Spectrum detecting method based on covariance absolute value method

Abstract

The invention relates to a spectrum detecting method which belongs to the technical field of communication. The method comprises the following steps: defining a system detection threshold value; continuously sampling spatial electromagnetic signals; overlapping and grouping the sampled data; confirming self-correlation values of all groups and merging the self-correlation values; establishing a covariance matrix; and judging if an electromagnetic spectrum signal exists. By using the method, a data signal received from a radio frequency front end is directly processed in the frequency-conversion sampling manner, the sampled data is grouped in preset mode, and the traditional serial data processing method is changed into the parallel data processing method, thereby increasing the running processing speed. By using the method provided by the invention, under the condition of maintaining the original detection property of system, the speed of the system for detecting the electromagnetic spectrum signal is increased, the time of the system for detecting the electromagnetic spectrum signal is reduced, the demand of real-time detection is satisfied, thereby being beneficial to efficiently using the finite radio spectrum resource by the system and realizing the spectrum resource sharing between radio users.

Description

technical field [0001] The invention belongs to a spectrum detection method in the field of communication technology, in particular to a detection method of an electromagnetic spectrum signal based on a covariance absolute value method in a cognitive radio system. Background technique [0002] With the rapid development of wireless communication technology, the number of wireless users has increased sharply, the traffic in the same period is also extremely unbalanced, and the utilization of spectrum resources is uneven. Currently, most of the spectrum resources are in a fixed allocation mode, and a specific licensed frequency band (Licensed Frequency Bands, LFB) is allocated by a special frequency management department for use by different communication services. However, in practice, part of the licensed spectrum is not enough or a certain period of time is not enough, and a considerable amount of licensed spectrum is not fully used at this time. Tests show that up to 70% ...

AI Technical Summary

Problems solved by technology

Each of these detection methods has some shortcomings. For example, although energy detection is simple to implement, it is easily affected by noise uncertainty in reality; matched filter detection needs to know the prior information of authorized users; and periodic characteristic detection Then there are high computational complexity, and the signals that require authorized users have cycle stationary characteristics, etc.

In the actual communication environment, due to the fading of the wireless channel, the uncertainty of channel noise and the lack of prior information of authorized users, the above sensing methods have obvious defects and poor reliability to a certain extent, so their applicability is poor.

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