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Cognitive radio electric dynamic smart frequency spectrum access method for unknown environmental model characteristics

A technology of cognitive radio and unknown environment, which is applied in the field of distributed non-central cognitive wireless network communication and wireless communication, which can solve the problems of unreliable communication, authorized user interference, etc.

Inactive Publication Date: 2012-07-25
HARBIN INST OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0019] In order to overcome the problem that the existing distributed non-cooperative cognitive radio dynamic spectrum access method cannot handle the unknown environment model, cannot perform reliable communication, and also causes serious interference to authorized users, the present invention provides A Cognitive Radio Dynamic Intelligent Spectrum Access Method for Unknown Environment Model Characteristics

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  • Cognitive radio electric dynamic smart frequency spectrum access method for unknown environmental model characteristics
  • Cognitive radio electric dynamic smart frequency spectrum access method for unknown environmental model characteristics
  • Cognitive radio electric dynamic smart frequency spectrum access method for unknown environmental model characteristics

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specific Embodiment approach 1

[0026] Specific implementation mode one: combine figure 1 To illustrate this embodiment, the specific steps of the cognitive radio dynamic intelligent spectrum access method for unknown environment model characteristics described in this embodiment are as follows:

[0027] Step A, establish the environmental model of the channels occupied by authorized users: each channel is independent of each other, and the situation that each channel is occupied by authorized users obeys the Markov (MARKOV) transfer process;

[0028] Step B. Each secondary user establishes the channel transfer model of the secondary user with respect to the authorized user through statistical learning method: the sampling number r is obtained by solving the central limit theorem i , through channel i at r i The sampling state of sub-sampling establishes maximum likelihood function, then maximum likelihood function is solved, solves the conversion probability of the Markov transfer process that each channel...

specific Embodiment approach 2

[0049] Embodiment 2: This embodiment is a further description of step C in Embodiment 1:

[0050] Step C1, at time t, the secondary user uses the belief matrix Λ(t)=[λ 1 (t),...,λ M (t)]

[0051] Λ ( t + 1 ) = Δ Γ ( Λ ( t ) | a , θ ) ) = Δ [ λ 1 ( t + 1 ) , . . . , λ M ( t + 1 ) ]

[0052] λ j ( ...

specific Embodiment approach 3

[0066] Specific embodiment three: this embodiment is a further description of step C in specific embodiment one, and the specific steps of step C are completed by the following steps:

[0067] Step C 1. At time t, based on the given perception and decision history, the available probability of channel i is the belief matrix:

[0068] Ω ( t + 1 ) = Δ [ w 1 ( t + 1 ) , . . . , w N ( t + 1 ) ] = Δ Γ ( Ω ( t ) | a ...

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Abstract

The invention relates to a cognitive radio electric dynamic smart frequency spectrum access method for unknown environmental model characteristics, which belongs to the field of distributed acentric cognitive radio network communication and solves the problem that the traditional cognitive radio electric dynamic smart frequency spectrum access method in a distributed non-cooperation mode can not process the unknown condition of an environment model. The cognitive radio electric dynamic smart frequency spectrum access method comprises the steps of: A, establishing an environmental model of channels occupied by an authorized user: assuming the channels are independent from each other, and the channel occupying condition of the authorized user accords with the Markov switching process; B, establishing an integral channel switching model by a secondary user through a statistical learning method: resolving the sampling quantity through a central limit theorem, establishing a maximum likelihood function through the sampling states of the channels, resolving the maximum likelihood function to obtain the switching probability of the Markov switching process; and C, making a dominant strategy by the secondary user through part observation of the Markov switching process. The invention is suitable for the cognitive radio electric dynamic smart frequency spectrum access for the unknown environmental model characteristics.

Description

technical field [0001] The invention relates to the field of wireless communication, in particular to the field of distributed non-central cognitive wireless network communication. Background technique [0002] Radio frequency spectrum resource is a kind of precious natural resource, generally authorized to use by the government. However, with the rapid development of communication technology, the shortage of spectrum resources has become an unavoidable problem. Cognitive radio is an effective means to alleviate the contradiction between the lack of spectrum resources and the increasing demand for wireless access. Cognitive radio is an intelligent wireless communication system. It can perceive the external environment, and use artificial intelligence technology to learn from the environment, by changing certain operating parameters (such as transmission power, carrier frequency and modulation technology, etc.) , in order to achieve highly reliable communication anytime, a...

Claims

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Application Information

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IPC IPC(8): H04W16/10H04W16/18
Inventor 汪洋张钦宇沙学军刘法潘启飞
Owner HARBIN INST OF TECH
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