MIMO (Multiple Input Multiple Output) transmitting antenna number blind estimation algorithm based on random matrix theory and feature threshold estimation

Abstract

The invention discloses a transmitting antenna number blind estimation method applicable to an MIMO (Multiple Input Multiple Output) system, and mainly solves the problem of low accuracy of identifying a number of transmitting antennas of the MIMO system in a time-variant fast fading channel environment and under the condition of a low signal-to-noise ratio. The method comprises the steps of: (1) constructing a received sample matrix by utilizing a received signal of a non-cooperative receiving machine, and implementing data acquisition of the non-cooperative receiving machine; (2) constructing a covariance matrix by utilizing the received signal sample matrix; (3) carrying out feature value decomposition on the covariance matrix; (4) setting a bilateral detection threshold, and initializing a counting variable; (5) calculating a second-order moment; (6) calculating a feature value judgment threshold; and (7) according to a feature value and a threshold, carrying out judgment to obtain the number of the transmitting antennas of the MIMO system. According to the transmitting antenna number blind estimation method disclosed by the invention, a correct identification rate in a fast fading channel under the condition of small sample received data and under the condition of the low signal-to-noise ratio is ensured, and applicability in military communication resistance and in the time-variant fast fading channel is ensured.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, and relates to an estimation algorithm for the number of transmitting antennas applicable to a Multiple Input Multiple Output (MIMO) system, which is mainly used for blind identification of communication signals and cognitive radio. Background technique [0002] The rapid development of mobile Internet and multimedia communication technology has put forward new requirements for future mobile communication systems. In the context of increasingly tight spectrum resources and increasing transmission rates, MIMO technology provides strong technical support for the realization of these goals. In non-cooperative communication scenarios, the receiver needs to perform blind estimation and identification of MIMO signal parameters, including the number of transmitting antennas, space-time coding type, channel parameters, and modulation methods, and the estimation of the number of transmittin...

AI Technical Summary

Problems solved by technology

[0004] The disadvantages of the above algorithms are: on the one hand, more received data samples are required to estimate the number of transmitting antennas, the calculation complexity is high, and the algorithm has poor real-time performance, making it difficult to apply to fast fading scenarios; on the other hand, in low SNR environments The recognition accuracy is low, and it is difficult to meet the scene requirements of blind recognition of non-cooperative communication MIMO signals in the environment of poor signal-to-noise ratio

Images