Blind signal to noise ratio estimation method based on multiple input multiple output (MIMO)-orthogonal frequency division multiplexing (OFDM) signal cyclostationarity

Abstract

The invention discloses a blind signal to noise ratio estimation method based on multiple input multiple output (MIMO)-orthogonal frequency division multiplexing (OFDM) signal cyclostationarity. A MIMO channel can be effectively converted into a plurality of single input single output channels by utilizing own cyclostationarity of an OFDM signal transmitted by a MIMO-OFDM system and selecting a proper cyclic suffix length and different null points of a cycle autocorrelation function of a transmission signal, and the signal to noise ratio of each channel in a multi-path environment can be accurately estimated by utilizing second-order statistic. Compared with the conventional training-sequence-based signal to noise ratio estimation method, the invention increases the frequency band utilization rate of the MIMO-OFDM system, ensures high estimation speed and simultaneously avoids reduction in estimation precision.

Description

Technical field [0001] The present invention relates to a method for estimating signal-to-noise ratio, in particular to a method for blind signal-to-noise ratio estimation based on the cyclostationary characteristics of MIMO-OFDM signals. Background technique [0002] From the 2G era to the 3G era, although the 3G system has increased the transmission rate by nearly a hundred times, it still cannot meet the needs of future multimedia communication. As a supplement to the 3G system, the fourth-generation mobile communication system is proposed to meet more Large frequency band demand. MIMO (Multiple Input Multiple Output, Multiple Input Multiple Output) technology and OFDM (Orthogonal Frequency Divided Multiplexing, Orthogonal Frequency Divided Multiplexing) technology as key technologies of 4G systems have been generally recognized. As a combination product of MIMO and OFDM technologies, MIMO-OFDM technology not only has the characteristics of fast transmission rate, high spectr...

AI Technical Summary

Problems solved by technology

However, these methods have different problems in use. For example, the SSME method can only estimate the signal-to-noise ratio under the Gaussian white noise channel under the binary phase shift keying (Binary Phase Shift Keying, BPSK) modulation, while the SNV method can only estimate the signal-to-noise ratio in the low Poor performance at signal-to-noise ratio, etc.

In the MIMO-OFDM system, the SNR estimation method based on the training sequence is mostly used, and the blind SNR estimation method has not yet been studied.

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