scholarly journals Source-Channel Codec for a WCDMA Based Multimedia System

2021 ◽  
Author(s):  
Boris Backovic
Keyword(s):  
Forward Error Correction ◽  
Convolutional Code ◽  
Random Noise ◽  
Direct Sequence Spread Spectrum ◽  
Multimedia System ◽  
Compression Algorithms ◽  
Still Image ◽  
Chip Sequencing ◽  
Code Algorithm ◽  
Matlab Programming

The project deals with the operation of a Source-Channel Codec for a WCDMA Based Multimedia System. The system is meant to transfer and receive both digitized speech and still image signals. It uses a part of the WCDMA technology to mix up the transmitted signals throughout the implementation of Direct Sequence Spread Spectrum and Chip Sequencing methodologies. The Walsh code algorithm is used to ensure the orthogonality among different Chip Sequences. On the transmitter side the system first offers the formatting stage where both a speech and a still image signal are digitized. The following stage in the system exhibits a significant degree of data compression applying appropriate compression algorithms: Lempel-Ziv-Welch for the speech signal and Huffman Code Algorithm for the still image. These compression algorithms are implemented in the Source Encoder stage of the system. The system also provides basic FEC (Forward Error Correction) capabilities, using both Linear Block Code and Convolutional Code algorithms introduced in the Channel Encoder stage. The goal of these FEC algorithms is to detect and correct errors during the transmission of data due to the channel imperfections. At the WCMDA stage the two signals are added together forming an aggregated signal that is being transmitted through the channel. On the receiver side a digital demodulator separates the aggregated signal into two signals using the feature of the orthogonality of vectors. Then the Channel Decoder stage follows, where both signals, which have gotten corrupted during the transmission through the channel due to channel imperfections, are recovered. The imperfections in the channel are simulated by random noise that is added to the aggregated signal in the WCDMA stage of the system. The last stage in the system, the Source Decoder stage, deals with the conversion of the received signals from the digital to analog form and reconstruction of the signals in the sense that they can be heard (speech) and seen (still image). Each stage in the system is simulated using MATLAB programming language. The report is formed of three major parts; the theoretical part where the theory behind each stage in the system is explained, the example part where applicable numerical examples are provided and analyzed for better understanding of both the theory and the Matlab code, and the result part where the Matlab results for each stage are analayzed.

scholarly journals Source-Channel Codec for a WCDMA Based Multimedia System

2021 ◽  
Author(s):  
Boris Backovic
Keyword(s):  
Forward Error Correction ◽  
Convolutional Code ◽  
Random Noise ◽  
Direct Sequence Spread Spectrum ◽  
Multimedia System ◽  
Compression Algorithms ◽  
Still Image ◽  
Chip Sequencing ◽  
Code Algorithm ◽  
Matlab Programming

The project deals with the operation of a Source-Channel Codec for a WCDMA Based Multimedia System. The system is meant to transfer and receive both digitized speech and still image signals. It uses a part of the WCDMA technology to mix up the transmitted signals throughout the implementation of Direct Sequence Spread Spectrum and Chip Sequencing methodologies. The Walsh code algorithm is used to ensure the orthogonality among different Chip Sequences. On the transmitter side the system first offers the formatting stage where both a speech and a still image signal are digitized. The following stage in the system exhibits a significant degree of data compression applying appropriate compression algorithms: Lempel-Ziv-Welch for the speech signal and Huffman Code Algorithm for the still image. These compression algorithms are implemented in the Source Encoder stage of the system. The system also provides basic FEC (Forward Error Correction) capabilities, using both Linear Block Code and Convolutional Code algorithms introduced in the Channel Encoder stage. The goal of these FEC algorithms is to detect and correct errors during the transmission of data due to the channel imperfections. At the WCMDA stage the two signals are added together forming an aggregated signal that is being transmitted through the channel. On the receiver side a digital demodulator separates the aggregated signal into two signals using the feature of the orthogonality of vectors. Then the Channel Decoder stage follows, where both signals, which have gotten corrupted during the transmission through the channel due to channel imperfections, are recovered. The imperfections in the channel are simulated by random noise that is added to the aggregated signal in the WCDMA stage of the system. The last stage in the system, the Source Decoder stage, deals with the conversion of the received signals from the digital to analog form and reconstruction of the signals in the sense that they can be heard (speech) and seen (still image). Each stage in the system is simulated using MATLAB programming language. The report is formed of three major parts; the theoretical part where the theory behind each stage in the system is explained, the example part where applicable numerical examples are provided and analyzed for better understanding of both the theory and the Matlab code, and the result part where the Matlab results for each stage are analayzed.

