XX. Processing and Transmission of Information

Silesian University of Technology, 2006

Academic textbook. This book is designated primarily for the third or fourth year student. It is assumed that students have some understanding of freshman calculus (matrix and polynomial algebra) and elementary probability. The major results of the theory are quite subtle and abstract, and to make them easy to comprehend numerous examples have been provided. The book does not contain proofs of theorems, as they can be found in many, commonly available books dealing with the same subject. On the other hand all the theorems and definitions are illustrated by many practical examples. The book consists of seven parts.

Electronics and Power, 1984

Digital signals, such as digitized television signals, are subjected to a source coding step followed by a channel mapping step. The source coding step causes the televi sion signal to be represented by two or more data streams while, in the channel mapping step, the map ping is such that the data elements of the various data streams have differing probabilities of being errone ously detected at the receiver. In preferred embodi ments, a first one of the aforementioned data streams carries components of the overall television signal which are regarded as the most important-for example the audio, the framing information, and the vital por tions of the video information, such as motion compen sation information-and that data stream is mapped such that its data elements have the lowest probability of error. A second one of the data streams carries com

IEEE Transactions on Information Theory, 1998

An overview of the many practical applications of channel coding theory in the past 50 years is presented. The following application areas are included: deep space communication, satellite communication, data transmission, data storage, mobile communication, file transfer, and digital audio/video transmission. Examples, both historical and current, are given that typify the different approaches used in each application area. Although no attempt is made to be comprehensive in our coverage, the examples chosen clearly illustrate the richness, variety, and importance of error-control coding methods in modern digital applications.

This thesis presents the results of an investigation into the transmission of coded or compressed digital video information over communications networks. Practical networks and transmission media have limitations in the “Quality of Service” that they can provide to transmitted data. The aim of this thesis is to examine the effect of Quality of Service limitations on the transmission of coded digital video and to investigate new techniques by which video quality can be improved in the presence of transmission impairments. The video coding algorithms are chosen from widely used International Standards for video coding and transmission. The effects of Quality of Service limitations during transmission of coded video are investigated experimentally. Based on the results of these experiments, several different techniques to improve the quality of coded video are proposed and tested. These techniques include video rate control algorithms, scalable or layered coding as a means of prioritising selected components of coded video and modifications to the structure of coded video frames in order to minimise the propagation of errors. Errors are introduced into coded video sequences and it is shown that their effects depend on the position of the error in the sequence. The error models include pseudorandom bit errors and cell errors as well as errors due to the User Network Interface in an Asynchronous Transfer Mode network. Prioritisation of selected components in coded video is investigated, by splitting coded video into several layers or by modifying the frequency of resynchronisation markers depending on the picture class of each video frame. The visual impact of transmission errors can be reduced in this way. The effect of encoding parameters (including quantizer scale, slice resynchronisation interval and intraframe interval) on the bit rate of encoded video is quantified. A modified rate control algorithm that jointly controls quantization and intraframe interval is implemented and is shown to have the potential to improve the visual quality of constant bit rate coded video. The results of these experimental investigations are discussed and evaluated in the context of a complete digital video communication system.

In this work we explore possibilities for coding and decoding tailor-made for mean squared error evaluation of error in contexts such as image transmission. To do so, we introduce a loss function that expresses the overall performance of a coding and decoding scheme for discrete channels and that exchanges the usual goal of minimizing the error probability to that of minimizing the expected loss. In this environment we explore the possibilities of using ordered decoders to create a message-wise unequal error protection (UEP), where the most valuable information is protected by placing in its proximity information words that differ by a small valued error. We give explicit examples, using scale-of-gray images, including small-scale performance analysis and visual simulations for the BSMC.

IEEE Communications Magazine, 2000

In any system that handles large amounts of data, uncorrected and undetected errors can degrade performance, response time, and possibly increase the need for intervention by human operators Aprll 4987-Vol. 25, No. 4 IEEE Communlcatlonr Magazine E rror Control is an area of increasing importance in communications. This is partly because the issue of data integrity is becoming increasingly important. There is downward pressure on the allowable error rates for communications and mass storage systems as bandwidths and volumes of data increase. Certain data cannot be wrong; for example, no one can be complacent about the effect of an undetected data error on a weapons control system. More generally, in any system which handles large amounts of data, uncorrected and undetected errors can degrade performance, response time, and possibly increase the need for intervention by human operators.