Multiple importance sampling for efficient symbol error rate estimation

Abstract: Digital constellations formed by hexagonal or other non-square two-dimensional lattices are often used in advanced digital communication systems. The integrals required to evaluate the symbol error rate (SER) of these constellations in the presence of Gaussian noise are in general difficult to compute in closed form, and therefore Monte Carlo simulation is typically used to estimate the SER. However, naive Monte Carlo simulation can be very inefficient and requires very long simulation runs, especially at high signal-to-noise ratios. In this letter, we adapt a recently proposed multiple importance sampling technique, called ALOE (for ?at least one rare event?), to this problem. Conditioned to a transmitted symbol, an error (or rare event) occurs when the observation falls in a union of half-spaces or, equivalently, outside a given polytope. The proposal distribution for ALOE samples the system conditionally on an error taking place, which makes it more efficient than other importance sampling techniques. ALOE provides unbiased SER estimates with simulation times orders of magnitude shorter than conventional Monte Carlo.

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 Autoría: Elvira V., Santamaria I.,

 Fuente: IEEE Signal Processing Letters, 2019, 26(3), 420-424

Editorial: Institute of Electrical and Electronics Engineers Inc.

 Fecha de publicación: 01/03/2019

Nº de páginas: 5

Tipo de publicación: Artículo de Revista

DOI: 10.1109/LSP.2019.2892835

ISSN: 1070-9908,1558-2361

Proyecto español: TEC2016-75067-C4-4-R

Url de la publicación: https://doi.org/10.1109/LSP.2019.2892835