AN IMPROVED EMBEDDED ZEROTREE WAVELET IMAGE CODING METHOD BASED ON COEFFICIENT PARTITIONING USING MORPHOLOGICAL OPERATION

2000 ◽  
Vol 14 (06) ◽  
pp. 795-807 ◽  
Author(s):  
JUNMEI ZHONG ◽  
C. H. LEUNG ◽  
Y. Y. TANG
Keyword(s):  
Image Compression ◽  
Video Coding ◽  
Image Coding ◽  
Experimental Results ◽  
Morphological Operation ◽  
Compression Algorithms ◽  
Still Image ◽  
Coding Method ◽  
Wavelet Image ◽  
Image Compression Algorithm

In recent years, wavelets have attracted great attention in both still image compression and video coding, and several novel wavelet-based image compression algorithms have been developed so far, one of which is Shapiro's embedded zerotree wavelet (EZW) image compression algorithm. However, there are still some deficiencies in this algorithm. In this paper, after the analysis of the deficiency in EZW, a new algorithm based on quantized coefficient partitioning using morphological operation is proposed. Instead of encoding the coefficients in each subband line-by-line, regions in which most of the quantized coefficients are significant are extracted by morphological dilation and encoded first. This is followed by using zerotrees to encode the remaining space which has mostly zeros. Experimental results show that the proposed algorithm is not only superior to the EZW, but also compares favorably with the most efficient wavelet-based image compression algorithms reported so far.

scholarly journals Performance Analysis Of A Cellular System Using C-Ofdm Techniques

2013 ◽  
pp. 48-57
Author(s):  
Lopamudra Swain
Keyword(s):  
Forward Error Correction ◽  
Convolutional Code ◽  
Wireless Channel ◽  
Background Information ◽  
Modulation Scheme ◽  
Carrier System ◽  
Single Carrier ◽  
Rate Transmission ◽  
Trellis Code ◽  
Forward Error

The basic idea of COFDM is to split the modulation samples of incoming data stream onto a large number of carriers instead of modulating a unique carrier. Therefore, COFDM is an effective technique for combating multi-path fading and for highbit- rate transmission over wireless channel. In a single carrier system a frequency Selective fading can cause the entire transmission link to fail, but in an COFDM multi carrier system, only a small percentage of the sub-carriers will be corrupted. Frequency and time interleaving in conjunction with forward error correction coding can then be used to correct for erroneous subcarriers. The background information with the aim to provide an intuitive explanation of our research motivation. C-OFDM is the modulation scheme of choice , as enshrined in International standard for all forms of digital broadcasting both audio and video and including satellite, terrestrial, and cable. In the existing standard the “coding” referred to consists of an inner convolutional code concatenated with an outer R-S code; here in this thesis, we replace the inner code with the coding like space time trellis code for analysis.

scholarly journals Analisis Unjuk Kerja Convolutional Code pada Sistem MIMO MC-DSSS Melalui Kanal Rayleigh Fading

2017 ◽  
Vol 16 (2) ◽  
pp. 66 ◽  
Author(s):  
Kadek Agus Mahabojana Dwi Prayoga ◽  
Ni Made Ary Esta Dewi Wirastuti ◽  
I Gst A. Komang Diafari Djuni Hartawan
Keyword(s):  
Spread Spectrum ◽  
Orthogonal Frequency Division Multiplexing ◽  
Rayleigh Fading ◽  
Convolutional Code ◽  
Multiple Input Multiple Output ◽  
Density Ratio ◽  
Direct Sequence Spread Spectrum ◽  
Noise Power ◽  
Noise Power Spectral Density ◽  
Input Multiple Output

Kombinasi antara sistem MIMO (multiple input multiple output), OFDM (orthogonal frequency division multiplexing), dan spread spectrum serta adanya teknik pengkodean kanal mampu mengurangi efek fading dan error yang terjadi. Penelitian ini bertujuan untuk mengetahui perbandingan performansi dari sistem MIMO MC-DSSS (multi carrier-direct sequence spread spectrum) Uncoded atau tanpa pengkodean kanal dan MIMO MC-DSSS Convolutional Code atau dengan pengkodean kanal Convolutional yang melalui kanal Rayleigh Fading, ditinjau dari nilai dan grafik BER (bit error rate) berbanding Eb/No (energy per bit to noise power spectral density ratio). Penelitian ini menggunakan metode simulasi dengan menggunakan program Matlab R2015a. Hasil dari simulasi didapat unjuk kerja sistem MIMO MC-DSSS dengan Convolutional Code memiliki hasil yang lebih baik dari MIMO MC-DSSS. Pada kanal transmisi Rayleigh Fading untuk mencapi nilai BER sebesar 10-3 pada sistem MIMO MC-DSSS dengan Convolutional Code dibutuhkan Eb/No sebesar -7 dB. Sedangkan pada sistem MIMO MC-DSSS dibutuhkan Eb/No sebesar -3 dB.[turnitin 20%, 7-11-2016]

