Abstract
The determination of channel characteristics has always been a research hotspot of wireless communication systems. It directly affects the correctness of channel state analysis. Channel feature extraction methods are endless, but most of the existing extraction methods are limited by specific environments. The methods are complex, the system analysis is not comprehensive enough, the applicability is not extensive, and it is affected by external interference. This paper avoids the disadvantages of direct extraction and innovatively introduces an image construction method that can analyze the channel state in real time. In addition, an improved image feature extraction algorithm is proposed for the state images proposed in this paper, which verifies high robust performance of the algorithm. In the end, a model capable of efficiently and accurately predicting real-time conditions of short-wave fading channel states is constructed. First, channel state images are constructed, including time domain image, frequency domain image, and related domain image. The three state images reflect the channel state in all aspects. Then, the multi-texton image feature extraction method is optimized and improved, and the multi-structure color difference (MSC) extraction method is constructed to extract the channel state image information. Then, through the experimental simulation, the method of channel state division is specified, and the performance advantage of the improved algorithm MSC relative to the original algorithm is verified. Finally, discriminating channel state based on SVM algorithm. A series of experiments on rotation invariance test, immunity from interference test and illumination variation test verify that the proposed method has high robustness and the recognition accuracy is between 80% and 100%, which can effectively identify Instantaneous channel advantages and disadvantages.
Highlights
Wireless communication has become the main method of communication
Because the wireless channel is affected by many factors and is affected by unstable factors such as external interference and noise, the channel characteristics such as Doppler shift, multipath effect and delay are changed in real time, and the
The traditional wireless channel state analysis method relies on applicable conditions, the algorithm is complex, and cannot effectively monitor the real-time channel state, and is interfered by external factors
Summary
Wireless communication has become the main method of communication. The wireless channel is closely related to the surrounding environment. 2) The general channel analysis method is greatly affected by external interference, and the extracted features cannot accurately and real-timely analyze the channel state. In view of the different characteristics of the three signals, the time domain, frequency domain and related domain images in the same channel environment will have delay and similarity, which is more convenient to prove whether the channel state discrimination proposed in this paper can be applied to most cases, and prove whether the method is reliable. This paper will use Channel State Information to transform into time domain, frequency domain and related domain images. CONSTRUCTION OF MULTI-STRUCTURE COLOR DIFFERENCE HISTOGRAM In this paper, multi-texton histogram (MTH) and color difference histogram (CDH) are used to construct a new image feature extraction method, which is multi-structure color difference histogram (MSC)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
