Capacity estimation of two-dimensional channels using Sequential Monte Carlo
2014 (English)In: 2014 IEEE Information Theory Workshop, 2014, 431-435 p.Conference paper (Refereed)
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 (1, ∞) 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.
Place, publisher, year, edition, pages
2014. 431-435 p.
Control Engineering Computer Science Probability Theory and Statistics
IdentifiersURN: urn:nbn:se:liu:diva-112966DOI: 10.1109/ITW.2014.6970868OAI: oai:DiVA.org:liu-112966DiVA: diva2:775991
Information Theory Workshop