinguishability of quantum channels via
PBS-diagrams [59.94347858883343]
We introduce a graphical language for coherent control of general quantum channels inspired by practical quantum optical setups involving polarising beam splitters (PBS)
We characterise the observational equivalence of purified channels in various coherent-control contexts, paving the way towards a faithful representation of quantum channels under coherent control.
arXiv Detail & Related papers (2021-03-02T22:56:25Z) - Bosonic Dirty Paper Coding [12.437226707039448]
The single-mode bosonic channel is addressed with classical interference in the modulation and with side information at the transmitter.
We show that the effect of the channel parameter can be canceled even when the decoder has no side information.
Considering the special case of a pure-loss bosonic channel, we demonstrate that the optimal coefficient for dirty paper coding is not necessarily the MMSE estimator coefficient as in the classical setting.
arXiv Detail & Related papers (2021-01-03T09:48:08Z) - Data-Driven Symbol Detection via Model-Based Machine Learning [117.58188185409904]
We review a data-driven framework to symbol detection design which combines machine learning (ML) and model-based algorithms.
In this hybrid approach, well-known channel-model-based algorithms are augmented with ML-based algorithms to remove their channel-model-dependence.
Our results demonstrate that these techniques can yield near-optimal performance of model-based algorithms without knowing the exact channel input-output statistical relationship.
arXiv Detail & Related papers (2020-02-14T06:58:27Z) - Communication over Quantum Channels with Parameter Estimation [12.437226707039448]
We study scenarios that include either strictly-causal, causal, or non-causal channel side information (CSI) available at the encoder, and also when CSI is not available.
Regularized formulas for the capacity-distortion regions are derived.
arXiv Detail & Related papers (2020-01-01T21:32:04Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.