A Study on Principal Component Analysis over Wireless Channel

Authors

  • R. Upadhyay Department of Electronics & Telecommunicati, Institute of Engineering & Technology, Devi Ahilya University, Khandwa Road, Indore 452001, India.
  • A. Soni Department of Electronics & Telecommunicati, Institute of Engineering & Technology, Devi Ahilya University, Khandwa Road, Indore 452001, India
  • P. Panse Department of Electronics & Telecommunicati, Institute of Engineering & Technology, Devi Ahilya University, Khandwa Road, Indore 452001, India
  • U. R. Bhatt Department of Electronics & Telecommunicati, Institute of Engineering & Technology, Devi Ahilya University, Khandwa Road, Indore 452001, India

Keywords:

AWGN, Dimensionality Reduction, Principal Component Analysis, Rician Channel,

Abstract

Applications in many fields such as the internet of things (IoT), stock market, image compression, food adulteration, wireless physical layer key generation, etc. are becoming progressively complex due to a large number of users and increment in their usage. Data obtained by these applications are in huge amount creating a high computational cost. Further, it is difficult to handle and analyze it. To deal with such problems, dimensionality reduction techniques are used and one of the dimensionality reduction techniques is the Principal Component Analysis (PCA). In this paper, PCA is applied over a wireless Rician channel with AWGN at different SNR. It is concluded that the information content is more in less number of principal components with samples at higher SNR. It is also observed that the different combinations of several groups and elements in the sample space provide a different cumulative percentage of information.

References

Shruti Sehgal, Harpreet Singh, Mohit Agarwal, V. Bhasker, Shantanu, Data analysis using principal component analysis, IEEE, International Conference on Medical Imaging, m-Health and Emerging Communication Systems (MedCom), 2014

Md Shahid Latif, “Principal Component Image Interpretation – A Logical and Statistical Approach’’, IJEDR, Volume 2, Issue 4, 2014, ISSN: 2321-9939

Luhui Lin, Jie Ma, Xiulan Ye, Xiaoli Xu Mechanical fault prediction based on principal component analysis, IEEE International Conference on Information and Automation, 2010

Muhammad Waqar, Hassan Dawood,Muhammad Bilal Shahnawaz, Mustansar Ali Ghazanfar, “Prediction of Stock Market by Principal Component Analysis ”,Ping Guo,2017 13th International Conference on Computational Intelligence and Security (CIS),2017, 17578286

M. Artac, Mobile robot localisation with incremental PCA, 11th IEEE Mediterranean Electrotechnical Conference, 2002

David A. Rusak, Leah M. Brown, and Scott D. Martin, “Classification of Vegetable Oils by Principal Component Analysis of FTIR Spectra’’, Journal of chemical education (J. Chem. Educ.), 2003, 80 (5), Pp 541

Ana-Maria Sevcenco ,Kin Fun Li, “ Principal Component Analysis in Business Intelligence Applications’’2013 Eighth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing, 2013, 13972144

G. K. SinghȦ , N. K. ChauhanḂ , Rajeev KumarĊ and V. YadavaḊ, Grey Relational Analysis Coupled with Principal Component Analysis for Optimization Design of the Machining Parameters in ElectroDischarge Diamond Face Grinding, International Journal of Current Engineering and Technology E-ISSN 2277 – 4106, P-ISSN 2347 – 5161, 2014

Y. Basiouny, M. Arafa,Amany M. Sarhan, “Enhancing Wi-Fi fingerprinting for indoor positioning system using single multiplicative neuron and PCA algorithm,’’ 2017 12th International Conference on Computer Engineering and Systems (ICCES), 2017, 17542818

Guyue Li, Aiqun Hu, Junqing Zhang, Linning Peng, Chen Sun, and Daming Cao, “High-Agreement Uncorrelated Secret Key Generation Based on Principal Component Analysis Preprocessing’’, IEEE Transactions on Communications, Volume: 66, Issue: 7, July 2018, 17916674: Pp 3022 - 3034

Liangjun Hu, Fangyu Zhang, Aiqun Hu, Yu Jiang, Guyue Li, “A key generation scheme for wireless physical layer based on frequency hopping”, 8th International Congress of Information and Communication Technology (ICICT-2018), Volume 131, 2018, Pp 1104-1112

Yu Dai, Jianfeng Guan, Wei Quan, Changqiao Xu, Hongke Zhang, PCA-based dimensionality reduction method for user information in universal network , IEEE 2nd International Conference on Cloud Computing and Intelligence Systems, 2012

K. Keerthi Vasan, B. Surendiran, Dimensionality reduction using Principal Component Analysis for network intrusion detection, Elsevier (Volume 8), September 2016

Ravi Ramamoorthi, Analytic PCA Construction for Theoretical Analysis of Lighting Variability in Images of a Lambertian Object, IEEE transactions on pattern analysis and machine intelligence, 2002

Moussa Hamadache, Dongik Lee, improving signal-to-noise ratio (SNR) for inchoate fault detection based on principal component analysis (PCA), 14th International Conference on Control, Automation and Systems, 2014

Liton Chandra Paul, Abdulla Al Suman , Nahid Sultan, Methodological Analysis of Principal Component Analysis (PCA) Method, IJCEM International Journal of Computational Engineering & Management, Vol. 16 Issue 2, March 2013

Hafiz zia ur Rehman , Sungon Lee, Automatic Image Alignment Using Principal Component Analysis, IEEE Access ( Volume: 6 ), 20 November 2018

Liu Wei-min, Chang Chein-I, Variants of Principal Components Analysis, IEEE International Geoscience and Remote Sensing Symposium, 2007.

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Published

2019-12-15

How to Cite

Upadhyay, R., Soni, A., Panse, P., & Bhatt, U. R. (2019). A Study on Principal Component Analysis over Wireless Channel. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 11(4), 5–9. Retrieved from https://jtec.utem.edu.my/jtec/article/view/5371

Issue

Vol. 11 No. 4: October - December 2019

Section

Articles

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