Efficient BER simulation of orthogonal space-time block codes in Nakagami-m fading

Jacobs, Lennert; Moeneclaey, Marc

doi:10.1109/pimrc.2014.7136250

Cited by 2 publications

(2 citation statements)

References 13 publications

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“…Many works in the literature are devoted for the choice of the IS proposal, using usually a mixture of components as proposal in multiple IS (MIS) [19] and through an iterative adaptation of this proposal in adaptive IS (AIS) [20]. In [21] a biased channel distribution is proposed for the simulation of orthogonal space-time block codes (OSTBCs) on Nakagami channels. The authors of [22] used IS for the estimation of the outage probability of multiantenna receivers with generalized selection combining.…”

Section: Introductionmentioning

confidence: 99%

Multiple Importance Sampling for Symbol Error Rate Estimation of Maximum-Likelihood Detectors in MIMO Channels

Elvira

Santamarı́a

2021

IEEE Trans. Signal Process.

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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 multipleoutput (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-noiseratio (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 10 4 random samples.

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Section: Introductionmentioning

confidence: 99%

Multiple Importance Sampling for Symbol Error Rate Estimation of Maximum-Likelihood Detectors in MIMO Channels

Elvira

Santamarı́a

2021

IEEE Trans. Signal Process.

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“…However, designing a good proposal with high density in regions where samples should be drawn might not be easy, and typically is problem dependent. For instance, a biased channel distribution is proposed in [13] for the simulation of orthogonal space-time block codes (OSTBCs) on Nakagami channels. Other recent work is [14], where IS is used for the estimation of the outage probability of multi-antenna receivers with generalized selection combining.…”

Section: Introductionmentioning

confidence: 99%

Multiple Importance Sampling for Efficient Symbol Error Rate Estimation

Elvira

Santamarı́a

2019

IEEE Signal Process. Lett.

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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 closedform, 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 (MIS) 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 halfspaces 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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Efficient BER simulation of orthogonal space-time block codes in Nakagami-m fading

Cited by 2 publications

References 13 publications

Multiple Importance Sampling for Symbol Error Rate Estimation of Maximum-Likelihood Detectors in MIMO Channels

Multiple Importance Sampling for Symbol Error Rate Estimation of Maximum-Likelihood Detectors in MIMO Channels

Multiple Importance Sampling for Efficient Symbol Error Rate Estimation

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