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Source-Channel Coding in Networks
KTH, School of Electrical Engineering (EES), Communication Theory.
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 [en]
source coding, channel coding, joint source-channel coding, bandwidth expansion, distributed source coding, multiple description coding, soft decoding
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:kth:diva-4751ISBN: 978-91-7415-002-5 (print)OAI: oai:DiVA.org:kth-4751DiVA: diva2:13774
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
List of papers
1. Polynomial Based Analog Source-Channel Codes
Open this publication in new window or tab >>Polynomial Based Analog Source-Channel Codes
2009 (English)In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 57, no 9, 2600-2606 p.Article in journal (Refereed) Published
Abstract [en]

In many communication applications one is interested in transmitting a time-discrete analog-valued (i.e. continuous alphabet) source over a time-discrete analog channel. We study this problem in the case of bandwidth expansion, in the sense that one source sample, X, is transmitted over N orthogonal channels. An analog source-channel code based on orthogonal polynomials is proposed and analyzed. The code can be generated using a Gram-Schmidt procedure, to fit virtually any source distribution.

Keyword
Modulation, nonlinear functions, source coding, channel coding, error correction
National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-8443 (URN)10.1109/TCOMM.2009.5281750 (DOI)000269798600020 ()2-s2.0-70350407185 (Scopus ID)
Note

QC 20100917. Uppdaterad från submitted till published (20100917).

Available from: 2008-05-15 Created: 2008-05-15 Last updated: 2017-06-14Bibliographically approved
2. Distributed Quantization over Noisy Channels
Open this publication in new window or tab >>Distributed Quantization over Noisy Channels
2009 (English)In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 57, no 6, 1693-1700 p.Article in journal (Refereed) Published
Abstract [en]

The problem of designing simple and energyefficient sensor nodes in a wireless sensor network is considered from a joint source-channel coding perspective. An algorithm for designing distributed scalar quantizers for orthogonal channels is proposed and evaluated. In particular the cases of the binary symmetric channel as well as the additive white Gaussian noise channel are studied. It is demonstrated that correlation between sources can be useful in order to reduce quantization distortion as well as protecting data when being transmitted over nonideal channels. It is also demonstrated that the obtained system is robust against channel SNR mismatch.

Place, publisher, year, edition, pages
IEEE Communications Society, 2009
Keyword
Source coding, quantization, channel coding, correlation
National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-8444 (URN)10.1109/TCOMM.2009.06.070482 (DOI)000266990500026 ()2-s2.0-67650675055 (Scopus ID)
Note
QC 20100908. Uppdaterad från Accepted till Published (20100908)Available from: 2008-11-27 Created: 2008-11-27 Last updated: 2011-12-27Bibliographically approved
3. Nonlinear Coding and Estimation for Correlated Data in Wireless Sensor Networks
Open this publication in new window or tab >>Nonlinear Coding and Estimation for Correlated Data in Wireless Sensor Networks
2009 (English)In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 57, no 10, 2932-2939 p.Article in journal (Refereed) Published
Abstract [en]

The problem of designing simple and energy-efficient nonlinear distributed source-channel codes is considered. By demonstrating similarities between this problem and the problem of bandwidth expansion, a structure for source-channel codes is presented and analyzed. Based on this analysis an understanding about desirable properties for such a system is gained and used to produce an explicit source-channel code which is then analyzed and simulated. One of the main advantages of the proposed scheme is that it is implementable for many sources, contrary to most existing nonlinear distributed source-channel coding systems.

Place, publisher, year, edition, pages
IEEE Communications Society, 2009
Keyword
Source coding, quantization, channel coding, correlation
National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-8445 (URN)10.1109/TCOMM.2009.10.080230 (DOI)000270908700020 ()2-s2.0-70350614010 (Scopus ID)
Note
QC 20100917. Uppdaterad från submitted till published (20100917).Available from: 2008-05-15 Created: 2008-05-15 Last updated: 2011-12-27Bibliographically approved
4. Sorting-Based Multiple Description Quantization
Open this publication in new window or tab >>Sorting-Based Multiple Description Quantization
2006 (English)In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 54, no 9, 1521-1526 p.Article in journal (Refereed) Published
Abstract [en]

We introduce a new method for multiple description quantization (MDQ), based on sorting a frame of samples and transmitting, as side-information/redundancy, an index that describes the resulting permutation. The sorting-based approach has a similar performance to multiple description scalar quantization and a flexible structure, providing straightforward implementation of multidimensional MDQ.

Place, publisher, year, edition, pages
IEEE Communications Society, 2006
Keyword
Bandwidth expansions, Correlated data, Correlation, Distributed sources, Energy efficient, Quantization, Source coding, Source-channel codes, Wireless sensor networks, Wireless telecommunication systems
National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-8446 (URN)10.1109/TCOMM.2006.881186 (DOI)000240699100002 ()2-s2.0-33749367017 (Scopus ID)
Note
QC 20100917Available from: 2008-05-15 Created: 2008-05-15 Last updated: 2011-12-27Bibliographically approved
5. Multiple Description Coding using Rotated Permutation Codes
Open this publication in new window or tab >>Multiple Description Coding using Rotated Permutation Codes
2006 (English)Report (Other academic)
Series
Trita-EE, ISSN 1653-5146 ; 2006:007
National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-8447 (URN)
Note
QC 20100920Available from: 2008-05-15 Created: 2008-05-15 Last updated: 2010-09-20Bibliographically approved
6. Improved Quantization in Multiple Description Coding by Correlating Transforms
Open this publication in new window or tab >>Improved Quantization in Multiple Description Coding by Correlating Transforms
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.

Keyword
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:nbn:se:kth:diva-8448 (URN)10.1109/MMSP.2004.1436601 (DOI)000224752800122 ()2-s2.0-13344259922 (Scopus ID)0-7803-8578-0 (ISBN)
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
7. On Source Decoding Based on Finite-Bandwidth Soft Information
Open this publication in new window or tab >>On Source Decoding Based on Finite-Bandwidth Soft Information
2005 (English)In: 2005 IEEE International Symposium on Information Theory (ISIT), 2005, 87-91 p.Conference paper, Published paper (Refereed)
Abstract [en]

Designing a communication system using joint source-channel coding in general makes it possible to achieve a better performance than when the source and channel codes are designed separately, especially under strict delay-constraints. The majority of work done in joint source-channel coding uses a discrete channel model, corresponding to an analog channel in conjunction with a hard decision modulation scheme. The performance of such a system can however be improved by using soft decision modulation. The main cost is a higher decoding complexity. An alternative is to quantize the soft information and store the pre-calculated soft decision values in a lookup table. In this paper we propose new methods for quantizing soft channel information, to be used in conjunction with soft-decision source decoding. We achieve a performance close to that of a system using unquantized soft information.

Keyword
Bandwidth, Communication channels (information theory), Communication systems, Computational complexity, Decoding, Modulation, Decoding complexity, Soft information, Source-channel coding, Strict delay-constraints
National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-8449 (URN)10.1109/ISIT.2005.1523298 (DOI)000234713800019 ()2-s2.0-33749452421 (Scopus ID)0-7803-9151-9 (ISBN)
Note
QC 20100920Available from: 2008-05-15 Created: 2008-05-15 Last updated: 2011-10-14Bibliographically approved

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Citation style
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  • en-GB
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  • nn-NO
  • nn-NB
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Output format
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