Print ISSN: 1811-9212

Online ISSN: 2617-3352

Keywords : BPSK


Implement Wireless Transceiver System Based On Convolutional Coding; Aided by Soft-Bit Decoding

Israa Hazem Ali

IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2018, Volume 18, Issue 1, Pages 49-55

The main aim with any modern digital communication systems is to provide error free data transmission. To achieve this aim, error control coding techniques are applied with these systems. In this paper, digital communication system was implemented based on convolutional code, aided by soft-bit decoding for error free transmission. Fixed length source encoder was represented with this work, and statistically described the output of the source encoder and save this description at the receiver as a priori knowledge about the source encode. These a priori knowledge were exploited at the receiver to improve the performance of the proposed system in term of BER by conceal the errors occurred through the transmission of information over AWGN channel, aided the convolutional encoder. Significant improvements were obtained with this proposed system.

Joint Hybrid Compression Techniques and Convolutional Coding for Wireless Lossy Image Transmissions

Salah Al-iesawi; Maha Abd Rajab; Ahmed I. A

IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2015, Volume 15, Issue 1, Pages 80-99

Abstract – This paper demonstrates the effect of color image transmission through AWGN channel using binary phase shift key modulation (BPSK) system and transmission of compressed color image through AWGN. On the other hand, the transmission consumes a large amount of channel and needs the processing, therefore utilizes compression techniques to reduce the size of the original color image to facilitate the transmission compressed color image through AWGN and to obtain the channel optimization. In this paper, a simple hybrid lossy color image compression transmission through AWGN using convolutional coding with Viterbi decoding system is proposed. It is based on combining effective techniques, started by wavelet transform that decompose the image signal followed by polynomial approximation model of linear based to compress approximation image band. The error caused by applying polynomial approximation is coded using bit plane slice coding, whereas the absolute moment block truncation coding exploited to coded the detail sub bands. Then, the compressed information encoded using LZW, run length coding and Huffman coding techniques, the compressed information is entered to the channel coding to coded the information using convolutional coding and modulation using BPSK to transmit through channel and added AWGN, the received signal is demodulated and decoded using Viterbi decoding, the result compressed data passed to source decoding to reconstruct the compressed image. The test results indicated that the proposed system can produce a balance between the compression performance and preserving the image quality, and also simulations results observed that with increase in signal to noise ratio (SNR) values the bit error rate (BER) values decrease.