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

Spectrum sensing method based on HDP-NSHMM

A spectrum sensing and sensing data technology, applied in the field of spectrum sensing based on HDP-NSHMM, can solve the problems of data fusion center processing capacity and processing speed requirements, large communication overhead, etc., to improve the accuracy of spectrum judgment and avoid redundant state , the effect of high perceptual performance

Active Publication Date: 2018-03-13
TONGJI UNIV
View PDF3 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, since each user needs to transmit perception data and receive decision decisions with the fusion center, this fusion method will bring a lot of communication overhead. At the same time, the processing capacity and processing speed of the data fusion center are also high requirements

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
  • Spectrum sensing method based on HDP-NSHMM
  • Spectrum sensing method based on HDP-NSHMM
  • Spectrum sensing method based on HDP-NSHMM

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0061] This method combines hierarchical Dirichlet processes with non-stationary hidden Markov models to achieve automatic clustering of historical perception data.

[0062] figure 1 Shown is the probability graphical model of HDP-NSHMM of this method. Changing the constant κ to a time-varying function variable κ(τ) makes the state transition probability related to the state duration and becomes a non-time stationary model. The k in the rectangular box means all τ in the box t-1 The serial numbers of the hidden state categories are all k, which satisfies This application proposes a spectrum sensing method based on HDP-NSHMM, including the following steps:

[0063] Step 1. Data initialization process

[0064] Step (11), collect the spectrum sensing observation data set {Y of all T historical moments t |t=1,2,...,T};

[0065] Step (12), in the scenario of spectrum sensing in a large-scale cognitive radio network, first divide the users who may have the same channel state d...

Embodiment 2

[0119] This embodiment verifies the clustering effect and spectrum decision performance of the spectrum sensing method proposed in this application in the scenario where the transition probability of the primary user (PU) on channel occupancy and release changes with the state duration.

[0120] Still considering the scenario of a small cognitive radio network, the signal of the PU passes through the Rayleigh channel and attenuates according to the free space propagation model. The difference is that the occupation and release of the channel by the PU obeys a non-stationary Markov model, and its initial The state transition probability is still set to p 0 (0 / 0) = 0.975, p 0 (1 / 0) = 0.025; p 0 (0 / 1) = 0.05, p 0 (1 / 1)=0.95, and when the current state has been maintained for longer than the preset value, the probability of state self-transition will be reduced. In the simulation setting of this embodiment, the preset holding time is set to be 10 time series lengths. After the ...

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 spectrum sensing method based on HDP-NSHMM. The spectrum sensing method comprises the following steps: performing fusion and clustering on historic sensing data by using a layered Dirichlet process-non-stationary hidden Markovmoder model; setting large self-transfer offset parameter when the maintaining time of the current state is short in the clustering cycle, therebyguaranteeing that the state cannot quickly change along the time, wherein the self-transfer offset parameter is reduced along the increasing of the maintaining time of the current state, thereby reducing the self-transfer probability of the state, and state can select to transfer to different states more possibly. Compared with the prior art, the channel state change can be judged more accuratelyby adjusting the state self-transfer probability through the self-transfer offset parameter related to the clustering class maintaining time, the occurrence of the redundancy state can be avoided through the fixed state class, the clustering accuracy of the historic sensing data is improved, the higher sensing performance is provided, and the spectrum judgment accuracy is improved.

Description

technical field [0001] The present invention relates to cognitive radio spectrum sensing technology, in particular to a spectrum sensing method based on HDP-NSHMM. Background technique [0002] Spectrum sensing is the core technology in cognitive radio. It needs to monitor the surrounding wireless environment in real time, provide available spectrum resources for unlicensed users, and ensure that licensed users occupy the current frequency band in a timely manner to avoid interference. Therefore, the accuracy of spectrum sensing plays a very critical role for cognitive radio networks. A lot of research work on spectrum sensing technology has provided many detection methods based on signal processing, and these detection methods can be mainly divided into two categories: non-cooperative spectrum sensing and cooperative spectrum sensing. [0003] Cognitive radio devices using non-cooperative spectrum sensing can independently select different detection methods, process local ...

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): H04W16/14H04L27/00H04L25/02
CPCH04L25/0222H04L27/0006H04W16/14
Inventor 黄新林唐小伟翟瑜博
Owner TONGJI UNIV
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

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com