@article{10902/20835,
year = {2021},
month = {2},
url = {http://hdl.handle.net/10902/20835},
abstract = {In this paper we propose a multiple importance sampling (MIS) method for the efficient symbol error rate (SER) estimation of maximum likelihood (ML) multiple-input multiple-output (MIMO) detectors. Given a transmitted symbol from the input lattice, obtaining the SER requires the computation of an integral outside its Voronoi region in a high-dimensional space, for which a closed-form solution does not exist. Hence, the SER must be approximated through crude or naive Monte Carlo (MC) simulations. This practice is widely used in the literature despite its inefficiency, particularly severe at high signal-to-noise-ratio (SNR) or for systems with stringent SER requirements. It is well-known that more sophisticated MC-based techniques such as MIS, when carefully designed, can reduce the variance of the estimators in several orders of magnitude with respect to naive Monte Carlo in rare-event estimation, or equivalently, they need significantly less samples for attaining a desired performance. The proposed MIS method provides unbiased SER estimates by sampling from a mixture of components that are carefully chosen and parametrized. The number of components, the parameters of the components, and their weights in the mixture, are automatically chosen by the proposed method. As a result, the proposed method is flexible, easy-to-use, theoretically sound, and presents a high performance in a variety of scenarios. We show in our simulations that SERs lower than 10?8 can be accurately estimated with just 104 random samples.},
organization = {The work of V. Elvira was supported by the Agence Nationale de la Recherche of France under PISCES project (ANR-17-CE40-0031-01). The work of I. Santamaria was supported by Ministerio de Ciencia, Innovación
y Universidades and AEI/FEDER funds of the E.U., under grant PID2019-104958RB-C43 (ADELE). A short preliminary version of this paper was presented at the 2019 Asilomar Conference on Signals, Systems, and Computers.},
publisher = {Institute of Electrical and Electronics Engineers, Inc.},
publisher = {IEEE Transactions on Signal Processing, 2021, 69, 1200-1212},
title = {Multiple importance sampling for symbol error rate estimation of maximum-likelihood detectors in MIMO channels},
author = {Elvira Arregui, Víctor and Santamaría Caballero, Luis Ignacio},
}