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Sharma, Chetna
- Testbed Implementation of Multi Dimensional Spectrum Sensing Schemes for Cognitive Radio
Abstract Views :180 |
PDF Views:2
Authors
Affiliations
1 Department of Electronics and Communication Engineering, Rajarshi Shahu College of Engineering, IN
2 Department of Electronics and Telecommunication Engineering, Pune Institute of Computer Technology, IN
1 Department of Electronics and Communication Engineering, Rajarshi Shahu College of Engineering, IN
2 Department of Electronics and Telecommunication Engineering, Pune Institute of Computer Technology, IN
Source
ICTACT Journal on Communication Technology, Vol 7, No 2 (2016), Pagination: 1289-1294Abstract
Cognitive Radio (CR) is a promising technology to exploit the underutilized spectrum. Spectrum sensing is one of the most important components for the establishment of cognitive radio system. Spectrum sensing allows the secondary users (SUs) to detect the presence of the primary users (PUs). The aim of this work is to create a CR environment to study the spectrum sensing methods using Universal software radio Peripheral (USRP) boards. In this paper a novel method of estimation of spectrum opportunities in multiple dimensions especially the space and the angle dimensions are carried out on USRP boards. This paper typically provides the experimental results carried out in an indoor wireless environment. To enhance the sensing performance the space dimension is firstly studied using spatial diversity of the cooperative SUs. Secondly the receiver diversity is analyzed using multiple antennas to enhance the error performance of the wireless system. The spectrum usage is also determined in the angle dimension by investigating the direction of the dominant signals using MUSIC algorithm.Keywords
Cognitive Radio, Multi-Dimensional Sensing, Diversity, USRP, MUSIC Algorithm.
- Performance Evaluation and Comparative Analysis of Watermarking Algorithm Based on Adaptive Prediction Method
Abstract Views :187 |
PDF Views:1
Authors
Chetna Sharma
1,
Neeraj Jain
1
Affiliations
1 Department of Electronics and Communication Engineering, Modern Institute of Technology & Research Centre, Alwar, IN
1 Department of Electronics and Communication Engineering, Modern Institute of Technology & Research Centre, Alwar, IN
Source
ICTACT Journal on Image and Video Processing, Vol 9, No 2 (2018), Pagination: 1876-1881Abstract
Now a days digital watermarking appeared as a solution for copyright detection, protection and maintenance of important data. This paper deals with a new reversible watermarking algorithm based on adaptive prediction error expansion, which can recover original image after extracting the hidden data. Embedding capacity of such algorithm depend on the prediction accuracy of the predictor. The method can embed secret data into 3×3 image block order by exploiting the pixel redundancy within each block. It has been observed that proposed method of reversible watermarking provide much better results in terms of Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) in comparison to existing literature.Keywords
Reversible Image Watermarking, Adaptive Prediction, Peak Signal to Noise Ratio (PSNR).References
- S. Kumar and T.P. Singh, “A Review of Digital Watermarking, Applications and its Techniques”, International Journal of Computer and Organization Trends, Vol. 4, No. 4, pp. 19-22, 2014.
- M. Durvey and D. Satyarthi, “A Review Paper on Digital Watermarking”, International Journal of Emerging Trends and Technology in Computer Science, Vol. 3, No. 4, pp. 99-105, 2014.
- R. Li, O. Au, C. Yuk and S. Yip, “Enhanced Image Transcoding using Reversible Data Hiding”, Proceedings of IEEE International Symposium on Circuits and Systems, pp. 1273-1276, 2007.
- J. Feng, I. Lin, C. Tsai and Y. Chu, “Reversible Watermarking: Current Status and Key Issues”, International Journal of Network Security, Vol. 2, No. 3, pp. 161-171, 2006.
- Y. Qi and L. Liu, “Reversible Watermarking Algorithm based on Prediction Error Expansion for Color Image”, Proceedings of International Conference on Image Processing, pp. 102-106, 2017.
- K. Pawar, B. Pillai and S.K. Mishra, “Conditional Local Prediction Based Image Watermarking”, International Journal of Engineering Technology and Applied Science, Vol. 2, No. 3, pp. 1-8, 2016.
- Jinal H. Mehta and Vishakha Kelkar, “Comparison of Reversible Watermarking using Prediction Error Expansion and Prediction Error Expansion Considering Region of Interest for Medical Images”, Proceedings of IEEE 2nd International Conference for Convergence in Technology, 2017.
- S. Yi, Y. Zhou and Z. Hua, “Reversible Data Hiding in Encrypted Images using Adaptive Block-Level Prediction-Error Expansion”, Signal Processing: Image Communication, Vol. 64, pp. 78-88, 2018.
- M. Chen, Z. Chen, X. Zeng and Z. Xiong “Reversible Image Watermarking based on Full Context Prediction”, Proceedings of International Conference on Image Processing, pp. 4253-4256, 2009.
- W. Zhang, K. Ma and N. Yu, “Reversibility Improved Data Hiding in Encrypted Images”, Signal Processing, Vol. 94, pp. 118-127, 2014
- Mahsa Afsharizadeh and Majid Mohammadi,“Prediction-based Reversible Image Watermarking using Artificial Neural Networks”, Turkish Journal of Electrical Engineering and Computer Sciences, Vol. 24, pp. 896-910, 2016.
- C. Vinoth Kumar and V. Natarajan, “Hybrid Local Prediction Error Based Difference Expansion Reversible Watermarking for Medical Images”, Computers and Electrical Engineering, Vol. 53, pp. 333-345, 2015.
- Xinlu Gui, Xiaolong Li and Bin Yang, “A High Capacity Reversible Data Hiding Scheme Based on generalized Prediction Error Expansion and Adaptive Embedding”, Signal Processing, Vol. 98, pp. 370-380, 2014.
- Raheleh Khorsand Movaghar and Hossein Khaleghi Bizaki, “A New Approach for Digital Image Watermarking to Predict Optimal Blocks using Artificial Neural Networks”, Turkish Journal of Electrical Engineering and Computer Science, Vol. 25, pp. 644-654,2017.
- Zahra Pakdaman, Saeid Saryazdi and Hossein Nezamabadi-Pour, “A Prediction based Reversible Image Watermarking in Hadamard Domain”, Multimedia Tools and Application, Vol. 76, No. 6, pp. 1-29, 2016.