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Improved Quantization in Multiple Description Coding by Correlating Transforms
KTH, Superseded Departments, Signals, Sensors and Systems. (Communication Theory)
KTH, Superseded Departments, Signals, Sensors and Systems. (Communication Theory)
KTH, Superseded Departments, Signals, Sensors and Systems. (Communication Theory)ORCID iD: 0000-0002-7926-5081
2004 (English)In: 2004 IEEE 6th Workshop on Multimedia Signal Processing, 2004, 486-489 p.Conference paper, Published paper (Refereed)
Abstract [en]

The objective with Multiple Description Coding (MDC) is to code one source of data into multiple bitstreams. The coding is done in such a way that multiple levels of quality is achieved. This means that even if one or a few of the bitstreams are lost, the received bits should make it possible to get an approximated version of the original data. One way to do this is to use pairwise correlating transforms which will introduce correlation between the bitstreams. This correlation can be used in order to get an estimate of a lost stream. In this paper a new approach for MDC using pairwise correlating transforms is presented. In this approach, contrary to previous work, quantization of the source data is performed after the data has been transformed. This makes it possible to improve the shape of the quantization cells and to tailor these to the employed transform. We demonstrate that this offers a substantial performance gain compared with previous approaches to MDC using pairwise correlating transforms.

Place, publisher, year, edition, pages
2004. 486-489 p.
Keyword [en]
Approximation theory, Communication systems, Correlation methods, Image quality, Network protocols, Optimization, Packet networks, Probability, Bitstreams, Correlating transforms, Multiple description coding (MDC), TCP protocol
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:kth:diva-8448DOI: 10.1109/MMSP.2004.1436601ISI: 000224752800122Scopus ID: 2-s2.0-13344259922ISBN: 0-7803-8578-0 (print)OAI: oai:DiVA.org:kth-8448DiVA: diva2:13772
Conference
6th IEEE Workshop on Multimedia Signal Processing. Siena, ITALY. SEP 29-OCT 01, 2004
Note
QC 20100920Available from: 2008-05-15 Created: 2008-05-15 Last updated: 2012-01-09Bibliographically approved
In thesis
1. Source-Channel Coding in Networks
Open this publication in new window or tab >>Source-Channel Coding in Networks
2008 (English)Doctoral thesis, comprehensive summary (Other scientific)
Abstract [en]

The aim of source coding is to represent information as accurately as possible using as few bits as possible and in order to do so redundancy from the source needs to be removed. The aim of channel coding is in some sense the contrary, namely to introduce redundancy that can be exploited to protect the information when being transmitted over a nonideal channel. Combining these two techniques leads to the area of joint source-channel coding which in general makes it possible to achieve a better performance when designing a communication system than in the case when source and channel codes are designed separately. In this thesis four particular areas in joint source-channel coding are studied: analog (i.e. continuous) bandwidth expansion, distributed source coding over noisy channels, multiple description coding (MDC) and soft decoding.

A general analog bandwidth expansion code based on orthogonal polynomials is proposed and analyzed. The code has a performance comparable with other existing schemes. However, the code is more general in the sense that it is implementable for a larger number of source distributions.

The problem of distributed source coding over noisy channels is studied. Two schemes are proposed and analyzed for this problem which both work on a sample by sample basis. The first code is based on scalar quantization optimized for a certain channel characteristics. The second code is nonlinear and analog.

Two new MDC schemes are proposed and investigated. The first is based on sorting a frame of samples and transmitting, as side-information/redundancy, an index that describes the resulting permutation. In case that some of the transmitted descriptors are lost during transmission this side information (if received) can be used to estimate the lost descriptors based on the received ones. The second scheme uses permutation codes to produce different descriptions of a block of source data. These descriptions can be used jointly to estimate the original source data. Finally, also the MDC method multiple description coding using pairwise correlating transforms as introduced by Wang et al. is studied. A modi fication of the quantization in this method is proposed which yields a performance gain.

A well known result in joint source-channel coding is that the performance of a communication system can be improved by using soft decoding of the channel output at the cost of a higher decoding complexity. An alternative to this is to quantize the soft information and store the pre-calculated soft decision values in a lookup table. In this thesis we propose new methods for quantizing soft channel information, to be used in conjunction with soft-decision source decoding. The issue on how to best construct finite-bandwidth representations of soft information is also studied.

Place, publisher, year, edition, pages
Stockholm: KTH, 2008. viii, 44 p.
Series
Trita-EE, ISSN 1653-5146 ; 2008:028
Keyword
source coding, channel coding, joint source-channel coding, bandwidth expansion, distributed source coding, multiple description coding, soft decoding
National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-4751 (URN)978-91-7415-002-5 (ISBN)
Public defence
2008-06-03, F3, KTH, Lindstedtsv 25, Stockholm, 13:15
Opponent
Supervisors
Note
QC 20100920Available from: 2008-05-15 Created: 2008-05-15 Last updated: 2010-09-20Bibliographically approved
2. Source-channel coding for wireless networks
Open this publication in new window or tab >>Source-channel coding for wireless networks
2006 (English)Licentiate thesis, comprehensive summary (Other scientific)
Abstract [en]

The aim of source coding is to represent information as accurately as possible using as few bits as possible and in order to do so redundancy from the source needs to be removed. The aim of channel coding is in some sense the contrary, namely to introduce redundancy that can be exploited to protect the information when being transmitted over a nonideal channel. Combining these two techniques leads to the area of joint source–channel coding which in general makes it possible to achieve a better performance when designing a communication system than in the case when source and channel codes are designed separately. In this thesis two particular areas in joint source–channel coding are studied: multiple description coding (MDC) and soft decoding. Two new MDC schemes are proposed and investigated. The first is based on sorting a frame of samples and transmitting, as side-information/redundancy, an index that describes the resulting permutation. In case that some of the transmitted descriptors are lost during transmission this side information (if received) can be used to estimate the lost descriptors based on the received ones. The second scheme uses permutation codes to produce different descriptions of a block of source data. These descriptions can be used jointly to estimate the original source data. Finally, also the MDC method multiple description coding using pairwise correlating transforms as introduced by Wang et al is studied. A modification of the quantization in this method is proposed which yields a performance gain. A well known result in joint source–channel coding is that the performance of a communication system can be improved by using soft decoding of the channel output at the cost of a higher decoding complexity. An alternative to this is to quantize the soft information and store the pre-calculated soft decision values in a lookup table. In this thesis we propose new methods for quantizing soft channel information, to be used in conjunction with soft-decision source decoding. The issue on how to best construct finite-bandwidth representations of soft information is also studied.

Place, publisher, year, edition, pages
Stockholm: KTH, 2006. vi, 31 p.
Series
Trita-EE, ISSN 1653-5146 ; 2006:009
Keyword
Source coding, channel coding, joint source-channel coding, multiple description coding, soft decoding, permutation codes
National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-3912 (URN)
Presentation
2006-04-11, Sal Q2, KTH, Osquldas väg 10, Stockholm, 13:00
Opponent
Supervisors
Note
QC 20101124Available from: 2006-04-07 Created: 2006-04-07 Last updated: 2010-11-24Bibliographically approved

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