Covariance matching-based multi-antenna spectrum sensing method

Abstract

The invention discloses a covariance matching-based multi-antenna spectrum sensing method, which specifically comprises a semi-blind detection method and a complete-blind detection method. In the semi-blind detection method, a new detection amount is constructed by comparing a received-signal sampling covariance matrix with a known noise covariance matrix (herein, the noise covariance refers to noise variance, M refers to the number of receiving antenna, and I[M] refers to a M*M unit matrix); and in the complete-blind detection method, another new detection amount is constructed by the fact that the normalized sampling covariance matrix of a main signal is approximately equal to a diagonal matrix when the main signal does not appear. In the two methods of the invention, because of using correlation as the basis of decision amount of construction, the statistic characteristics of a master user signal and a transmission channel are not required to be known in advance; and especially fora complete-blind detection algorithm based on covariance matching, the spectrum sensing can effectively be implemented under the condition that the noise variance is unknown.

Description

technical field The invention relates to two implementation methods adapted to idle frequency band perception in cognitive radio, and belongs to cognitive radio technology in wireless communication. Background technique Cognitive radio technology is considered to be a technology that can effectively alleviate the contradiction between the increasing spectrum demand and limited spectrum resources. Cognitive radio requires that the communication between secondary users (unauthorized users) cannot interfere with the normal communication of primary users (authorized users). To avoid such interference, cognitive radio systems usually require secondary users to periodically detect the activities of primary users using spectrum sensing technology. Only when it is detected that the signal of the primary user does not appear, the secondary user can use the spectrum resources vacated by the primary user. Therefore, the effective implementation of spectrum sensing is the premise and ...

AI Technical Summary

Problems solved by technology

Technical problem: The classic energy detection method only uses the energy information of the received signal to judge the presence or absence of the primary user signal. When there is correlation in signal sampling or noise uncertainty occurs, its performance will drop significantly

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