Multi-Level Kernel-Based QAM Symbol Error Probability Estimation

Kernel density estimators technique has been successfully applied to efficient Bit Error Rate (BER) computation issue under a diversity of simulation frameworks. However, as contemporary and emerging digital communication systems are increasingly provided with advanced transceivers, it is questionable if the Symbol Error Rate (SER) can be anyway derived from the BER. This paper investigates for a direct way to efficiently compute the SER. Focusing on the ubiquitous multi-level Quadrature Amplitude Modulation (QAM) transmission schemes, a Gaussian kernel-based estimator is designed. Simulation of the 4-QAM transmission scheme under various channel models shows that the proposed estimator can achieve efficient estimations with a very high degree of accuracy and reliability

A Kernel-Based QAM Symbol Error Probability Estimation Technique

International audienceKernel techniques for efficient error probability estimation have demonstrated good performance in Bit Error Probability (BEP) estimation under a diversity of simulation frameworks. However, the transmission schemes of contemporary and emerging communication systems are more and more complex so that it is questionable if the Symbol Error Probability (SEP) estimate can be anyway derived from the BEP estimate. In this paper, we investigate for a direct way to efficiently estimate the SEP based on the kernel technique. We focus on the ubiquitous Quadrature Amplitude Modulation (QAM) systems and design a Gaussian kernel-based estimator. Simulation results, involving 4-QAM and 16-QAM symbols transmissions over the additive white Gaussian noise channel and over a frequency-selective channel, show that the proposed estimator can perform efficient, reliable and accurate SEP estimations

An Efficient kernel-based technique for QAM symbol error probability estimation

International audienceIt is of a major interest for contemporary and emerging wireless communication systems to be able to compute error rates fastly, efficiently and in real time. We propose a novel kernel-based Symbol Error Probability (SEP) estimation approach for Quadrature Amplitude Modulation (QAM) systems. The received soft observations are partitioned using an unsupervised stochastic expectation maximisation algorithm. The SEP is estimated using kernel-based probability density function estimate of modified versions of the received observations. Simu- lation results involving 4-QAM transmissions over a frequency- selective channel showed, for practically equivalent estimation accuracy, drastical computational cost reductions compared to the conventional way of estimating the SEP

Design Techniques of Spatially Coupled Low-Density Parity-Check Codes: A Review and Tutorial on 5G New Radio

International audienceAs active as the research is on the various possible uses of 5G and B5G (beyond 5G), we herein make a tutorial and review on the existing spatial coupling techniques that are used in the protograph-based design of Spatially Coupled Low-Density Parity-Check (SC-LDPC) codes. We unroll useful details for the computing of these techniques, implement them in the context of the 5G standard and draw up their performances. As a main result in terms of lesson learnt, a guide is provided to select the most appropriate spatially coupled technique for the three main 5G services and for three of its numerous use cases. Three research tracks are pointed out

Enhancing 5G Forward Error Correction Codes for URLLC by Spatial Coupling

International audienceIn this paper, we investigate how to relax the tradeoff between reliability and latency in 5G Ultra-Reliable and Low-Latency Communications (URLLC) services. We propose a redesign of the 5G Forward Error Correction (FEC) code to increase its error correction capability for 5G-enabled URLLC use cases. Starting from the base matrix of the 5G standard Low-Density Parity-Check (LDPC) code we construct a spatially coupled base matrix. From this base matrix, a binary spatially coupled parity check matrix is then obtained after a lifting operation based on one of the lifting factors supported by the standard. The results of the simulation demonstrate that the proposing spatially coupled codes allow additional coding gains of up to 0.8 dB under the considerate scenarios

Estimation non-paramétrique par méthode à noyau de la probabilité d'erreur binaire dans les systèmes de communication numériques : un estimateur pour le calcul du taux d'erreur binaire des systèmes MAQ codés

International audienceThe standard Monte Carlo estimations of rare events probabilities suffer from too much computational time. To make estimations faster, kernel-based estimators proved to be more efficient for binary systems whilst appearing to be more suitable in situations where the probability density function of the samples is unknown. We propose a kernel-based Bit Error Probability (BEP) estimator for coded M-ary Quadrature Amplitude Modulation (QAM) systems. We defined soft real bits upon which an Epanechnikov kernel-based estimator is designed. Simulation results showed, compared to the standard Monte Carlo simulation technique, accurate, reliable and efficient BEP estimates for 4-QAM and 16-QAM symbols transmissions over the additive white Gaussian noise channel and over a frequency-selective Rayleigh fading channel.Les estimations de probabilités d'événements rares par la méthode de Monte Carlo classique souffrent de trop de temps de calculs. Des estimateurs à noyau se sont montrés plus efficaces sur des systèmes binaires en même temps qu'ils paraissent mieux adaptés aux situations où la fonction de densité de probabilité est inconnue. Nous proposons un estimateur de Probabilité d'Erreur Bit (PEB) à noyau pour les systèmes M-aires codés de Modulations d'Amplitude en Quadrature (MAQ). Nous avons défini des bits souples à valeurs réelles à partir desquels un estimateur à noyau d'Epanechnikov est conçu. Les simulations ont montré, par rapport à la méthode Monte Carlo, des estimées de PEB précises, fiables et efficaces pour des transmissions MAQ-4 et MAQ-16 sur canaux à bruit additif blanc Gaussien et à évanouïssements de Rayleigh sélectif en fréquence

Kernel-based performance evaluation of coded QAM systems

International audienceKernel Bit Error Rate (BER) estimators are of recent interest for Monte Carlo sample size reduction. Until now, they mainly addressed binary modulation systems. In this paper, a kernelbased BER estimator is designed for coded M-ary Quadrature Amplitude Modulation (QAM) systems. The observations from which estimations are made are defined in the form of bounded soft bits. An Epanechnikov kernel function is selected and its smoothing parameter is derived based on the concept of canonical bandwidth. Simulations are run for 4-QAM and 16-QAM systems, involving additive white Gaussian noise and frequency-selective Rayleigh fading channels respectively. Simulation results show that the proposed estimator yields significative sample savings that grow with Eb/N0

A Kernel-based soft BER estimator for coded QAM transmission systems

International audienceThis paper addresses the problem of the Monte Carlo method complexity reduction regarding bit error probability (BEP) estimation. A kernel-based BEP estimator is designed for coded M-ary quadrature amplitude modulation (QAM) transmissions schemes. The design of the kernel estimator is made in a context where the soft observations are spread along a bounded support. An Epanechnikov kernel function is chosen. The optimal smoothing parameter is selected based on an asymptotic mean integrated squared error criterion and replacing the unkonwn density function by a reference distribution. Simulations are run for 4-QAM transmission scheme over a frequency-selective Rayleigh fading channel. The proposed estimator is demonstrated reliable and efficient bringing otherwise significative sample size savings