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Robust Image Communication over Fading Channel

Harsh Ahuja, Anushree Pachegaokar

Abstract


Communication across noisy channels is extremely challenging. Various techniques are used to mitigate the adverse effect of noise, such as Error Control Coding (ECC), Space-Time Coding (STC), Spread Spectrum Modulation, Multi-carrier Modulation, etc. In this paper, we have considered image communication using Forward Error Correction (FEC) techniques like Hamming code, Cyclic code, Reed-Muller (RM) code, and Convolutional code along with Binary Phase Shift Keying (BPSK) over Rayleigh Fading channel. A simple communication model consisting of a data source in the form of MATLAB’s inbuilt grayscale images, Channel Encoder and Decoder, BPSK Modulator and Demodulator along with a complex Fading channel is built in the MATLAB software and can also be implemented on a low power hardware. A theoretical background on the above mentioned ECC techniques has been provided for comparative analysis. The transmitted grayscale images are recovered back using ECC techniques at constant SNR values of 10 dB and 15 dB to observe the effect of complex Gaussian noise i.e., Fading on the recovered image which is present as Impulse noise in the image. The results are presented in terms of Mean Square Error (MSE) versus Signal to Noise Ratio (SNR) and are simulated in MATLAB. We have also compared the performance of the above-mentioned coding techniques and concluded that Convolutional code is far more robust compared to any of the Block codes in case of transmitting large data streams majorly in applications like wired or wireless image communication. However, the computational complexity of Convolutional code exponentially increases with the length of the code

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References


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DOI: https://doi.org/10.37591/jscrs.v7i2.1649

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