MC CDMA Paper Reduction Using Discrete Wavelet Transform and Companding on Rayleigh Fading Channel

2012 ◽  
Vol 2 (6) ◽  
pp. 244-247
Author(s):  
Rashmi Pant ◽  
◽  
Srashti Vyas
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Fading Channel ◽  
Rayleigh Fading ◽  
Rayleigh Fading Channel ◽  
Discrete Wavelet

scholarly journals Improving MIMO-OFDM Performance with Convolutional Coding and Discrete Wavelet Transform

2020 ◽  
pp. 299-305
Author(s):  
Saad S. Hreshee ◽  
◽  
Qais K. Al-Gayem
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Fading Channel ◽  
Orthogonal Frequency Division Multiplexing ◽  
Rayleigh Fading ◽  
Rician Fading ◽  
Discrete Wavelet ◽  
Ofdm System ◽  
Convolutional Coding ◽  
Mimo Ofdm

This paper presents a new way to improve the performance of MIMO-OFDM (multiple input multiple output - orthogonal frequency division multiplexing) by reducing the Bit Error Rate (BER) using both Convolutional Coding (CC) and discrete wavelet transform (DWT). In this Paper, OFDM system was simulated and studied with three models, SISO-OFDM, MISO-OFDM and MIMO-OFDM. The final system (MIMO-OFDM) has been improved by using CC at a coding rate 1/2 and using a DWT instead of FFT and then using both CC and DWT. The communication channels used in the study are Rician and Rayleigh fading channels and the modulation technique is Binary Phase-Shift Keying (BPSK) with 64 number of carrier frequencies. The results showed that the use of both convolutional coding and discrete wavelet transform in the MIMO-OFDM system reduces the bit energy to the intensity of noise energy (Eb/N0) by 3.4 dB as the Rayleigh fading channel is used and 4.6 dB as the Rician fading channel is used when BER=10-3. The results were obtained by modeling in the MATLAB program.

Improving Space Localization Properties of the Discrete Wavelet Transform

Informatica ◽  
2013 ◽  
Vol 24 (4) ◽  
pp. 657-675
Author(s):  
Jonas Valantinas ◽  
Deividas Kančelkis ◽  
Rokas Valantinas ◽  
Gintarė Viščiūtė
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Discrete Wavelet ◽  
Space Localization

An Adaptive Binarization Method for Cost-efficient Document Image System in Wavelet Domain

2020 ◽  
Vol 64 (3) ◽  
pp. 30401-1-30401-14 ◽  
Author(s):  
Chih-Hsien Hsia ◽  
Ting-Yu Lin ◽  
Jen-Shiun Chiang
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Document Image ◽  
Background Information ◽  
Raspberry Pi ◽  
Discrete Wavelet ◽  
Image System ◽  
Low Frequencies ◽  
Cost Efficient ◽  
Binarization Method

Abstract In recent years, the preservation of handwritten historical documents and scripts archived by digitized images has been gradually emphasized. However, the selection of different thicknesses of the paper for printing or writing is likely to make the content of the back page seep into the front page. In order to solve this, a cost-efficient document image system is proposed. In this system, the authors use Adaptive Directional Lifting-Based Discrete Wavelet Transform to transform image data from spatial domain to frequency domain and perform on high and low frequencies, respectively. For low frequencies, the authors use local threshold to remove most background information. For high frequencies, they use modified Least Mean Square training algorithm to produce a unique weighted mask and perform convolution on original frequency, respectively. Afterward, Inverse Adaptive Directional Lifting-Based Discrete Wavelet Transform is performed to reconstruct the four subband images to a resulting image with original size. Finally, a global binarization method, Otsu’s method, is applied to transform a gray scale image to a binary image as the output result. The results show that the difference in operation time of this work between a personal computer (PC) and Raspberry Pi is little. Therefore, the proposed cost-efficient document image system which performed on Raspberry Pi embedded platform has the same performance and obtains the same results as those performed on a PC.

SoS models for Rayleigh fading channel

2014 ◽  
Author(s):  
Y.H. Ding ◽  
R.J. Tian ◽  
J.S. Tao ◽  
X.R. Ma ◽  
X.C. Wang ◽  
...  
Keyword(s):  
Fading Channel ◽  
Rayleigh Fading ◽  
Rayleigh Fading Channel
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