Zhu Anshi
Ordnance Engineering College

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Analysis on Channel Capacity of Transform Domain Communication System Wei Naiqi; Chen Zili; Lv Junwei; Zhu Anshi
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 4: April 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

Transform Domain Communication System (TDCS) has caught attention for its characteristics of flexible spectrum application, excellent anti-interference performance and low interception probability. Analysis on channel capacity is one aspect of important basic theory research for TDCS. The fundamental principle of TDCS is studied at first. Then the channel capacity model of TDCS is deduced and built on the background of Gaussian white noise channel with typical interference. The channel capacity of TDCS under different spectrum sensing methods is investigated on the basis of the model. The research indicates that the spectrum sensing methods based on AR model and wavelet-packet transform make more improvement for TDCS channel capacity. Therefore, from the perspective of maximizing TDCS channel capacity, the spectrum sensing methods based on AR model and wavelet-packet transform can be adopted. DOI : http://dx.doi.org/10.11591/telkomnika.v12i4.4112
Research of Adaptive Resolution Spectrum Sensing Method Based on Discrete Wavelet Packet Transform Wei Naiqi; Chen Zili; Zhu Anshi
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: February 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

Spectrum sensing is the precondition of the realization of cognitive radio. In order to achieve efficient multi-resolution spectrum sensing, and find the available spectrum hole quickly, it proposes a variable resolution adaptive frequency spectrum energy sensing method based on discrete wavelet packet transform (DWPT). The method applied hierarchical decomposition and threshold denoising characteristic of wavelet packet transform, and solved the problem of subband sort disorder in wavelet packet decomposition process; it can eliminate the influence of uncertainty noise on detection performance, effectively. It also can reduce the computational complexity according to demand of selection resolution and perception band. The simulation results and its analysis show that the proposed method has advantages of high precision, simple arithmetic and fine flexibility, etc. The method is adapted to fast sensing in the cognitive radio environment. DOI : http://dx.doi.org/10.11591/telkomnika.v12i2.3971