High Speed Data Transmission Using Coding

2012 ◽  
Vol 229-231 ◽  
pp. 1635-1638
Author(s):  
Yousef Hwegi ◽  
Nasser Hassen
Keyword(s):  
Data Transmission ◽  
High Speed ◽  
Forward Error Correction ◽  
Convolutional Code ◽  
Turbo Code ◽  
System Capacity ◽  
Signal Degradation ◽  
High Speed Data ◽  
Forward Error ◽  
Speed Data Transmission

The relible and fast data transmission over noisy band limitted channels is the basic requirment of digital communication and transmission system. Reliability considerations require that forward error correction techniques be used. This techniques find and correct limitted erros caused by a transport or storage systems. Such coding technique is therefore used to help compensate for signal degradation and provide increase in system capacity and reliability. In this paper, we analyze the performance of three codes which are the Reed Soloman Code, the convolutional code, and turbo code for the same signal that is corrupted by transmission channel. The type of channel considered in this work is the AWGN. For the same message length, the turbo code gives the best performance and the Reed Soloman Code gave the poorest performance when the signal is corrupted by AWGN channel.

Digital Image Restoration in Matlab: A Case Study on Inverse and Wiener Filtering

2018 ◽  
Author(s):  
Mohammad Mahmudur Rahman Khan ◽  
Shadman Sakib ◽  
Rezoana Bente Arif ◽  
Md. Abu Bakr Siddique
Keyword(s):  
Color Image ◽  
Random Noise ◽  
Wiener Filtering ◽  
Inverse Filtering ◽  
Degradation Model ◽  
Blurred Image ◽  
Blurred Images ◽  
Blurring Effect ◽  
Matlab Programming

In this paper, at first, a color image of a car is taken. Then the image is transformed into a grayscale image. After that, the motion blurring effect is applied to that image according to the image degradation model described in equation 3. The blurring effect can be controlled by a and b components of the model. Then random noise is added in the image via Matlab programming. Many methods can restore the noisy and motion blurred image; particularly in this paper Inverse filtering as well as Wiener filtering are implemented for the restoration purpose. Consequently, both motion blurred and noisy motion blurred images are restored via Inverse filtering as well as Wiener filtering techniques and the comparison is made among them.

scholarly journals A Study on Digital Image Restoration Filters

2020 ◽  
pp. 28-33
Author(s):  
Shaila Banu SK ◽  
Sivaparvathi B ◽  
Munwar Ali SK ◽  
Raheema SK ◽  
Sailaja R ◽  
...  
Keyword(s):  
Color Image ◽  
Random Noise ◽  
Wiener Filtering ◽  
Grayscale Image ◽  
Inverse Filtering ◽  
Degradation Model ◽  
Blurred Image ◽  
Blurring Effect ◽  
Matlab Programming ◽  
Image Degradation Model

In this paper, at first a color image is taken Then the image is transformed into a grayscale image. After that, the motion blurring effect is applied to that image according to the image degradation model described in equation 3.the blurring effect can be controlled by a and b components of the model. Then random noise is added in the image via MATLAB programming. Many methods can restore the noisy and motion blurred image: particularly in this paper inverse filtering as well as wiener filtering are implemented for the restoration purpose consequently, both motion blurred and noisy motion blurred image are restored via inverse filtering as well as wiener filtering techniques and the comparison is made among them.

scholarly journals Area and Energy Efficient QCA Based Compact Serial Concatenated Convolutional Code Encoder

2022 ◽  
Vol 2161 (1) ◽  
pp. 012025
Author(s):  
B.S. Premananda ◽  
T.N. Dhanush ◽  
Vaishnavi S. Parashar
Keyword(s):  
Energy Dissipation ◽  
Error Correction ◽  
Forward Error Correction ◽  
Convolutional Code ◽  
Internal Clock ◽  
Random Errors ◽  
Clock Generation ◽  
Convolutional Coding ◽  
External Clock ◽  
Forward Error

Abstract Quantum-dot Cellular Automata (QCA) is a transistor-less technology known for its low power consumption and higher clock rate. Serial Concatenated Convolutional Coding (SCCC) encoder is a class of forward error correction. This paper picturizes the implementation of the outer encoder as a (7, 4, 1) Bose Chaudhary Hocquenghem encoder that serves the purpose of burst error correction, a pseudo-random inter-leaver used for permuting of systematic code words and finally the inner encoder which is used for the correction of random errors in QCA. Two different architectures of the SCCC encoder have been proposed and discussed in this study. In the proposed two architectures, the first based on external clock signals whereas the second based on internal clock generation. The sub-blocks outer encoder, pseudo-random inter-leaver and inner encoder of the SCCC encoder are optimized, implemented and simulated using QCADesigner and then integrated to design a compact SCCC encoder. The energy dissipation is computed using QCADesigner-E. The proposed SCCC encoder reduced the total area by 46% and energy dissipation by 50% when compared to the reference SCCC encoder. The proposed encoders are more efficient in terms of cell count, energy dissipation and area occupancy respectively.

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