Capacity estimation of two-dimensional channels using Sequential Monte Carlo
Information Theory
2014-08-12 v2 math.IT
Computation
Abstract
We derive a new Sequential-Monte-Carlo-based algorithm to estimate the capacity of two-dimensional channel models. The focus is on computing the noiseless capacity of the 2-D one-infinity run-length limited constrained channel, but the underlying idea is generally applicable. The proposed algorithm is profiled against a state-of-the-art method, yielding more than an order of magnitude improvement in estimation accuracy for a given computation time.
Cite
@article{arxiv.1405.0102,
title = {Capacity estimation of two-dimensional channels using Sequential Monte Carlo},
author = {Christian A. Naesseth and Fredrik Lindsten and Thomas B. Schön},
journal= {arXiv preprint arXiv:1405.0102},
year = {2014}
}