A Deterministic Algorithm for the Capacity of Finite-State Channels

01/09/2019
by   Chengyu Wu, et al.
0

We propose a modified version of the classical gradient descent method to compute the capacity of finite-state channels with Markovian input. Under some concavity assumption, our algorithm proves to achieve a polynomial accuracy in a polynomial time for general finite-state channels. Moreover, for some special families of finite-state channels, our algorithm can achieve an exponential accuracy in a polynomial time.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
10/26/2017

A polynomial time algorithm to compute geodesics in CAT(0) cubical complexes

This paper presents the first polynomial time algorithm to compute geode...
research
05/10/2019

Quantifying information flow in interactive systems

We consider the problem of quantifying information flow in interactive s...
research
05/30/2020

Finite-Support Capacity-Approaching Distributions for AWGN Channels

In this paper, the Dynamic-Assignment Blahut-Arimoto (DAB) algorithm ide...
research
01/09/2019

Polynomial-time Capacity Calculation and Scheduling for Half-Duplex 1-2-1 Networks

This paper studies the 1-2-1 half-duplex network model, where two half-d...
research
09/03/2018

Delocalisation of one-dimensional marginals of product measures and the capacity of LTI discrete channels

We consider discrete linear time invariant (LTI) channels satisfying the...
research
07/15/2020

How to apply the rubber method for channels with feedback

We give an overview of applications of the rubber method. The rubber met...
research
04/16/2022

Polynomial-time sparse measure recovery

How to recover a probability measure with sparse support from particular...

Please sign up or login with your details

Forgot password? Click here to reset