Communication error function approximation method based on Pad approximation

Abstract

The invention relates to a communication error function approximation method based on Pad approximation. An existing approximation method or approximation effect is not accurate enough, or the equation complexity is higher. The method comprises the following steps of firstly, setting an upper bound function U (x), enabling an i-order derivative U (i) (x) of an x point to be equal to Q (i) (x), obtaining an equation set containing n unknown numbers and n equations, substituting the solved ai into the U (x), and collating to obtain UQ (x); then setting a lower bound function L (x), establishingan equation set, and substituting the solved bj into the L (x), and sorting to obtain LQ (x); and enabling the obtained UQ (x) and LQ (x) to tightly surround the Q (x) up and down to achieve an approximation effect. Through high-precision estimation of the Q (x) and the integral thereof, the performance analysis precision of the communication signal system can be improved. The approximation method of the communication error function can be applied to the computer simulation software of various communication systems. Compared with a conventional table lookup method, the method is more accurate, and the calculation of the communication error rate is more accurate.

Description

technical field [0001] The invention belongs to the technical field of communication and electronic information, in particular to the field of computer simulation, and relates to a communication error function approximation method based on Padre approximation. Background technique [0002] In the field of communication, the communication error Gaussian Q function plays a key role in the estimation of symbol error probability (SEP) and additive white Gaussian noise of digital modulation schemes. The approximation problem of the Gaussian Q function is widely used in signal processing and communication principles. For additive Gaussian white noise and fading channels, the Gaussian Q function is used in the BER estimation of multiple digital modulation schemes, which plays an important role in the approximation of symbol error probability. [0003] Q function, that is, the right tail function of the standard normal distribution, also known as the complementary cumulative distri...

AI Technical Summary

Problems solved by technology

Theoretically, it can be estimated by the approximate N-point Gaussian Hermite quadrature rule improved by the Gaussian Q function, where increasing the value of N can improve the accuracy, but it will correspondingly increase the computational complexity and its computational cost

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