Signal-to-noise-ratio estimation method

Abstract

The invention provides a signal-to-noise-ratio estimation method which is used for estimating the signal to noise ratio of a receiving signal according to pilot frequencies inserted into the receiving signal. The signal-to-noise-ratio estimation method includes the following steps: S1, a pilot frequency numerical value Xm, k, a channel estimation value Hm, k and Gaussian white noise Nm, k of the positions where the pilot frequencies are located are obtained from the receiving signal, wherein the m and the k show that the corresponding pilot frequencies are located at the mth data symbol and the kth subcarrier; S2, pilot frequency position information Ym, k of the positions where the corresponding pilot frequencies are located is obtained according to the pilot frequency numerical value Xm, k, the channel estimation value Hm, k and the Gaussian white noise Nm, k; S3, a signal-to-noise-ratio estimation value of the receiving signal is obtained according to the pilot frequency numerical value Xm, k, the channel estimation value Hm, k and the pilot frequency position information Ym, k. By means of the signal-to-noise-ratio estimation method, under the condition that the number of the pilot frequencies inserted into data symbols is limited and a large amount of statistics cannot be carried out, contiguous items between the noise and the signal can be eliminated, the accuracy and the stability of the algorithm estimation value can be optimized, and the computing complexity can be simplified.

Description

technical field [0001] The invention relates to the field of communication technology, in particular to a signal-to-noise ratio estimation method. Background technique [0002] In a communication system, the parameters that characterize channel quality mainly include bit error rate, packet error rate, signal-to-noise ratio (signal-to-interference ratio), received signal strength, Doppler frequency shift, and channel delay spread. Among them, bit error rate and packet error rate are direct measures of signal transmission quality, but they need to be obtained through a large number of statistics, which takes a long time and cannot reflect real-time system performance. As an important parameter in the communication system, the Signal to Noise Ratio (SNR) is an important basis for the realization of various communication technologies, including handover in mobile communication, link adaptive technology, decoding algorithm, etc. etc., which are directly related to the bit error ...

AI Technical Summary

Problems solved by technology

However, for frequency-selective channels, frequency-domain autocorrelation ignores frequency-selective fading when averaging

Therefore, when the channel has serious deep fading, the estimation performance will be seriously deteriorated, and the calculation amount of the algorithm is relatively large, and there are more correlation operations than time autocorrelation

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