Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Improved particle swarm-based power control optimization algorithm in cognitive radio network

A technology for improving particle swarm and cognitive radio, which is applied in power management, wireless communication, network planning, etc., and can solve problems such as low utilization of licensed frequency bands, crowded unlicensed frequency bands, and inability to meet spectrum requirements

Inactive Publication Date: 2011-03-02
LUDONG UNIVERSITY
View PDF2 Cites 42 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] The current spectrum usage method follows the principle of fixed allocation. The licensed frequency bands are sometimes not highly utilized, and the unlicensed frequency bands are overcrowded, which cannot meet the increasing spectrum demand.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Improved particle swarm-based power control optimization algorithm in cognitive radio network
  • Improved particle swarm-based power control optimization algorithm in cognitive radio network
  • Improved particle swarm-based power control optimization algorithm in cognitive radio network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0066] Below in conjunction with the accompanying drawings, specific embodiments of the present invention are given to further illustrate the present invention.

[0067] The goal of the present invention is to maximize the total utility under the condition of total constraints, use the penalty function method to deal with the constraints in the model, and use the adaptive penalty The function method uses the information obtained in the search process as feedback to guide the adjustment of the penalty factor. The fitness function in the power allocation algorithm is defined as follows:

[0068]

[0069] In the formula, U = Σ i = 1 N w i U i ( γ ( P i ) ) , V ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention relates to a power control optimization algorithm in a cognitive radio network, which belongs to the field of system resource allocation. The algorithm comprises the following steps: 1, initializing the iteration number of the algorithm, the positions and speed of particles and the basic parameters of the particle swarm; 2, calculating a fitness function value, setting the position Xa of an individual particle as the initial best position, and setting the particle with the best function value in the swarm as the initial best swarm position Gbestk; 3, searching based on a PSO algorithm, updating the best positions of the particles and the swarm and updating the speed and positions of the particles by using a fundamental formula of the particle swarm; and 4, setting a termination standard. The invention conducts study on the non-convex optimization problem controlled by the cognitive radio power and puts forward an improved particle swarm-based power control algorithm which allows utility functions such as an S-type function a convex function and the like to be non-concave, thereby conforming to the actual network better. Parameter adjustment is performed by the particle swarm algorithm to guarantee the global astringency of the algorithm. The algorithm of the invention has better validity and rapidity.

Description

technical field [0001] The invention relates to a power control optimization algorithm based on an improved particle swarm in a cognitive radio network, and belongs to the technical field of system resource allocation. Background technique [0002] The current spectrum usage method follows the principle of fixed allocation. The licensed frequency bands are sometimes underutilized, and the unlicensed frequency bands are overcrowded, which cannot meet the increasing spectrum demand. In order to solve this contradiction, people put forward cognitive radio (Cognitive Radio, CR) [1] the concept of. [0003] Cognitive radio system is an intelligent wireless communication system. It can perceive the surrounding wireless environment, and through understanding and learning of the environment, its internal state can adapt to changes in the external wireless environment, so as to realize reliable communication anytime and anywhere and spectrum resources. Efficient use of [2] . Powe...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): H04W16/14H04W52/24
Inventor 唐美芹刘晓华辛亚林
Owner LUDONG UNIVERSITY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products