Performance analysis of a finite radon transform in OFDM system under different channel models

2015 ◽  
Author(s):  
Sameer A. Dawood ◽  
F. Malek ◽  
M. S. Anuar ◽  
Rashid A. Fayadh ◽  
Farrah Salwani Abdullah
Keyword(s):  
Performance Analysis ◽  
Radon Transform ◽  
Ofdm System ◽  
Channel Models ◽  
Finite Radon Transform

scholarly journals A Radon Slantlet Transforms Based OFDM System Design and Performance Simulation under Different Channel Conditions

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Abbas Hasan Kattoush
Keyword(s):  
Radon Transform ◽  
Spectral Efficiency ◽  
Fading Channel ◽  
Orthogonal Frequency Division Multiplexing ◽  
Additive White Gaussian Noise ◽  
Mapping Technique ◽  
Intercarrier Interference ◽  
Ofdm Systems ◽  
Ofdm System ◽  
Channel Parameters

Due to its good orthogonality, slantlet transform (SLT) is used in orthogonal frequency division multiplexing (OFDM) systems to reduce intersymbol interference (ISI) and intercarrier interference (ICI). This eliminates the need for cyclic prefix (CP) and increases the spectral efficiency of the design. Finite Radon transform (FRAT) mapper has the ability to increase orthogonality of subcarriers, is nonsensitive to channel parameters variations, and has a small constellation energy compared with conventional fast-Fourier-transform- (FFT-) based OFDM. It is also able to work as a good interleaver, which significantly reduces the bit error rate (BER). In this paper both FRAT mapping technique and SLT modulator are implemented in a new design of an OFDM system. The new structure was tested and compared with conventional FFT-based OFDM, Radon transform-based OFDM, and SLT-based OFDM for additive white Gaussian noise (AWGN) channel, flat fading channel (FFC), and multipath selective fading channel (SFC). Simulation tests were generated for different channel parameters values. The obtained results showed that the proposed system has increased the spectral efficiency, reduced ISI and ICI, and improved BER performance compared with other systems.

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